{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "c705f79a-a280-4b0e-92c0-b38c274c06de",
"showTitle": false,
"title": ""
}
},
"source": [
"#CI Challenge 2021 - Q4\n",
"## California 2020 Census data profiling\n",
"Sudha Kumar\n",
"12/13/21"
]
},
{
"cell_type": "markdown",
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "0670ed52-9368-48e2-9a8e-65176419ce77",
"showTitle": false,
"title": ""
}
},
"source": [
"Source data: California 2020 Census - California_CA.csv file from https://www.kaggle.com/zusmani/us-census-2020/version/3?select=California_CA.csv
\n",
"File size: 721 MB
\n",
"669171 x 401 columns
"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "fbb6cd48-0ff0-44f6-bd21-7bc9bf8816ca",
"showTitle": false,
"title": ""
}
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "6808f945-3b41-4ba0-98fa-6dd1d731b434",
"showTitle": false,
"title": ""
}
},
"source": [
"### Install packages"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "f4dd9727-a4c8-476f-a92a-f1d28b1e07d3",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"Python interpreter will be restarted.\n",
"Collecting seaborn\n",
" Downloading seaborn-0.11.2-py3-none-any.whl (292 kB)\n",
"Requirement already satisfied, skipping upgrade: pandas>=0.23 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from seaborn) (1.3.5)\n",
"Requirement already satisfied, skipping upgrade: matplotlib>=2.2 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from seaborn) (3.1.3)\n",
"Requirement already satisfied, skipping upgrade: scipy>=1.0 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from seaborn) (1.4.1)\n",
"Requirement already satisfied, skipping upgrade: numpy>=1.15 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from seaborn) (1.21.4)\n",
"Requirement already satisfied, skipping upgrade: python-dateutil>=2.7.3 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from pandas>=0.23->seaborn) (2.8.1)\n",
"Requirement already satisfied, skipping upgrade: pytz>=2017.3 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from pandas>=0.23->seaborn) (2019.3)\n",
"Requirement already satisfied, skipping upgrade: cycler>=0.10 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from matplotlib>=2.2->seaborn) (0.10.0)\n",
"Requirement already satisfied, skipping upgrade: kiwisolver>=1.0.1 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from matplotlib>=2.2->seaborn) (1.1.0)\n",
"Requirement already satisfied, skipping upgrade: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from matplotlib>=2.2->seaborn) (2.4.6)\n",
"Requirement already satisfied, skipping upgrade: six>=1.5 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from python-dateutil>=2.7.3->pandas>=0.23->seaborn) (1.12.0)\n",
"Requirement already satisfied, skipping upgrade: setuptools in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from kiwisolver>=1.0.1->matplotlib>=2.2->seaborn) (45.2.0.post20200210)\n",
"Installing collected packages: seaborn\n",
" Attempting uninstall: seaborn\n",
" Found existing installation: seaborn 0.10.0\n",
" Uninstalling seaborn-0.10.0:\n",
" Successfully uninstalled seaborn-0.10.0\n",
"Successfully installed seaborn-0.11.2\n",
"Python interpreter will be restarted.\n",
"
"
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "Python interpreter will be restarted.\nCollecting seaborn\n Downloading seaborn-0.11.2-py3-none-any.whl (292 kB)\nRequirement already satisfied, skipping upgrade: pandas>=0.23 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from seaborn) (1.3.5)\nRequirement already satisfied, skipping upgrade: matplotlib>=2.2 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from seaborn) (3.1.3)\nRequirement already satisfied, skipping upgrade: scipy>=1.0 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from seaborn) (1.4.1)\nRequirement already satisfied, skipping upgrade: numpy>=1.15 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from seaborn) (1.21.4)\nRequirement already satisfied, skipping upgrade: python-dateutil>=2.7.3 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from pandas>=0.23->seaborn) (2.8.1)\nRequirement already satisfied, skipping upgrade: pytz>=2017.3 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from pandas>=0.23->seaborn) (2019.3)\nRequirement already satisfied, skipping upgrade: cycler>=0.10 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from matplotlib>=2.2->seaborn) (0.10.0)\nRequirement already satisfied, skipping upgrade: kiwisolver>=1.0.1 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from matplotlib>=2.2->seaborn) (1.1.0)\nRequirement already satisfied, skipping upgrade: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from matplotlib>=2.2->seaborn) (2.4.6)\nRequirement already satisfied, skipping upgrade: six>=1.5 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from python-dateutil>=2.7.3->pandas>=0.23->seaborn) (1.12.0)\nRequirement already satisfied, skipping upgrade: setuptools in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from kiwisolver>=1.0.1->matplotlib>=2.2->seaborn) (45.2.0.post20200210)\nInstalling collected packages: seaborn\n Attempting uninstall: seaborn\n Found existing installation: seaborn 0.10.0\n Uninstalling seaborn-0.10.0:\n Successfully uninstalled seaborn-0.10.0\nSuccessfully installed seaborn-0.11.2\nPython interpreter will be restarted.\n
",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"%pip install -U seaborn"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "17c8e378-4f1d-470f-be3c-c12a94527c7f",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"Python interpreter will be restarted.\n",
"Requirement already satisfied: geopandas in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (0.10.2)\n",
"Requirement already satisfied: shapely>=1.6 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from geopandas) (1.8.0)\n",
"Requirement already satisfied: pyproj>=2.2.0 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from geopandas) (3.2.1)\n",
"Requirement already satisfied: fiona>=1.8 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from geopandas) (1.8.20)\n",
"Requirement already satisfied: pandas>=0.25.0 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from geopandas) (1.3.5)\n",
"Requirement already satisfied: certifi in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from pyproj>=2.2.0->geopandas) (2020.6.20)\n",
"Requirement already satisfied: munch in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from fiona>=1.8->geopandas) (2.5.0)\n",
"Requirement already satisfied: cligj>=0.5 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from fiona>=1.8->geopandas) (0.7.2)\n",
"Requirement already satisfied: setuptools in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from fiona>=1.8->geopandas) (45.2.0.post20200210)\n",
"Requirement already satisfied: click>=4.0 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from fiona>=1.8->geopandas) (7.1.2)\n",
"Requirement already satisfied: click-plugins>=1.0 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from fiona>=1.8->geopandas) (1.1.1)\n",
"Requirement already satisfied: attrs>=17 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from fiona>=1.8->geopandas) (21.2.0)\n",
"Requirement already satisfied: six>=1.7 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from fiona>=1.8->geopandas) (1.12.0)\n",
"Requirement already satisfied: python-dateutil>=2.7.3 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from pandas>=0.25.0->geopandas) (2.8.1)\n",
"Requirement already satisfied: numpy>=1.17.3; platform_machine != "aarch64" and platform_machine != "arm64" and python_version < "3.10" in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from pandas>=0.25.0->geopandas) (1.21.4)\n",
"Requirement already satisfied: pytz>=2017.3 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from pandas>=0.25.0->geopandas) (2019.3)\n",
"Python interpreter will be restarted.\n",
"
"
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "Python interpreter will be restarted.\nRequirement already satisfied: geopandas in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (0.10.2)\nRequirement already satisfied: shapely>=1.6 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from geopandas) (1.8.0)\nRequirement already satisfied: pyproj>=2.2.0 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from geopandas) (3.2.1)\nRequirement already satisfied: fiona>=1.8 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from geopandas) (1.8.20)\nRequirement already satisfied: pandas>=0.25.0 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from geopandas) (1.3.5)\nRequirement already satisfied: certifi in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from pyproj>=2.2.0->geopandas) (2020.6.20)\nRequirement already satisfied: munch in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from fiona>=1.8->geopandas) (2.5.0)\nRequirement already satisfied: cligj>=0.5 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from fiona>=1.8->geopandas) (0.7.2)\nRequirement already satisfied: setuptools in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from fiona>=1.8->geopandas) (45.2.0.post20200210)\nRequirement already satisfied: click>=4.0 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from fiona>=1.8->geopandas) (7.1.2)\nRequirement already satisfied: click-plugins>=1.0 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from fiona>=1.8->geopandas) (1.1.1)\nRequirement already satisfied: attrs>=17 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from fiona>=1.8->geopandas) (21.2.0)\nRequirement already satisfied: six>=1.7 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from fiona>=1.8->geopandas) (1.12.0)\nRequirement already satisfied: python-dateutil>=2.7.3 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from pandas>=0.25.0->geopandas) (2.8.1)\nRequirement already satisfied: numpy>=1.17.3; platform_machine != "aarch64" and platform_machine != "arm64" and python_version < "3.10" in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from pandas>=0.25.0->geopandas) (1.21.4)\nRequirement already satisfied: pytz>=2017.3 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from pandas>=0.25.0->geopandas) (2019.3)\nPython interpreter will be restarted.\n
",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"%pip install geopandas"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "f6a984a0-40a5-4227-a0b5-9ac2e6d054b7",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"Python interpreter will be restarted.\n",
"Collecting folium\n",
" Downloading folium-0.12.1.post1-py2.py3-none-any.whl (95 kB)\n",
"Requirement already satisfied: jinja2>=2.9 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from folium) (2.11.1)\n",
"Requirement already satisfied: requests in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from folium) (2.22.0)\n",
"Requirement already satisfied: numpy in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from folium) (1.21.4)\n",
"Collecting branca>=0.3.0\n",
" Downloading branca-0.4.2-py3-none-any.whl (24 kB)\n",
"Requirement already satisfied: MarkupSafe>=0.23 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from jinja2>=2.9->folium) (1.1.1)\n",
"Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from requests->folium) (1.25.8)\n",
"Requirement already satisfied: idna<2.9,>=2.5 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from requests->folium) (2.8)\n",
"Requirement already satisfied: chardet<3.1.0,>=3.0.2 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from requests->folium) (3.0.4)\n",
"Requirement already satisfied: certifi>=2017.4.17 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from requests->folium) (2020.6.20)\n",
"Installing collected packages: branca, folium\n",
"Successfully installed branca-0.4.2 folium-0.12.1.post1\n",
"Python interpreter will be restarted.\n",
"
"
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "Python interpreter will be restarted.\nCollecting folium\n Downloading folium-0.12.1.post1-py2.py3-none-any.whl (95 kB)\nRequirement already satisfied: jinja2>=2.9 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from folium) (2.11.1)\nRequirement already satisfied: requests in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from folium) (2.22.0)\nRequirement already satisfied: numpy in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from folium) (1.21.4)\nCollecting branca>=0.3.0\n Downloading branca-0.4.2-py3-none-any.whl (24 kB)\nRequirement already satisfied: MarkupSafe>=0.23 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from jinja2>=2.9->folium) (1.1.1)\nRequirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from requests->folium) (1.25.8)\nRequirement already satisfied: idna<2.9,>=2.5 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from requests->folium) (2.8)\nRequirement already satisfied: chardet<3.1.0,>=3.0.2 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from requests->folium) (3.0.4)\nRequirement already satisfied: certifi>=2017.4.17 in /local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages (from requests->folium) (2020.6.20)\nInstalling collected packages: branca, folium\nSuccessfully installed branca-0.4.2 folium-0.12.1.post1\nPython interpreter will be restarted.\n
",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"%pip install folium"
]
},
{
"cell_type": "markdown",
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "2c25c52f-a89f-48be-bdd3-c904e6a3cc50",
"showTitle": false,
"title": ""
}
},
"source": [
"### Import libraries"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "1d51ad56-89c8-446d-b238-88a4d93eccfa",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
""
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"import pandas as pd\n",
"import seaborn as sns\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"%matplotlib inline\n",
"import warnings\n",
"warnings.filterwarnings('ignore')\n",
"import databricks.koalas as ks"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "601d5b47-52b7-456e-a920-ffd876b873c4",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
""
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"from pyspark.sql.functions import regexp_replace, regexp_extract, col"
]
},
{
"cell_type": "markdown",
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "1a002c37-08b6-472d-a8aa-5f27a0d010d7",
"showTitle": false,
"title": ""
}
},
"source": [
"### Read csv file with pandas"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "c190277c-5e6d-4cf8-96a3-5cc598d92f8c",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
""
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"df_pd = pd.read_csv(\"/dbfs/FileStore/tables/tables/skum_test/ca_2020_census/California_CA.csv\", header='infer')"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "2787def2-d6f3-4618-b33b-f5c590daa1bc",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" FILEID | \n",
" STUSAB | \n",
" SUMLEV | \n",
" GEOVAR | \n",
" GEOCOMP | \n",
" CHARITER | \n",
" CIFSN_x | \n",
" LOGRECNO | \n",
" GEOID | \n",
" GEOCODE | \n",
" REGION | \n",
" DIVISION | \n",
" STATE | \n",
" STATENS | \n",
" COUNTY | \n",
" COUNTYCC | \n",
" COUNTYNS | \n",
" COUSUB | \n",
" COUSUBCC | \n",
" COUSUBNS | \n",
" SUBMCD | \n",
" SUBMCDCC | \n",
" SUBMCDNS | \n",
" ESTATE | \n",
" ESTATECC | \n",
" ESTATENS | \n",
" CONCIT | \n",
" CONCITCC | \n",
" CONCITNS | \n",
" PLACE | \n",
" PLACECC | \n",
" PLACENS | \n",
" TRACT | \n",
" BLKGRP | \n",
" BLOCK | \n",
" AIANHH | \n",
" AIHHTLI | \n",
" AIANHHFP | \n",
" AIANHHCC | \n",
" AIANHHNS | \n",
" ... | \n",
" P0040048 | \n",
" P0040049 | \n",
" P0040050 | \n",
" P0040051 | \n",
" P0040052 | \n",
" P0040053 | \n",
" P0040054 | \n",
" P0040055 | \n",
" P0040056 | \n",
" P0040057 | \n",
" P0040058 | \n",
" P0040059 | \n",
" P0040060 | \n",
" P0040061 | \n",
" P0040062 | \n",
" P0040063 | \n",
" P0040064 | \n",
" P0040065 | \n",
" P0040066 | \n",
" P0040067 | \n",
" P0040068 | \n",
" P0040069 | \n",
" P0040070 | \n",
" P0040071 | \n",
" P0040072 | \n",
" P0040073 | \n",
" H0010001 | \n",
" H0010002 | \n",
" H0010003 | \n",
" CIFSN_y.1 | \n",
" P0050001 | \n",
" P0050002 | \n",
" P0050003 | \n",
" P0050004 | \n",
" P0050005 | \n",
" P0050006 | \n",
" P0050007 | \n",
" P0050008 | \n",
" P0050009 | \n",
" P0050010 | \n",
"
\n",
" \n",
" \n",
" \n",
" | 0 | \n",
" PLST | \n",
" CA | \n",
" 50 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 2 | \n",
" 0500000US06001 | \n",
" 6001 | \n",
" 4 | \n",
" 9 | \n",
" 6 | \n",
" 1779778 | \n",
" 1.0 | \n",
" H1 | \n",
" 1675839.0 | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" ... | \n",
" 39 | \n",
" 472 | \n",
" 179 | \n",
" 22 | \n",
" 92 | \n",
" 41 | \n",
" 43 | \n",
" 2 | \n",
" 59 | \n",
" 5 | \n",
" 0 | \n",
" 8 | \n",
" 14 | \n",
" 3 | \n",
" 0 | \n",
" 1 | \n",
" 3 | \n",
" 63 | \n",
" 28 | \n",
" 21 | \n",
" 0 | \n",
" 7 | \n",
" 7 | \n",
" 0 | \n",
" 5 | \n",
" 5 | \n",
" 621958 | \n",
" 591636 | \n",
" 30322 | \n",
" 3 | \n",
" 53833 | \n",
" 10130 | \n",
" 3406 | \n",
" 397 | \n",
" 6218 | \n",
" 109 | \n",
" 43703 | \n",
" 17463 | \n",
" 421 | \n",
" 25819 | \n",
"
\n",
" \n",
" | 1 | \n",
" PLST | \n",
" CA | \n",
" 50 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 3 | \n",
" 0500000US06003 | \n",
" 6003 | \n",
" 4 | \n",
" 9 | \n",
" 6 | \n",
" 1779778 | \n",
" 3.0 | \n",
" H1 | \n",
" 1675840.0 | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" ... | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1540 | \n",
" 530 | \n",
" 1010 | \n",
" 3 | \n",
" 52 | \n",
" 1 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 51 | \n",
" 0 | \n",
" 0 | \n",
" 51 | \n",
"
\n",
" \n",
" | 2 | \n",
" PLST | \n",
" CA | \n",
" 50 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 4 | \n",
" 0500000US06005 | \n",
" 6005 | \n",
" 4 | \n",
" 9 | \n",
" 6 | \n",
" 1779778 | \n",
" 5.0 | \n",
" H1 | \n",
" 1675841.0 | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" ... | \n",
" 2 | \n",
" 6 | \n",
" 0 | \n",
" 2 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 3 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 3 | \n",
" 0 | \n",
" 2 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 18805 | \n",
" 15678 | \n",
" 3127 | \n",
" 3 | \n",
" 4311 | \n",
" 4098 | \n",
" 4045 | \n",
" 2 | \n",
" 51 | \n",
" 0 | \n",
" 213 | \n",
" 0 | \n",
" 0 | \n",
" 213 | \n",
"
\n",
" \n",
" | 3 | \n",
" PLST | \n",
" CA | \n",
" 50 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 5 | \n",
" 0500000US06007 | \n",
" 6007 | \n",
" 4 | \n",
" 9 | \n",
" 6 | \n",
" 1779778 | \n",
" 7.0 | \n",
" H1 | \n",
" 1675842.0 | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" ... | \n",
" 3 | \n",
" 19 | \n",
" 5 | \n",
" 1 | \n",
" 5 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 7 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 8 | \n",
" 5 | \n",
" 3 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 90133 | \n",
" 83268 | \n",
" 6865 | \n",
" 3 | \n",
" 4941 | \n",
" 1449 | \n",
" 496 | \n",
" 31 | \n",
" 902 | \n",
" 20 | \n",
" 3492 | \n",
" 2234 | \n",
" 0 | \n",
" 1258 | \n",
"
\n",
" \n",
" | 4 | \n",
" PLST | \n",
" CA | \n",
" 50 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 6 | \n",
" 0500000US06009 | \n",
" 6009 | \n",
" 4 | \n",
" 9 | \n",
" 6 | \n",
" 1779778 | \n",
" 9.0 | \n",
" H1 | \n",
" 1675885.0 | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" ... | \n",
" 0 | \n",
" 10 | \n",
" 2 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 4 | \n",
" 0 | \n",
" 0 | \n",
" 3 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 27422 | \n",
" 18758 | \n",
" 8664 | \n",
" 3 | \n",
" 461 | \n",
" 311 | \n",
" 170 | \n",
" 40 | \n",
" 101 | \n",
" 0 | \n",
" 150 | \n",
" 0 | \n",
" 0 | \n",
" 150 | \n",
"
\n",
" \n",
"
\n",
"
5 rows × 401 columns
\n",
"
\n\n
\n \n \n | \n FILEID | \n STUSAB | \n SUMLEV | \n GEOVAR | \n GEOCOMP | \n CHARITER | \n CIFSN_x | \n LOGRECNO | \n GEOID | \n GEOCODE | \n REGION | \n DIVISION | \n STATE | \n STATENS | \n COUNTY | \n COUNTYCC | \n COUNTYNS | \n COUSUB | \n COUSUBCC | \n COUSUBNS | \n SUBMCD | \n SUBMCDCC | \n SUBMCDNS | \n ESTATE | \n ESTATECC | \n ESTATENS | \n CONCIT | \n CONCITCC | \n CONCITNS | \n PLACE | \n PLACECC | \n PLACENS | \n TRACT | \n BLKGRP | \n BLOCK | \n AIANHH | \n AIHHTLI | \n AIANHHFP | \n AIANHHCC | \n AIANHHNS | \n ... | \n P0040048 | \n P0040049 | \n P0040050 | \n P0040051 | \n P0040052 | \n P0040053 | \n P0040054 | \n P0040055 | \n P0040056 | \n P0040057 | \n P0040058 | \n P0040059 | \n P0040060 | \n P0040061 | \n P0040062 | \n P0040063 | \n P0040064 | \n P0040065 | \n P0040066 | \n P0040067 | \n P0040068 | \n P0040069 | \n P0040070 | \n P0040071 | \n P0040072 | \n P0040073 | \n H0010001 | \n H0010002 | \n H0010003 | \n CIFSN_y.1 | \n P0050001 | \n P0050002 | \n P0050003 | \n P0050004 | \n P0050005 | \n P0050006 | \n P0050007 | \n P0050008 | \n P0050009 | \n P0050010 | \n
\n \n \n \n | 0 | \n PLST | \n CA | \n 50 | \n 0 | \n 0 | \n 0 | \n 0 | \n 2 | \n 0500000US06001 | \n 6001 | \n 4 | \n 9 | \n 6 | \n 1779778 | \n 1.0 | \n H1 | \n 1675839.0 | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n ... | \n 39 | \n 472 | \n 179 | \n 22 | \n 92 | \n 41 | \n 43 | \n 2 | \n 59 | \n 5 | \n 0 | \n 8 | \n 14 | \n 3 | \n 0 | \n 1 | \n 3 | \n 63 | \n 28 | \n 21 | \n 0 | \n 7 | \n 7 | \n 0 | \n 5 | \n 5 | \n 621958 | \n 591636 | \n 30322 | \n 3 | \n 53833 | \n 10130 | \n 3406 | \n 397 | \n 6218 | \n 109 | \n 43703 | \n 17463 | \n 421 | \n 25819 | \n
\n \n | 1 | \n PLST | \n CA | \n 50 | \n 0 | \n 0 | \n 0 | \n 0 | \n 3 | \n 0500000US06003 | \n 6003 | \n 4 | \n 9 | \n 6 | \n 1779778 | \n 3.0 | \n H1 | \n 1675840.0 | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n ... | \n 0 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 1540 | \n 530 | \n 1010 | \n 3 | \n 52 | \n 1 | \n 1 | \n 0 | \n 0 | \n 0 | \n 51 | \n 0 | \n 0 | \n 51 | \n
\n \n | 2 | \n PLST | \n CA | \n 50 | \n 0 | \n 0 | \n 0 | \n 0 | \n 4 | \n 0500000US06005 | \n 6005 | \n 4 | \n 9 | \n 6 | \n 1779778 | \n 5.0 | \n H1 | \n 1675841.0 | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n ... | \n 2 | \n 6 | \n 0 | \n 2 | \n 0 | \n 0 | \n 0 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 3 | \n 0 | \n 0 | \n 0 | \n 0 | \n 3 | \n 0 | \n 2 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 18805 | \n 15678 | \n 3127 | \n 3 | \n 4311 | \n 4098 | \n 4045 | \n 2 | \n 51 | \n 0 | \n 213 | \n 0 | \n 0 | \n 213 | \n
\n \n | 3 | \n PLST | \n CA | \n 50 | \n 0 | \n 0 | \n 0 | \n 0 | \n 5 | \n 0500000US06007 | \n 6007 | \n 4 | \n 9 | \n 6 | \n 1779778 | \n 7.0 | \n H1 | \n 1675842.0 | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n ... | \n 3 | \n 19 | \n 5 | \n 1 | \n 5 | \n 1 | \n 0 | \n 0 | \n 7 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 8 | \n 5 | \n 3 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 90133 | \n 83268 | \n 6865 | \n 3 | \n 4941 | \n 1449 | \n 496 | \n 31 | \n 902 | \n 20 | \n 3492 | \n 2234 | \n 0 | \n 1258 | \n
\n \n | 4 | \n PLST | \n CA | \n 50 | \n 0 | \n 0 | \n 0 | \n 0 | \n 6 | \n 0500000US06009 | \n 6009 | \n 4 | \n 9 | \n 6 | \n 1779778 | \n 9.0 | \n H1 | \n 1675885.0 | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n ... | \n 0 | \n 10 | \n 2 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 4 | \n 0 | \n 0 | \n 3 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 1 | \n 0 | \n 0 | \n 0 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 27422 | \n 18758 | \n 8664 | \n 3 | \n 461 | \n 311 | \n 170 | \n 40 | \n 101 | \n 0 | \n 150 | \n 0 | \n 0 | \n 150 | \n
\n \n
\n
5 rows × 401 columns
\n
Out[4]:
",
"type": "htmlSandbox"
}
},
"output_type": "display_data"
}
],
"source": [
"df_pd.head()"
]
},
{
"cell_type": "markdown",
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "75c01555-9bdb-4cb9-afce-aa784ac0585c",
"showTitle": false,
"title": ""
}
},
"source": [
"### Read csv file with spark"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "46deccff-f06f-4c56-8e70-eff6f7e12158",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
""
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "",
"datasetInfos": [
{
"name": "df_sp",
"schema": {
"fields": [
{
"metadata": {},
"name": "FILEID",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "STUSAB",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SUMLEV",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "GEOVAR",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "GEOCOMP",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "CHARITER",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "CIFSN_x6",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "LOGRECNO",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "GEOID",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "GEOCODE",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "REGION",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "DIVISION",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "STATE",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "STATENS",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "COUNTY",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "COUNTYCC",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "COUNTYNS",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "COUSUB",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "COUSUBCC",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "COUSUBNS",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SUBMCD",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SUBMCDCC",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SUBMCDNS",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "ESTATE",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "ESTATECC",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "ESTATENS",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "CONCIT",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "CONCITCC",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "CONCITNS",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "PLACE",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "PLACECC",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "PLACENS",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "TRACT",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "BLKGRP",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "BLOCK",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "AIANHH",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "AIHHTLI",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "AIANHHFP",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "AIANHHCC",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "AIANHHNS",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "AITS",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "AITSFP",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "AITSCC",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "AITSNS",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "TTRACT",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "TBLKGRP",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "ANRC",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "ANRCCC",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "ANRCNS",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "CBSA",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "MEMI",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "CSA",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "METDIV",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "NECTA",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "NMEMI",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "CNECTA",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "NECTADIV",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "CBSAPCI",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "NECTAPCI",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "UA",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "UATYPE",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "UR",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "CD116",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "CD118",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "CD119",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "CD120",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "CD121",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SLDU18",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SLDU22",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SLDU24",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SLDU26",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SLDU28",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SLDL18",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SLDL22",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SLDL24",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SLDL26",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SLDL28",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "VTD",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "VTDI",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "ZCTA",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SDELM",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SDSEC",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SDUNI",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "PUMA",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "AREALAND",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "AREAWATR",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "BASENAME",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "NAME",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "FUNCSTAT",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "GCUNI",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "POP100",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "HU100",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "INTPTLAT",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "INTPTLON",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "LSADC",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "PARTFLAG",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "UGA",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "CIFSN_y97",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010001",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010002",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010003",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010004",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010005",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010006",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010007",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010008",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010009",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010010",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010011",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010012",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010013",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010014",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010015",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010016",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010017",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010018",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010019",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010020",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010021",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010022",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010023",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010024",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010025",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010026",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010027",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010028",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010029",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010030",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010031",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010032",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010033",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010034",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010035",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010036",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010037",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010038",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010039",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010040",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010041",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010042",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010043",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010044",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010045",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010046",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010047",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010048",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010049",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010050",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010051",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010052",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010053",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010054",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010055",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010056",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010057",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010058",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010059",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010060",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010061",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010062",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010063",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010064",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010065",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010066",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010067",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010068",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010069",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010070",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010071",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020001",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020002",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020003",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020004",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020005",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020006",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020007",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020008",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020009",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020010",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020011",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020012",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020013",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020014",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020015",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020016",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020017",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020018",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020019",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020020",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020021",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020022",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020023",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020024",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020025",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020026",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020027",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020028",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020029",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020030",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020031",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020032",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020033",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020034",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020035",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020036",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020037",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020038",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020039",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020040",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020041",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020042",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020043",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020044",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020045",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020046",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020047",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020048",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020049",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020050",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020051",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020052",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020053",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020054",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020055",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020056",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020057",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020058",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020059",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020060",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020061",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020062",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020063",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020064",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020065",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020066",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020067",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020068",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020069",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020070",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020071",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020072",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0020073",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "CIFSN_x242",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030001",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030002",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030003",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030004",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030005",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030006",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030007",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030008",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030009",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030010",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030011",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030012",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030013",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030014",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030015",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030016",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030017",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030018",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030019",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030020",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030021",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030022",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030023",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030024",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030025",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030026",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030027",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030028",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030029",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030030",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030031",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030032",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030033",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030034",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030035",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030036",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030037",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030038",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030039",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030040",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030041",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030042",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030043",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030044",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030045",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030046",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030047",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030048",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030049",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030050",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030051",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030052",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030053",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030054",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030055",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030056",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030057",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030058",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030059",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030060",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030061",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030062",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030063",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030064",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030065",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030066",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030067",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030068",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030069",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030070",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0030071",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040001",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040002",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040003",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040004",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040005",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040006",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040007",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040008",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040009",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040010",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040011",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040012",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040013",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040014",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040015",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040016",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040017",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040018",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040019",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040020",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040021",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040022",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040023",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040024",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040025",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040026",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040027",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040028",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040029",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040030",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040031",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040032",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040033",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040034",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040035",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040036",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040037",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040038",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040039",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040040",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040041",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040042",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040043",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040044",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040045",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040046",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040047",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040048",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040049",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040050",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040051",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040052",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040053",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040054",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040055",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040056",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040057",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040058",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040059",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040060",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040061",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040062",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040063",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040064",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040065",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040066",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040067",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040068",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040069",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040070",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040071",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040072",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0040073",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "H0010001",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "H0010002",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "H0010003",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "CIFSN_y390",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0050001",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0050002",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0050003",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0050004",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0050005",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0050006",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0050007",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0050008",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0050009",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0050010",
"nullable": true,
"type": "string"
}
],
"type": "struct"
},
"tableIdentifier": null,
"typeStr": "pyspark.sql.dataframe.DataFrame"
}
],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"df_sp=spark.read.format(\"csv\").option(\"header\",\"true\").load(\"/FileStore/tables/tables/skum_test/ca_2020_census/California_CA.csv\")"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "1ad2c86a-1a0c-4e02-9686-fb31b5d82104",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
""
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"#df_sp.head()"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "f0e429b1-0836-4902-9fca-3707a328e29f",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
""
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"#df_sp.dtypes"
]
},
{
"cell_type": "markdown",
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "6990706f-436a-4fb9-997e-ea209c4715f1",
"showTitle": false,
"title": ""
}
},
"source": [
"### Read csv file with Spark using inferSchema option"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "1b51691b-0b21-4281-b2b5-a9397d2aabf9",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
""
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "",
"datasetInfos": [
{
"name": "census_df_sp",
"schema": {
"fields": [
{
"metadata": {},
"name": "FILEID",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "STUSAB",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SUMLEV",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "GEOVAR",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "GEOCOMP",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "CHARITER",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "CIFSN_x6",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "LOGRECNO",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "GEOID",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "GEOCODE",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "REGION",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "DIVISION",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "STATE",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "STATENS",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "COUNTY",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "COUNTYCC",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "COUNTYNS",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "COUSUB",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "COUSUBCC",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "COUSUBNS",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "SUBMCD",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SUBMCDCC",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SUBMCDNS",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "ESTATE",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "ESTATECC",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "ESTATENS",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "CONCIT",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "CONCITCC",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "CONCITNS",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "PLACE",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "PLACECC",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "PLACENS",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "TRACT",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "BLKGRP",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "BLOCK",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "AIANHH",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "AIHHTLI",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "AIANHHFP",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "AIANHHCC",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "AIANHHNS",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "AITS",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "AITSFP",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "AITSCC",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "AITSNS",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "TTRACT",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "TBLKGRP",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "ANRC",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "ANRCCC",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "ANRCNS",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "CBSA",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "MEMI",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "CSA",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "METDIV",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "NECTA",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "NMEMI",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "CNECTA",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "NECTADIV",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "CBSAPCI",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "NECTAPCI",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "UA",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "UATYPE",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "UR",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "CD116",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "CD118",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "CD119",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "CD120",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "CD121",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SLDU18",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "SLDU22",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SLDU24",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SLDU26",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SLDU28",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SLDL18",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "SLDL22",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SLDL24",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SLDL26",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SLDL28",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "VTD",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "VTDI",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "ZCTA",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "SDELM",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "SDSEC",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "SDUNI",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "PUMA",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "AREALAND",
"nullable": true,
"type": "long"
},
{
"metadata": {},
"name": "AREAWATR",
"nullable": true,
"type": "long"
},
{
"metadata": {},
"name": "BASENAME",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "NAME",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "FUNCSTAT",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "GCUNI",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "POP100",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "HU100",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "INTPTLAT",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "INTPTLON",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "LSADC",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "PARTFLAG",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "UGA",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "CIFSN_y97",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010001",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010002",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010003",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010004",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010005",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010006",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010007",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010008",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010009",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010010",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010011",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010012",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010013",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010014",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010015",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010016",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010017",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010018",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010019",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010020",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010021",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010022",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010023",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010024",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010025",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010026",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010027",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010028",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010029",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010030",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010031",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010032",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010033",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010034",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010035",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010036",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010037",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010038",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010039",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010040",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010041",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010042",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010043",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010044",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010045",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010046",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010047",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010048",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010049",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010050",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010051",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010052",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010053",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010054",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010055",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010056",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010057",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010058",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010059",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010060",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010061",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010062",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010063",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010064",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010065",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010066",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010067",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010068",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010069",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010070",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010071",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020001",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020002",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020003",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020004",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020005",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020006",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020007",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020008",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020009",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020010",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020011",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020012",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020013",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020014",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020015",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020016",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020017",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020018",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020019",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020020",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020021",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020022",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020023",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020024",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020025",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020026",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020027",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020028",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020029",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020030",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020031",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020032",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020033",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020034",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020035",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020036",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020037",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020038",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020039",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020040",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020041",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020042",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020043",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020044",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020045",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020046",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020047",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020048",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020049",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020050",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020051",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020052",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020053",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020054",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020055",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020056",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020057",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020058",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020059",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020060",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020061",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020062",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020063",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020064",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020065",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020066",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020067",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020068",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020069",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020070",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020071",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020072",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020073",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "CIFSN_x242",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030001",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030002",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030003",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030004",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030005",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030006",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030007",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030008",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030009",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030010",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030011",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030012",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030013",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030014",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030015",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030016",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030017",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030018",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030019",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030020",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030021",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030022",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030023",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030024",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030025",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030026",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030027",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030028",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030029",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030030",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030031",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030032",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030033",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030034",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030035",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030036",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030037",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030038",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030039",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030040",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030041",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030042",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030043",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030044",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030045",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030046",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030047",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030048",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030049",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030050",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030051",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030052",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030053",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030054",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030055",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030056",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030057",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030058",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030059",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030060",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030061",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030062",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030063",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030064",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030065",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030066",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030067",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030068",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030069",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030070",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0030071",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040001",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040002",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040003",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040004",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040005",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040006",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040007",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040008",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040009",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040010",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040011",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040012",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040013",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040014",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040015",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040016",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040017",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040018",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040019",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040020",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040021",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040022",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040023",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040024",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040025",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040026",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040027",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040028",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040029",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040030",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040031",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040032",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040033",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040034",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040035",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040036",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040037",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040038",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040039",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040040",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040041",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040042",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040043",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040044",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040045",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040046",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040047",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040048",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040049",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040050",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040051",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040052",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040053",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040054",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040055",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040056",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040057",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040058",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040059",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040060",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040061",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040062",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040063",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040064",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040065",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040066",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040067",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040068",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040069",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040070",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040071",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040072",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0040073",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "H0010001",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "H0010002",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "H0010003",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "CIFSN_y390",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0050001",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0050002",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0050003",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0050004",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0050005",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0050006",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0050007",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0050008",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0050009",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0050010",
"nullable": true,
"type": "integer"
}
],
"type": "struct"
},
"tableIdentifier": null,
"typeStr": "pyspark.sql.dataframe.DataFrame"
}
],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"census_df_sp = spark.read.option(\"inferSchema\", True).option(\"header\", True).csv(\"/FileStore/tables/tables/skum_test/ca_2020_census/California_CA.csv\")"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "882225b6-e23c-4a9d-93fa-0be540e78ef2",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
""
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"#display(census_df_sp)"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "13b41e85-8e68-4e88-8e9b-cae69fa27845",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
""
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"#display(census_df.summary())"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "ec4e01ac-0a48-41b2-a94b-05ee20286f99",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"Out[11]: 669171
"
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "Out[11]: 669171
",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"census_df_sp.count()"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "3b5ce639-e4b5-4848-8984-cb82011847e9",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"Out[12]: 401
"
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "Out[12]: 401
",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"len(census_df_sp.columns)"
]
},
{
"cell_type": "markdown",
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "8c07d541-47ef-446c-b787-b0601cdb0047",
"showTitle": false,
"title": ""
}
},
"source": [
"### Convert Spark dataframe to Koalas dataframe to perform Pandas like operations"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "45acc15b-8082-4321-8e3f-418eba65a3d9",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" FILEID | \n",
" STUSAB | \n",
" SUMLEV | \n",
" GEOVAR | \n",
" GEOCOMP | \n",
" CHARITER | \n",
" CIFSN_x6 | \n",
" LOGRECNO | \n",
" GEOID | \n",
" GEOCODE | \n",
" REGION | \n",
" DIVISION | \n",
" STATE | \n",
" STATENS | \n",
" COUNTY | \n",
" COUNTYCC | \n",
" COUNTYNS | \n",
" COUSUB | \n",
" COUSUBCC | \n",
" COUSUBNS | \n",
" SUBMCD | \n",
" SUBMCDCC | \n",
" SUBMCDNS | \n",
" ESTATE | \n",
" ESTATECC | \n",
" ESTATENS | \n",
" CONCIT | \n",
" CONCITCC | \n",
" CONCITNS | \n",
" PLACE | \n",
" PLACECC | \n",
" PLACENS | \n",
" TRACT | \n",
" BLKGRP | \n",
" BLOCK | \n",
" AIANHH | \n",
" AIHHTLI | \n",
" AIANHHFP | \n",
" AIANHHCC | \n",
" AIANHHNS | \n",
" AITS | \n",
" AITSFP | \n",
" AITSCC | \n",
" AITSNS | \n",
" TTRACT | \n",
" TBLKGRP | \n",
" ANRC | \n",
" ANRCCC | \n",
" ANRCNS | \n",
" CBSA | \n",
" MEMI | \n",
" CSA | \n",
" METDIV | \n",
" NECTA | \n",
" NMEMI | \n",
" CNECTA | \n",
" NECTADIV | \n",
" CBSAPCI | \n",
" NECTAPCI | \n",
" UA | \n",
" UATYPE | \n",
" UR | \n",
" CD116 | \n",
" CD118 | \n",
" CD119 | \n",
" CD120 | \n",
" CD121 | \n",
" SLDU18 | \n",
" SLDU22 | \n",
" SLDU24 | \n",
" SLDU26 | \n",
" SLDU28 | \n",
" SLDL18 | \n",
" SLDL22 | \n",
" SLDL24 | \n",
" SLDL26 | \n",
" SLDL28 | \n",
" VTD | \n",
" VTDI | \n",
" ZCTA | \n",
" SDELM | \n",
" SDSEC | \n",
" SDUNI | \n",
" PUMA | \n",
" AREALAND | \n",
" AREAWATR | \n",
" BASENAME | \n",
" NAME | \n",
" FUNCSTAT | \n",
" GCUNI | \n",
" POP100 | \n",
" HU100 | \n",
" INTPTLAT | \n",
" INTPTLON | \n",
" LSADC | \n",
" PARTFLAG | \n",
" UGA | \n",
" CIFSN_y97 | \n",
" P0010001 | \n",
" P0010002 | \n",
" P0010003 | \n",
" P0010004 | \n",
" P0010005 | \n",
" P0010006 | \n",
" P0010007 | \n",
" P0010008 | \n",
" P0010009 | \n",
" P0010010 | \n",
" P0010011 | \n",
" P0010012 | \n",
" P0010013 | \n",
" P0010014 | \n",
" P0010015 | \n",
" P0010016 | \n",
" P0010017 | \n",
" P0010018 | \n",
" P0010019 | \n",
" P0010020 | \n",
" P0010021 | \n",
" P0010022 | \n",
" P0010023 | \n",
" P0010024 | \n",
" P0010025 | \n",
" P0010026 | \n",
" P0010027 | \n",
" P0010028 | \n",
" P0010029 | \n",
" P0010030 | \n",
" P0010031 | \n",
" P0010032 | \n",
" P0010033 | \n",
" P0010034 | \n",
" P0010035 | \n",
" P0010036 | \n",
" P0010037 | \n",
" P0010038 | \n",
" P0010039 | \n",
" P0010040 | \n",
" P0010041 | \n",
" P0010042 | \n",
" P0010043 | \n",
" P0010044 | \n",
" P0010045 | \n",
" P0010046 | \n",
" P0010047 | \n",
" P0010048 | \n",
" P0010049 | \n",
" P0010050 | \n",
" P0010051 | \n",
" P0010052 | \n",
" P0010053 | \n",
" P0010054 | \n",
" P0010055 | \n",
" P0010056 | \n",
" P0010057 | \n",
" P0010058 | \n",
" P0010059 | \n",
" P0010060 | \n",
" P0010061 | \n",
" P0010062 | \n",
" P0010063 | \n",
" P0010064 | \n",
" P0010065 | \n",
" P0010066 | \n",
" P0010067 | \n",
" P0010068 | \n",
" P0010069 | \n",
" P0010070 | \n",
" P0010071 | \n",
" P0020001 | \n",
" P0020002 | \n",
" P0020003 | \n",
" P0020004 | \n",
" P0020005 | \n",
" P0020006 | \n",
" P0020007 | \n",
" P0020008 | \n",
" P0020009 | \n",
" P0020010 | \n",
" P0020011 | \n",
" P0020012 | \n",
" P0020013 | \n",
" P0020014 | \n",
" P0020015 | \n",
" P0020016 | \n",
" P0020017 | \n",
" P0020018 | \n",
" P0020019 | \n",
" P0020020 | \n",
" P0020021 | \n",
" P0020022 | \n",
" P0020023 | \n",
" P0020024 | \n",
" P0020025 | \n",
" P0020026 | \n",
" P0020027 | \n",
" P0020028 | \n",
" P0020029 | \n",
" P0020030 | \n",
" P0020031 | \n",
" P0020032 | \n",
" P0020033 | \n",
" P0020034 | \n",
" P0020035 | \n",
" P0020036 | \n",
" P0020037 | \n",
" P0020038 | \n",
" P0020039 | \n",
" P0020040 | \n",
" P0020041 | \n",
" P0020042 | \n",
" P0020043 | \n",
" P0020044 | \n",
" P0020045 | \n",
" P0020046 | \n",
" P0020047 | \n",
" P0020048 | \n",
" P0020049 | \n",
" P0020050 | \n",
" P0020051 | \n",
" P0020052 | \n",
" P0020053 | \n",
" P0020054 | \n",
" P0020055 | \n",
" P0020056 | \n",
" P0020057 | \n",
" P0020058 | \n",
" P0020059 | \n",
" P0020060 | \n",
" P0020061 | \n",
" P0020062 | \n",
" P0020063 | \n",
" P0020064 | \n",
" P0020065 | \n",
" P0020066 | \n",
" P0020067 | \n",
" P0020068 | \n",
" P0020069 | \n",
" P0020070 | \n",
" P0020071 | \n",
" P0020072 | \n",
" P0020073 | \n",
" CIFSN_x242 | \n",
" P0030001 | \n",
" P0030002 | \n",
" P0030003 | \n",
" P0030004 | \n",
" P0030005 | \n",
" P0030006 | \n",
" P0030007 | \n",
" P0030008 | \n",
" P0030009 | \n",
" P0030010 | \n",
" P0030011 | \n",
" P0030012 | \n",
" P0030013 | \n",
" P0030014 | \n",
" P0030015 | \n",
" P0030016 | \n",
" P0030017 | \n",
" P0030018 | \n",
" P0030019 | \n",
" P0030020 | \n",
" P0030021 | \n",
" P0030022 | \n",
" P0030023 | \n",
" P0030024 | \n",
" P0030025 | \n",
" P0030026 | \n",
" P0030027 | \n",
" P0030028 | \n",
" P0030029 | \n",
" P0030030 | \n",
" P0030031 | \n",
" P0030032 | \n",
" P0030033 | \n",
" P0030034 | \n",
" P0030035 | \n",
" P0030036 | \n",
" P0030037 | \n",
" P0030038 | \n",
" P0030039 | \n",
" P0030040 | \n",
" P0030041 | \n",
" P0030042 | \n",
" P0030043 | \n",
" P0030044 | \n",
" P0030045 | \n",
" P0030046 | \n",
" P0030047 | \n",
" P0030048 | \n",
" P0030049 | \n",
" P0030050 | \n",
" P0030051 | \n",
" P0030052 | \n",
" P0030053 | \n",
" P0030054 | \n",
" P0030055 | \n",
" P0030056 | \n",
" P0030057 | \n",
" P0030058 | \n",
" P0030059 | \n",
" P0030060 | \n",
" P0030061 | \n",
" P0030062 | \n",
" P0030063 | \n",
" P0030064 | \n",
" P0030065 | \n",
" P0030066 | \n",
" P0030067 | \n",
" P0030068 | \n",
" P0030069 | \n",
" P0030070 | \n",
" P0030071 | \n",
" P0040001 | \n",
" P0040002 | \n",
" P0040003 | \n",
" P0040004 | \n",
" P0040005 | \n",
" P0040006 | \n",
" P0040007 | \n",
" P0040008 | \n",
" P0040009 | \n",
" P0040010 | \n",
" P0040011 | \n",
" P0040012 | \n",
" P0040013 | \n",
" P0040014 | \n",
" P0040015 | \n",
" P0040016 | \n",
" P0040017 | \n",
" P0040018 | \n",
" P0040019 | \n",
" P0040020 | \n",
" P0040021 | \n",
" P0040022 | \n",
" P0040023 | \n",
" P0040024 | \n",
" P0040025 | \n",
" P0040026 | \n",
" P0040027 | \n",
" P0040028 | \n",
" P0040029 | \n",
" P0040030 | \n",
" P0040031 | \n",
" P0040032 | \n",
" P0040033 | \n",
" P0040034 | \n",
" P0040035 | \n",
" P0040036 | \n",
" P0040037 | \n",
" P0040038 | \n",
" P0040039 | \n",
" P0040040 | \n",
" P0040041 | \n",
" P0040042 | \n",
" P0040043 | \n",
" P0040044 | \n",
" P0040045 | \n",
" P0040046 | \n",
" P0040047 | \n",
" P0040048 | \n",
" P0040049 | \n",
" P0040050 | \n",
" P0040051 | \n",
" P0040052 | \n",
" P0040053 | \n",
" P0040054 | \n",
" P0040055 | \n",
" P0040056 | \n",
" P0040057 | \n",
" P0040058 | \n",
" P0040059 | \n",
" P0040060 | \n",
" P0040061 | \n",
" P0040062 | \n",
" P0040063 | \n",
" P0040064 | \n",
" P0040065 | \n",
" P0040066 | \n",
" P0040067 | \n",
" P0040068 | \n",
" P0040069 | \n",
" P0040070 | \n",
" P0040071 | \n",
" P0040072 | \n",
" P0040073 | \n",
" H0010001 | \n",
" H0010002 | \n",
" H0010003 | \n",
" CIFSN_y390 | \n",
" P0050001 | \n",
" P0050002 | \n",
" P0050003 | \n",
" P0050004 | \n",
" P0050005 | \n",
" P0050006 | \n",
" P0050007 | \n",
" P0050008 | \n",
" P0050009 | \n",
" P0050010 | \n",
"
\n",
" \n",
" \n",
" \n",
" | 0 | \n",
" PLST | \n",
" CA | \n",
" 50 | \n",
" 00 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 2 | \n",
" 0500000US06001 | \n",
" 06001 | \n",
" 4 | \n",
" 9 | \n",
" 6 | \n",
" 1779778 | \n",
" 1.0 | \n",
" H1 | \n",
" 1675839.0 | \n",
" NaN | \n",
" None | \n",
" NaN | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" None | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" None | \n",
" NaN | \n",
" None | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" None | \n",
" NaN | \n",
" None | \n",
" None | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" 41860.0 | \n",
" 1.0 | \n",
" 488.0 | \n",
" 36084.0 | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" NaN | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" NaN | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" NaN | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" None | \n",
" 1910017353 | \n",
" 216902808 | \n",
" Alameda | \n",
" Alameda County | \n",
" A | \n",
" None | \n",
" 1682353 | \n",
" 621958 | \n",
" 37.647139 | \n",
" -121.912488 | \n",
" 06 | \n",
" None | \n",
" NaN | \n",
" 1 | \n",
" 1682353 | \n",
" 1491537 | \n",
" 523836 | \n",
" 164879 | \n",
" 19659 | \n",
" 545261 | \n",
" 14123 | \n",
" 223779 | \n",
" 190816 | \n",
" 171703 | \n",
" 13579 | \n",
" 10768 | \n",
" 39888 | \n",
" 2293 | \n",
" 81119 | \n",
" 2682 | \n",
" 4125 | \n",
" 640 | \n",
" 4182 | \n",
" 707 | \n",
" 151 | \n",
" 3685 | \n",
" 3684 | \n",
" 3285 | \n",
" 915 | \n",
" 16711 | \n",
" 2460 | \n",
" 1652 | \n",
" 154 | \n",
" 1551 | \n",
" 1066 | \n",
" 137 | \n",
" 4502 | \n",
" 1704 | \n",
" 2121 | \n",
" 206 | \n",
" 176 | \n",
" 34 | \n",
" 231 | \n",
" 205 | \n",
" 194 | \n",
" 30 | \n",
" 64 | \n",
" 77 | \n",
" 20 | \n",
" 127 | \n",
" 2112 | \n",
" 404 | \n",
" 49 | \n",
" 819 | \n",
" 110 | \n",
" 159 | \n",
" 22 | \n",
" 124 | \n",
" 257 | \n",
" 21 | \n",
" 105 | \n",
" 25 | \n",
" 8 | \n",
" 0 | \n",
" 6 | \n",
" 3 | \n",
" 262 | \n",
" 95 | \n",
" 129 | \n",
" 14 | \n",
" 12 | \n",
" 12 | \n",
" 0 | \n",
" 28 | \n",
" 28 | \n",
" 1682353 | \n",
" 393749 | \n",
" 1288604 | \n",
" 1200067 | \n",
" 472277 | \n",
" 159499 | \n",
" 4131 | \n",
" 540511 | \n",
" 13209 | \n",
" 10440 | \n",
" 88537 | \n",
" 80792 | \n",
" 11936 | \n",
" 7033 | \n",
" 37058 | \n",
" 1921 | \n",
" 9261 | \n",
" 2221 | \n",
" 3799 | \n",
" 566 | \n",
" 1376 | \n",
" 452 | \n",
" 92 | \n",
" 59 | \n",
" 3343 | \n",
" 1125 | \n",
" 550 | \n",
" 6898 | \n",
" 1803 | \n",
" 1394 | \n",
" 116 | \n",
" 417 | \n",
" 710 | \n",
" 92 | \n",
" 67 | \n",
" 1444 | \n",
" 315 | \n",
" 15 | \n",
" 105 | \n",
" 17 | \n",
" 71 | \n",
" 157 | \n",
" 72 | \n",
" 13 | \n",
" 25 | \n",
" 7 | \n",
" 3 | \n",
" 55 | \n",
" 750 | \n",
" 300 | \n",
" 27 | \n",
" 120 | \n",
" 99 | \n",
" 71 | \n",
" 2 | \n",
" 78 | \n",
" 5 | \n",
" 0 | \n",
" 27 | \n",
" 14 | \n",
" 3 | \n",
" 0 | \n",
" 1 | \n",
" 3 | \n",
" 92 | \n",
" 48 | \n",
" 23 | \n",
" 7 | \n",
" 7 | \n",
" 7 | \n",
" 0 | \n",
" 5 | \n",
" 5 | \n",
" 2 | \n",
" 1338388 | \n",
" 1208791 | \n",
" 448581 | \n",
" 134525 | \n",
" 14919 | \n",
" 434901 | \n",
" 10921 | \n",
" 164944 | \n",
" 129597 | \n",
" 117917 | \n",
" 8444 | \n",
" 8557 | \n",
" 21834 | \n",
" 1557 | \n",
" 61432 | \n",
" 2112 | \n",
" 2214 | \n",
" 361 | \n",
" 2852 | \n",
" 426 | \n",
" 119 | \n",
" 2807 | \n",
" 2882 | \n",
" 1654 | \n",
" 666 | \n",
" 10250 | \n",
" 1748 | \n",
" 665 | \n",
" 75 | \n",
" 860 | \n",
" 585 | \n",
" 87 | \n",
" 3459 | \n",
" 1075 | \n",
" 930 | \n",
" 108 | \n",
" 100 | \n",
" 20 | \n",
" 172 | \n",
" 100 | \n",
" 97 | \n",
" 4 | \n",
" 40 | \n",
" 40 | \n",
" 9 | \n",
" 76 | \n",
" 1246 | \n",
" 229 | \n",
" 28 | \n",
" 585 | \n",
" 41 | \n",
" 81 | \n",
" 5 | \n",
" 75 | \n",
" 105 | \n",
" 12 | \n",
" 46 | \n",
" 25 | \n",
" 7 | \n",
" 0 | \n",
" 4 | \n",
" 3 | \n",
" 159 | \n",
" 51 | \n",
" 85 | \n",
" 7 | \n",
" 7 | \n",
" 9 | \n",
" 0 | \n",
" 25 | \n",
" 25 | \n",
" 1338388 | \n",
" 286178 | \n",
" 1052210 | \n",
" 994680 | \n",
" 410177 | \n",
" 131210 | \n",
" 3319 | \n",
" 431949 | \n",
" 10355 | \n",
" 7670 | \n",
" 57530 | \n",
" 52710 | \n",
" 7762 | \n",
" 5969 | \n",
" 20670 | \n",
" 1375 | \n",
" 7303 | \n",
" 1834 | \n",
" 2101 | \n",
" 332 | \n",
" 1126 | \n",
" 276 | \n",
" 83 | \n",
" 49 | \n",
" 2660 | \n",
" 709 | \n",
" 461 | \n",
" 4280 | \n",
" 1369 | \n",
" 575 | \n",
" 64 | \n",
" 279 | \n",
" 415 | \n",
" 60 | \n",
" 58 | \n",
" 942 | \n",
" 179 | \n",
" 4 | \n",
" 66 | \n",
" 8 | \n",
" 63 | \n",
" 84 | \n",
" 43 | \n",
" 1 | \n",
" 24 | \n",
" 7 | \n",
" 0 | \n",
" 39 | \n",
" 472 | \n",
" 179 | \n",
" 22 | \n",
" 92 | \n",
" 41 | \n",
" 43 | \n",
" 2 | \n",
" 59 | \n",
" 5 | \n",
" 0 | \n",
" 8 | \n",
" 14 | \n",
" 3 | \n",
" 0 | \n",
" 1 | \n",
" 3 | \n",
" 63 | \n",
" 28 | \n",
" 21 | \n",
" 0 | \n",
" 7 | \n",
" 7 | \n",
" 0 | \n",
" 5 | \n",
" 5 | \n",
" 621958 | \n",
" 591636 | \n",
" 30322 | \n",
" 3 | \n",
" 53833 | \n",
" 10130 | \n",
" 3406 | \n",
" 397 | \n",
" 6218 | \n",
" 109 | \n",
" 43703 | \n",
" 17463 | \n",
" 421 | \n",
" 25819 | \n",
"
\n",
" \n",
" | 1 | \n",
" PLST | \n",
" CA | \n",
" 50 | \n",
" 00 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 3 | \n",
" 0500000US06003 | \n",
" 06003 | \n",
" 4 | \n",
" 9 | \n",
" 6 | \n",
" 1779778 | \n",
" 3.0 | \n",
" H1 | \n",
" 1675840.0 | \n",
" NaN | \n",
" None | \n",
" NaN | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" None | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" None | \n",
" NaN | \n",
" None | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" None | \n",
" NaN | \n",
" None | \n",
" None | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" 99999.0 | \n",
" 9.0 | \n",
" 999.0 | \n",
" 99999.0 | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" NaN | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" NaN | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" NaN | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" None | \n",
" 1912292607 | \n",
" 12557304 | \n",
" Alpine | \n",
" Alpine County | \n",
" A | \n",
" None | \n",
" 1204 | \n",
" 1540 | \n",
" 38.621783 | \n",
" -119.798352 | \n",
" 06 | \n",
" None | \n",
" NaN | \n",
" 1 | \n",
" 1204 | \n",
" 1085 | \n",
" 814 | \n",
" 10 | \n",
" 236 | \n",
" 12 | \n",
" 0 | \n",
" 13 | \n",
" 119 | \n",
" 89 | \n",
" 5 | \n",
" 10 | \n",
" 6 | \n",
" 1 | \n",
" 50 | \n",
" 5 | \n",
" 2 | \n",
" 1 | \n",
" 0 | \n",
" 1 | \n",
" 1 | \n",
" 3 | \n",
" 2 | \n",
" 2 | \n",
" 0 | \n",
" 20 | \n",
" 2 | \n",
" 0 | \n",
" 4 | \n",
" 0 | \n",
" 0 | \n",
" 2 | \n",
" 3 | \n",
" 0 | \n",
" 4 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 1 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 9 | \n",
" 2 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 5 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1204 | \n",
" 84 | \n",
" 1120 | \n",
" 1044 | \n",
" 801 | \n",
" 10 | \n",
" 214 | \n",
" 12 | \n",
" 0 | \n",
" 7 | \n",
" 76 | \n",
" 56 | \n",
" 5 | \n",
" 10 | \n",
" 4 | \n",
" 1 | \n",
" 25 | \n",
" 5 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 1 | \n",
" 2 | \n",
" 1 | \n",
" 0 | \n",
" 15 | \n",
" 2 | \n",
" 0 | \n",
" 3 | \n",
" 0 | \n",
" 0 | \n",
" 2 | \n",
" 0 | \n",
" 0 | \n",
" 4 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 4 | \n",
" 2 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 2 | \n",
" 1009 | \n",
" 941 | \n",
" 736 | \n",
" 9 | \n",
" 174 | \n",
" 11 | \n",
" 0 | \n",
" 11 | \n",
" 68 | \n",
" 54 | \n",
" 5 | \n",
" 1 | \n",
" 2 | \n",
" 1 | \n",
" 40 | \n",
" 0 | \n",
" 2 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 1 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 8 | \n",
" 1 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 2 | \n",
" 0 | \n",
" 3 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 6 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 5 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1009 | \n",
" 62 | \n",
" 947 | \n",
" 915 | \n",
" 726 | \n",
" 9 | \n",
" 162 | \n",
" 11 | \n",
" 0 | \n",
" 7 | \n",
" 32 | \n",
" 26 | \n",
" 5 | \n",
" 1 | \n",
" 0 | \n",
" 1 | \n",
" 18 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 5 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 3 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1540 | \n",
" 530 | \n",
" 1010 | \n",
" 3 | \n",
" 52 | \n",
" 1 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 51 | \n",
" 0 | \n",
" 0 | \n",
" 51 | \n",
"
\n",
" \n",
" | 2 | \n",
" PLST | \n",
" CA | \n",
" 50 | \n",
" 00 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 4 | \n",
" 0500000US06005 | \n",
" 06005 | \n",
" 4 | \n",
" 9 | \n",
" 6 | \n",
" 1779778 | \n",
" 5.0 | \n",
" H1 | \n",
" 1675841.0 | \n",
" NaN | \n",
" None | \n",
" NaN | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" None | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" None | \n",
" NaN | \n",
" None | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" None | \n",
" NaN | \n",
" None | \n",
" None | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" 99999.0 | \n",
" 9.0 | \n",
" 999.0 | \n",
" 99999.0 | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" NaN | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" NaN | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" NaN | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" None | \n",
" 1539965777 | \n",
" 29438413 | \n",
" Amador | \n",
" Amador County | \n",
" A | \n",
" None | \n",
" 40474 | \n",
" 18805 | \n",
" 38.443549 | \n",
" -120.653858 | \n",
" 06 | \n",
" None | \n",
" NaN | \n",
" 1 | \n",
" 40474 | \n",
" 36596 | \n",
" 31104 | \n",
" 1236 | \n",
" 757 | \n",
" 582 | \n",
" 82 | \n",
" 2835 | \n",
" 3878 | \n",
" 3591 | \n",
" 163 | \n",
" 1123 | \n",
" 307 | \n",
" 59 | \n",
" 1804 | \n",
" 20 | \n",
" 5 | \n",
" 0 | \n",
" 6 | \n",
" 18 | \n",
" 2 | \n",
" 15 | \n",
" 59 | \n",
" 6 | \n",
" 4 | \n",
" 261 | \n",
" 28 | \n",
" 7 | \n",
" 4 | \n",
" 12 | \n",
" 34 | \n",
" 11 | \n",
" 87 | \n",
" 26 | \n",
" 19 | \n",
" 5 | \n",
" 2 | \n",
" 1 | \n",
" 1 | \n",
" 8 | \n",
" 1 | \n",
" 7 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 8 | \n",
" 17 | \n",
" 0 | \n",
" 2 | \n",
" 4 | \n",
" 1 | \n",
" 4 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 5 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 9 | \n",
" 5 | \n",
" 3 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 40474 | \n",
" 6014 | \n",
" 34460 | \n",
" 32393 | \n",
" 29725 | \n",
" 1215 | \n",
" 577 | \n",
" 554 | \n",
" 73 | \n",
" 249 | \n",
" 2067 | \n",
" 1948 | \n",
" 139 | \n",
" 977 | \n",
" 263 | \n",
" 52 | \n",
" 417 | \n",
" 13 | \n",
" 5 | \n",
" 0 | \n",
" 2 | \n",
" 9 | \n",
" 2 | \n",
" 9 | \n",
" 59 | \n",
" 1 | \n",
" 0 | \n",
" 107 | \n",
" 24 | \n",
" 4 | \n",
" 0 | \n",
" 6 | \n",
" 31 | \n",
" 7 | \n",
" 2 | \n",
" 22 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 8 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 2 | \n",
" 9 | \n",
" 0 | \n",
" 2 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 5 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 3 | \n",
" 0 | \n",
" 2 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 2 | \n",
" 34042 | \n",
" 31277 | \n",
" 26465 | \n",
" 1193 | \n",
" 578 | \n",
" 498 | \n",
" 60 | \n",
" 2483 | \n",
" 2765 | \n",
" 2617 | \n",
" 99 | \n",
" 831 | \n",
" 185 | \n",
" 42 | \n",
" 1353 | \n",
" 9 | \n",
" 0 | \n",
" 0 | \n",
" 2 | \n",
" 16 | \n",
" 0 | \n",
" 15 | \n",
" 59 | \n",
" 6 | \n",
" 0 | \n",
" 133 | \n",
" 13 | \n",
" 1 | \n",
" 0 | \n",
" 6 | \n",
" 15 | \n",
" 7 | \n",
" 56 | \n",
" 12 | \n",
" 10 | \n",
" 0 | \n",
" 2 | \n",
" 0 | \n",
" 1 | \n",
" 5 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 4 | \n",
" 10 | \n",
" 0 | \n",
" 2 | \n",
" 4 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 3 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 5 | \n",
" 1 | \n",
" 3 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 34042 | \n",
" 4550 | \n",
" 29492 | \n",
" 27953 | \n",
" 25572 | \n",
" 1184 | \n",
" 450 | \n",
" 478 | \n",
" 53 | \n",
" 216 | \n",
" 1539 | \n",
" 1471 | \n",
" 87 | \n",
" 755 | \n",
" 160 | \n",
" 40 | \n",
" 343 | \n",
" 9 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 7 | \n",
" 0 | \n",
" 9 | \n",
" 59 | \n",
" 1 | \n",
" 0 | \n",
" 59 | \n",
" 13 | \n",
" 1 | \n",
" 0 | \n",
" 6 | \n",
" 12 | \n",
" 7 | \n",
" 0 | \n",
" 12 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 5 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 2 | \n",
" 6 | \n",
" 0 | \n",
" 2 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 3 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 3 | \n",
" 0 | \n",
" 2 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 18805 | \n",
" 15678 | \n",
" 3127 | \n",
" 3 | \n",
" 4311 | \n",
" 4098 | \n",
" 4045 | \n",
" 2 | \n",
" 51 | \n",
" 0 | \n",
" 213 | \n",
" 0 | \n",
" 0 | \n",
" 213 | \n",
"
\n",
" \n",
" | 3 | \n",
" PLST | \n",
" CA | \n",
" 50 | \n",
" 00 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 5 | \n",
" 0500000US06007 | \n",
" 06007 | \n",
" 4 | \n",
" 9 | \n",
" 6 | \n",
" 1779778 | \n",
" 7.0 | \n",
" H1 | \n",
" 1675842.0 | \n",
" NaN | \n",
" None | \n",
" NaN | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" None | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" None | \n",
" NaN | \n",
" None | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" None | \n",
" NaN | \n",
" None | \n",
" None | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" 17020.0 | \n",
" 1.0 | \n",
" 999.0 | \n",
" 99999.0 | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" NaN | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" NaN | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" NaN | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" None | \n",
" 4238488698 | \n",
" 105260548 | \n",
" Butte | \n",
" Butte County | \n",
" A | \n",
" None | \n",
" 211632 | \n",
" 90133 | \n",
" 39.665336 | \n",
" -121.603209 | \n",
" 06 | \n",
" None | \n",
" NaN | \n",
" 1 | \n",
" 211632 | \n",
" 186947 | \n",
" 149557 | \n",
" 3644 | \n",
" 4492 | \n",
" 10533 | \n",
" 573 | \n",
" 18148 | \n",
" 24685 | \n",
" 22849 | \n",
" 1764 | \n",
" 6709 | \n",
" 2396 | \n",
" 388 | \n",
" 10402 | \n",
" 177 | \n",
" 93 | \n",
" 24 | \n",
" 157 | \n",
" 69 | \n",
" 22 | \n",
" 374 | \n",
" 172 | \n",
" 84 | \n",
" 18 | \n",
" 1652 | \n",
" 345 | \n",
" 97 | \n",
" 16 | \n",
" 124 | \n",
" 162 | \n",
" 61 | \n",
" 480 | \n",
" 182 | \n",
" 87 | \n",
" 21 | \n",
" 16 | \n",
" 1 | \n",
" 21 | \n",
" 4 | \n",
" 7 | \n",
" 0 | \n",
" 5 | \n",
" 16 | \n",
" 1 | \n",
" 6 | \n",
" 156 | \n",
" 30 | \n",
" 7 | \n",
" 41 | \n",
" 1 | \n",
" 6 | \n",
" 7 | \n",
" 29 | \n",
" 23 | \n",
" 2 | \n",
" 7 | \n",
" 0 | \n",
" 2 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 28 | \n",
" 12 | \n",
" 11 | \n",
" 2 | \n",
" 3 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 211632 | \n",
" 40112 | \n",
" 171520 | \n",
" 158046 | \n",
" 139651 | \n",
" 3320 | \n",
" 3050 | \n",
" 10333 | \n",
" 508 | \n",
" 1184 | \n",
" 13474 | \n",
" 12581 | \n",
" 1537 | \n",
" 5837 | \n",
" 2174 | \n",
" 348 | \n",
" 2129 | \n",
" 127 | \n",
" 80 | \n",
" 22 | \n",
" 55 | \n",
" 50 | \n",
" 21 | \n",
" 21 | \n",
" 154 | \n",
" 25 | \n",
" 1 | \n",
" 824 | \n",
" 263 | \n",
" 87 | \n",
" 16 | \n",
" 37 | \n",
" 122 | \n",
" 45 | \n",
" 31 | \n",
" 170 | \n",
" 15 | \n",
" 2 | \n",
" 6 | \n",
" 0 | \n",
" 16 | \n",
" 4 | \n",
" 2 | \n",
" 0 | \n",
" 5 | \n",
" 0 | \n",
" 0 | \n",
" 3 | \n",
" 55 | \n",
" 23 | \n",
" 2 | \n",
" 10 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 16 | \n",
" 3 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 14 | \n",
" 5 | \n",
" 6 | \n",
" 0 | \n",
" 3 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 2 | \n",
" 168339 | \n",
" 151623 | \n",
" 123122 | \n",
" 2773 | \n",
" 3324 | \n",
" 7963 | \n",
" 464 | \n",
" 13977 | \n",
" 16716 | \n",
" 15688 | \n",
" 852 | \n",
" 4862 | \n",
" 1444 | \n",
" 259 | \n",
" 7450 | \n",
" 105 | \n",
" 56 | \n",
" 13 | \n",
" 112 | \n",
" 41 | \n",
" 19 | \n",
" 270 | \n",
" 132 | \n",
" 65 | \n",
" 8 | \n",
" 921 | \n",
" 181 | \n",
" 50 | \n",
" 1 | \n",
" 59 | \n",
" 56 | \n",
" 26 | \n",
" 325 | \n",
" 107 | \n",
" 50 | \n",
" 18 | \n",
" 5 | \n",
" 0 | \n",
" 16 | \n",
" 4 | \n",
" 4 | \n",
" 0 | \n",
" 5 | \n",
" 8 | \n",
" 0 | \n",
" 6 | \n",
" 86 | \n",
" 7 | \n",
" 6 | \n",
" 19 | \n",
" 1 | \n",
" 6 | \n",
" 7 | \n",
" 20 | \n",
" 13 | \n",
" 2 | \n",
" 3 | \n",
" 0 | \n",
" 2 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 21 | \n",
" 12 | \n",
" 8 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 168339 | \n",
" 28425 | \n",
" 139914 | \n",
" 130683 | \n",
" 116628 | \n",
" 2606 | \n",
" 2317 | \n",
" 7828 | \n",
" 416 | \n",
" 888 | \n",
" 9231 | \n",
" 8761 | \n",
" 776 | \n",
" 4390 | \n",
" 1334 | \n",
" 234 | \n",
" 1637 | \n",
" 79 | \n",
" 50 | \n",
" 11 | \n",
" 39 | \n",
" 31 | \n",
" 18 | \n",
" 18 | \n",
" 120 | \n",
" 23 | \n",
" 1 | \n",
" 443 | \n",
" 144 | \n",
" 44 | \n",
" 1 | \n",
" 24 | \n",
" 49 | \n",
" 26 | \n",
" 25 | \n",
" 100 | \n",
" 4 | \n",
" 2 | \n",
" 0 | \n",
" 0 | \n",
" 12 | \n",
" 4 | \n",
" 0 | \n",
" 0 | \n",
" 5 | \n",
" 0 | \n",
" 0 | \n",
" 3 | \n",
" 19 | \n",
" 5 | \n",
" 1 | \n",
" 5 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 7 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 8 | \n",
" 5 | \n",
" 3 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 90133 | \n",
" 83268 | \n",
" 6865 | \n",
" 3 | \n",
" 4941 | \n",
" 1449 | \n",
" 496 | \n",
" 31 | \n",
" 902 | \n",
" 20 | \n",
" 3492 | \n",
" 2234 | \n",
" 0 | \n",
" 1258 | \n",
"
\n",
" \n",
" | 4 | \n",
" PLST | \n",
" CA | \n",
" 50 | \n",
" 00 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 6 | \n",
" 0500000US06009 | \n",
" 06009 | \n",
" 4 | \n",
" 9 | \n",
" 6 | \n",
" 1779778 | \n",
" 9.0 | \n",
" H1 | \n",
" 1675885.0 | \n",
" NaN | \n",
" None | \n",
" NaN | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" None | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" None | \n",
" NaN | \n",
" None | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" None | \n",
" NaN | \n",
" None | \n",
" None | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" 99999.0 | \n",
" 9.0 | \n",
" 999.0 | \n",
" 99999.0 | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" NaN | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" NaN | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" NaN | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" None | \n",
" 2641837359 | \n",
" 43789489 | \n",
" Calaveras | \n",
" Calaveras County | \n",
" A | \n",
" None | \n",
" 45292 | \n",
" 27422 | \n",
" 38.191068 | \n",
" -120.554106 | \n",
" 06 | \n",
" None | \n",
" NaN | \n",
" 1 | \n",
" 45292 | \n",
" 40264 | \n",
" 36315 | \n",
" 364 | \n",
" 747 | \n",
" 743 | \n",
" 100 | \n",
" 1995 | \n",
" 5028 | \n",
" 4706 | \n",
" 195 | \n",
" 1513 | \n",
" 428 | \n",
" 110 | \n",
" 2285 | \n",
" 13 | \n",
" 13 | \n",
" 0 | \n",
" 24 | \n",
" 6 | \n",
" 6 | \n",
" 43 | \n",
" 39 | \n",
" 28 | \n",
" 3 | \n",
" 285 | \n",
" 15 | \n",
" 8 | \n",
" 2 | \n",
" 28 | \n",
" 25 | \n",
" 24 | \n",
" 104 | \n",
" 39 | \n",
" 21 | \n",
" 0 | \n",
" 8 | \n",
" 0 | \n",
" 2 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 5 | \n",
" 0 | \n",
" 4 | \n",
" 31 | \n",
" 6 | \n",
" 1 | \n",
" 4 | \n",
" 0 | \n",
" 7 | \n",
" 0 | \n",
" 4 | \n",
" 0 | \n",
" 6 | \n",
" 3 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 5 | \n",
" 3 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 1 | \n",
" 0 | \n",
" 1 | \n",
" 1 | \n",
" 45292 | \n",
" 5865 | \n",
" 39427 | \n",
" 36548 | \n",
" 34668 | \n",
" 334 | \n",
" 497 | \n",
" 706 | \n",
" 75 | \n",
" 268 | \n",
" 2879 | \n",
" 2748 | \n",
" 182 | \n",
" 1370 | \n",
" 385 | \n",
" 109 | \n",
" 618 | \n",
" 13 | \n",
" 5 | \n",
" 0 | \n",
" 2 | \n",
" 0 | \n",
" 6 | \n",
" 5 | \n",
" 39 | \n",
" 11 | \n",
" 3 | \n",
" 112 | \n",
" 15 | \n",
" 6 | \n",
" 0 | \n",
" 10 | \n",
" 25 | \n",
" 8 | \n",
" 8 | \n",
" 36 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 3 | \n",
" 0 | \n",
" 0 | \n",
" 15 | \n",
" 3 | \n",
" 1 | \n",
" 4 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 4 | \n",
" 0 | \n",
" 0 | \n",
" 3 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 4 | \n",
" 3 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 2 | \n",
" 37337 | \n",
" 33724 | \n",
" 30591 | \n",
" 278 | \n",
" 613 | \n",
" 652 | \n",
" 82 | \n",
" 1508 | \n",
" 3613 | \n",
" 3411 | \n",
" 105 | \n",
" 1163 | \n",
" 237 | \n",
" 80 | \n",
" 1694 | \n",
" 11 | \n",
" 5 | \n",
" 0 | \n",
" 22 | \n",
" 1 | \n",
" 6 | \n",
" 36 | \n",
" 35 | \n",
" 13 | \n",
" 3 | \n",
" 184 | \n",
" 11 | \n",
" 6 | \n",
" 2 | \n",
" 20 | \n",
" 18 | \n",
" 15 | \n",
" 67 | \n",
" 24 | \n",
" 14 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 5 | \n",
" 0 | \n",
" 2 | \n",
" 16 | \n",
" 5 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 4 | \n",
" 0 | \n",
" 3 | \n",
" 3 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 2 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 37337 | \n",
" 4153 | \n",
" 33184 | \n",
" 31086 | \n",
" 29518 | \n",
" 254 | \n",
" 422 | \n",
" 621 | \n",
" 66 | \n",
" 205 | \n",
" 2098 | \n",
" 2006 | \n",
" 101 | \n",
" 1058 | \n",
" 221 | \n",
" 80 | \n",
" 474 | \n",
" 11 | \n",
" 5 | \n",
" 0 | \n",
" 2 | \n",
" 0 | \n",
" 6 | \n",
" 5 | \n",
" 35 | \n",
" 5 | \n",
" 3 | \n",
" 81 | \n",
" 11 | \n",
" 6 | \n",
" 0 | \n",
" 10 | \n",
" 18 | \n",
" 4 | \n",
" 8 | \n",
" 21 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 3 | \n",
" 0 | \n",
" 0 | \n",
" 10 | \n",
" 2 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 4 | \n",
" 0 | \n",
" 0 | \n",
" 3 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 27422 | \n",
" 18758 | \n",
" 8664 | \n",
" 3 | \n",
" 461 | \n",
" 311 | \n",
" 170 | \n",
" 40 | \n",
" 101 | \n",
" 0 | \n",
" 150 | \n",
" 0 | \n",
" 0 | \n",
" 150 | \n",
"
\n",
" \n",
"
\n",
"
\n\n
\n \n \n | \n FILEID | \n STUSAB | \n SUMLEV | \n GEOVAR | \n GEOCOMP | \n CHARITER | \n CIFSN_x6 | \n LOGRECNO | \n GEOID | \n GEOCODE | \n REGION | \n DIVISION | \n STATE | \n STATENS | \n COUNTY | \n COUNTYCC | \n COUNTYNS | \n COUSUB | \n COUSUBCC | \n COUSUBNS | \n SUBMCD | \n SUBMCDCC | \n SUBMCDNS | \n ESTATE | \n ESTATECC | \n ESTATENS | \n CONCIT | \n CONCITCC | \n CONCITNS | \n PLACE | \n PLACECC | \n PLACENS | \n TRACT | \n BLKGRP | \n BLOCK | \n AIANHH | \n AIHHTLI | \n AIANHHFP | \n AIANHHCC | \n AIANHHNS | \n AITS | \n AITSFP | \n AITSCC | \n AITSNS | \n TTRACT | \n TBLKGRP | \n ANRC | \n ANRCCC | \n ANRCNS | \n CBSA | \n MEMI | \n CSA | \n METDIV | \n NECTA | \n NMEMI | \n CNECTA | \n NECTADIV | \n CBSAPCI | \n NECTAPCI | \n UA | \n UATYPE | \n UR | \n CD116 | \n CD118 | \n CD119 | \n CD120 | \n CD121 | \n SLDU18 | \n SLDU22 | \n SLDU24 | \n SLDU26 | \n SLDU28 | \n SLDL18 | \n SLDL22 | \n SLDL24 | \n SLDL26 | \n SLDL28 | \n VTD | \n VTDI | \n ZCTA | \n SDELM | \n SDSEC | \n SDUNI | \n PUMA | \n AREALAND | \n AREAWATR | \n BASENAME | \n NAME | \n FUNCSTAT | \n GCUNI | \n POP100 | \n HU100 | \n INTPTLAT | \n INTPTLON | \n LSADC | \n PARTFLAG | \n UGA | \n CIFSN_y97 | \n P0010001 | \n P0010002 | \n P0010003 | \n P0010004 | \n P0010005 | \n P0010006 | \n P0010007 | \n P0010008 | \n P0010009 | \n P0010010 | \n P0010011 | \n P0010012 | \n P0010013 | \n P0010014 | \n P0010015 | \n P0010016 | \n P0010017 | \n P0010018 | \n P0010019 | \n P0010020 | \n P0010021 | \n P0010022 | \n P0010023 | \n P0010024 | \n P0010025 | \n P0010026 | \n P0010027 | \n P0010028 | \n P0010029 | \n P0010030 | \n P0010031 | \n P0010032 | \n P0010033 | \n P0010034 | \n P0010035 | \n P0010036 | \n P0010037 | \n P0010038 | \n P0010039 | \n P0010040 | \n P0010041 | \n P0010042 | \n P0010043 | \n P0010044 | \n P0010045 | \n P0010046 | \n P0010047 | \n P0010048 | \n P0010049 | \n P0010050 | \n P0010051 | \n P0010052 | \n P0010053 | \n P0010054 | \n P0010055 | \n P0010056 | \n P0010057 | \n P0010058 | \n P0010059 | \n P0010060 | \n P0010061 | \n P0010062 | \n P0010063 | \n P0010064 | \n P0010065 | \n P0010066 | \n P0010067 | \n P0010068 | \n P0010069 | \n P0010070 | \n P0010071 | \n P0020001 | \n P0020002 | \n P0020003 | \n P0020004 | \n P0020005 | \n P0020006 | \n P0020007 | \n P0020008 | \n P0020009 | \n P0020010 | \n P0020011 | \n P0020012 | \n P0020013 | \n P0020014 | \n P0020015 | \n P0020016 | \n P0020017 | \n P0020018 | \n P0020019 | \n P0020020 | \n P0020021 | \n P0020022 | \n P0020023 | \n P0020024 | \n P0020025 | \n P0020026 | \n P0020027 | \n P0020028 | \n P0020029 | \n P0020030 | \n P0020031 | \n P0020032 | \n P0020033 | \n P0020034 | \n P0020035 | \n P0020036 | \n P0020037 | \n P0020038 | \n P0020039 | \n P0020040 | \n P0020041 | \n P0020042 | \n P0020043 | \n P0020044 | \n P0020045 | \n P0020046 | \n P0020047 | \n P0020048 | \n P0020049 | \n P0020050 | \n P0020051 | \n P0020052 | \n P0020053 | \n P0020054 | \n P0020055 | \n P0020056 | \n P0020057 | \n P0020058 | \n P0020059 | \n P0020060 | \n P0020061 | \n P0020062 | \n P0020063 | \n P0020064 | \n P0020065 | \n P0020066 | \n P0020067 | \n P0020068 | \n P0020069 | \n P0020070 | \n P0020071 | \n P0020072 | \n P0020073 | \n CIFSN_x242 | \n P0030001 | \n P0030002 | \n P0030003 | \n P0030004 | \n P0030005 | \n P0030006 | \n P0030007 | \n P0030008 | \n P0030009 | \n P0030010 | \n P0030011 | \n P0030012 | \n P0030013 | \n P0030014 | \n P0030015 | \n P0030016 | \n P0030017 | \n P0030018 | \n P0030019 | \n P0030020 | \n P0030021 | \n P0030022 | \n P0030023 | \n P0030024 | \n P0030025 | \n P0030026 | \n P0030027 | \n P0030028 | \n P0030029 | \n P0030030 | \n P0030031 | \n P0030032 | \n P0030033 | \n P0030034 | \n P0030035 | \n P0030036 | \n P0030037 | \n P0030038 | \n P0030039 | \n P0030040 | \n P0030041 | \n P0030042 | \n P0030043 | \n P0030044 | \n P0030045 | \n P0030046 | \n P0030047 | \n P0030048 | \n P0030049 | \n P0030050 | \n P0030051 | \n P0030052 | \n P0030053 | \n P0030054 | \n P0030055 | \n P0030056 | \n P0030057 | \n P0030058 | \n P0030059 | \n P0030060 | \n P0030061 | \n P0030062 | \n P0030063 | \n P0030064 | \n P0030065 | \n P0030066 | \n P0030067 | \n P0030068 | \n P0030069 | \n P0030070 | \n P0030071 | \n P0040001 | \n P0040002 | \n P0040003 | \n P0040004 | \n P0040005 | \n P0040006 | \n P0040007 | \n P0040008 | \n P0040009 | \n P0040010 | \n P0040011 | \n P0040012 | \n P0040013 | \n P0040014 | \n P0040015 | \n P0040016 | \n P0040017 | \n P0040018 | \n P0040019 | \n P0040020 | \n P0040021 | \n P0040022 | \n P0040023 | \n P0040024 | \n P0040025 | \n P0040026 | \n P0040027 | \n P0040028 | \n P0040029 | \n P0040030 | \n P0040031 | \n P0040032 | \n P0040033 | \n P0040034 | \n P0040035 | \n P0040036 | \n P0040037 | \n P0040038 | \n P0040039 | \n P0040040 | \n P0040041 | \n P0040042 | \n P0040043 | \n P0040044 | \n P0040045 | \n P0040046 | \n P0040047 | \n P0040048 | \n P0040049 | \n P0040050 | \n P0040051 | \n P0040052 | \n P0040053 | \n P0040054 | \n P0040055 | \n P0040056 | \n P0040057 | \n P0040058 | \n P0040059 | \n P0040060 | \n P0040061 | \n P0040062 | \n P0040063 | \n P0040064 | \n P0040065 | \n P0040066 | \n P0040067 | \n P0040068 | \n P0040069 | \n P0040070 | \n P0040071 | \n P0040072 | \n P0040073 | \n H0010001 | \n H0010002 | \n H0010003 | \n CIFSN_y390 | \n P0050001 | \n P0050002 | \n P0050003 | \n P0050004 | \n P0050005 | \n P0050006 | \n P0050007 | \n P0050008 | \n P0050009 | \n P0050010 | \n
\n \n \n \n | 0 | \n PLST | \n CA | \n 50 | \n 00 | \n 0 | \n 0 | \n 0 | \n 2 | \n 0500000US06001 | \n 06001 | \n 4 | \n 9 | \n 6 | \n 1779778 | \n 1.0 | \n H1 | \n 1675839.0 | \n NaN | \n None | \n NaN | \n None | \n None | \n None | \n None | \n None | \n None | \n NaN | \n NaN | \n NaN | \n NaN | \n None | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n None | \n NaN | \n None | \n NaN | \n NaN | \n NaN | \n None | \n NaN | \n None | \n None | \n NaN | \n NaN | \n NaN | \n 41860.0 | \n 1.0 | \n 488.0 | \n 36084.0 | \n NaN | \n NaN | \n NaN | \n NaN | \n None | \n None | \n None | \n None | \n None | \n NaN | \n None | \n None | \n None | \n None | \n NaN | \n None | \n None | \n None | \n None | \n NaN | \n None | \n None | \n None | \n None | \n None | \n None | \n None | \n NaN | \n NaN | \n NaN | \n None | \n 1910017353 | \n 216902808 | \n Alameda | \n Alameda County | \n A | \n None | \n 1682353 | \n 621958 | \n 37.647139 | \n -121.912488 | \n 06 | \n None | \n NaN | \n 1 | \n 1682353 | \n 1491537 | \n 523836 | \n 164879 | \n 19659 | \n 545261 | \n 14123 | \n 223779 | \n 190816 | \n 171703 | \n 13579 | \n 10768 | \n 39888 | \n 2293 | \n 81119 | \n 2682 | \n 4125 | \n 640 | \n 4182 | \n 707 | \n 151 | \n 3685 | \n 3684 | \n 3285 | \n 915 | \n 16711 | \n 2460 | \n 1652 | \n 154 | \n 1551 | \n 1066 | \n 137 | \n 4502 | \n 1704 | \n 2121 | \n 206 | \n 176 | \n 34 | \n 231 | \n 205 | \n 194 | \n 30 | \n 64 | \n 77 | \n 20 | \n 127 | \n 2112 | \n 404 | \n 49 | \n 819 | \n 110 | \n 159 | \n 22 | \n 124 | \n 257 | \n 21 | \n 105 | \n 25 | \n 8 | \n 0 | \n 6 | \n 3 | \n 262 | \n 95 | \n 129 | \n 14 | \n 12 | \n 12 | \n 0 | \n 28 | \n 28 | \n 1682353 | \n 393749 | \n 1288604 | \n 1200067 | \n 472277 | \n 159499 | \n 4131 | \n 540511 | \n 13209 | \n 10440 | \n 88537 | \n 80792 | \n 11936 | \n 7033 | \n 37058 | \n 1921 | \n 9261 | \n 2221 | \n 3799 | \n 566 | \n 1376 | \n 452 | \n 92 | \n 59 | \n 3343 | \n 1125 | \n 550 | \n 6898 | \n 1803 | \n 1394 | \n 116 | \n 417 | \n 710 | \n 92 | \n 67 | \n 1444 | \n 315 | \n 15 | \n 105 | \n 17 | \n 71 | \n 157 | \n 72 | \n 13 | \n 25 | \n 7 | \n 3 | \n 55 | \n 750 | \n 300 | \n 27 | \n 120 | \n 99 | \n 71 | \n 2 | \n 78 | \n 5 | \n 0 | \n 27 | \n 14 | \n 3 | \n 0 | \n 1 | \n 3 | \n 92 | \n 48 | \n 23 | \n 7 | \n 7 | \n 7 | \n 0 | \n 5 | \n 5 | \n 2 | \n 1338388 | \n 1208791 | \n 448581 | \n 134525 | \n 14919 | \n 434901 | \n 10921 | \n 164944 | \n 129597 | \n 117917 | \n 8444 | \n 8557 | \n 21834 | \n 1557 | \n 61432 | \n 2112 | \n 2214 | \n 361 | \n 2852 | \n 426 | \n 119 | \n 2807 | \n 2882 | \n 1654 | \n 666 | \n 10250 | \n 1748 | \n 665 | \n 75 | \n 860 | \n 585 | \n 87 | \n 3459 | \n 1075 | \n 930 | \n 108 | \n 100 | \n 20 | \n 172 | \n 100 | \n 97 | \n 4 | \n 40 | \n 40 | \n 9 | \n 76 | \n 1246 | \n 229 | \n 28 | \n 585 | \n 41 | \n 81 | \n 5 | \n 75 | \n 105 | \n 12 | \n 46 | \n 25 | \n 7 | \n 0 | \n 4 | \n 3 | \n 159 | \n 51 | \n 85 | \n 7 | \n 7 | \n 9 | \n 0 | \n 25 | \n 25 | \n 1338388 | \n 286178 | \n 1052210 | \n 994680 | \n 410177 | \n 131210 | \n 3319 | \n 431949 | \n 10355 | \n 7670 | \n 57530 | \n 52710 | \n 7762 | \n 5969 | \n 20670 | \n 1375 | \n 7303 | \n 1834 | \n 2101 | \n 332 | \n 1126 | \n 276 | \n 83 | \n 49 | \n 2660 | \n 709 | \n 461 | \n 4280 | \n 1369 | \n 575 | \n 64 | \n 279 | \n 415 | \n 60 | \n 58 | \n 942 | \n 179 | \n 4 | \n 66 | \n 8 | \n 63 | \n 84 | \n 43 | \n 1 | \n 24 | \n 7 | \n 0 | \n 39 | \n 472 | \n 179 | \n 22 | \n 92 | \n 41 | \n 43 | \n 2 | \n 59 | \n 5 | \n 0 | \n 8 | \n 14 | \n 3 | \n 0 | \n 1 | \n 3 | \n 63 | \n 28 | \n 21 | \n 0 | \n 7 | \n 7 | \n 0 | \n 5 | \n 5 | \n 621958 | \n 591636 | \n 30322 | \n 3 | \n 53833 | \n 10130 | \n 3406 | \n 397 | \n 6218 | \n 109 | \n 43703 | \n 17463 | \n 421 | \n 25819 | \n
\n \n | 1 | \n PLST | \n CA | \n 50 | \n 00 | \n 0 | \n 0 | \n 0 | \n 3 | \n 0500000US06003 | \n 06003 | \n 4 | \n 9 | \n 6 | \n 1779778 | \n 3.0 | \n H1 | \n 1675840.0 | \n NaN | \n None | \n NaN | \n None | \n None | \n None | \n None | \n None | \n None | \n NaN | \n NaN | \n NaN | \n NaN | \n None | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n None | \n NaN | \n None | \n NaN | \n NaN | \n NaN | \n None | \n NaN | \n None | \n None | \n NaN | \n NaN | \n NaN | \n 99999.0 | \n 9.0 | \n 999.0 | \n 99999.0 | \n NaN | \n NaN | \n NaN | \n NaN | \n None | \n None | \n None | \n None | \n None | \n NaN | \n None | \n None | \n None | \n None | \n NaN | \n None | \n None | \n None | \n None | \n NaN | \n None | \n None | \n None | \n None | \n None | \n None | \n None | \n NaN | \n NaN | \n NaN | \n None | \n 1912292607 | \n 12557304 | \n Alpine | \n Alpine County | \n A | \n None | \n 1204 | \n 1540 | \n 38.621783 | \n -119.798352 | \n 06 | \n None | \n NaN | \n 1 | \n 1204 | \n 1085 | \n 814 | \n 10 | \n 236 | \n 12 | \n 0 | \n 13 | \n 119 | \n 89 | \n 5 | \n 10 | \n 6 | \n 1 | \n 50 | \n 5 | \n 2 | \n 1 | \n 0 | \n 1 | \n 1 | \n 3 | \n 2 | \n 2 | \n 0 | \n 20 | \n 2 | \n 0 | \n 4 | \n 0 | \n 0 | \n 2 | \n 3 | \n 0 | \n 4 | \n 1 | \n 0 | \n 0 | \n 1 | \n 1 | \n 0 | \n 1 | \n 0 | \n 1 | \n 0 | \n 0 | \n 9 | \n 2 | \n 0 | \n 0 | \n 0 | \n 1 | \n 0 | \n 0 | \n 1 | \n 0 | \n 5 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 1 | \n 0 | \n 0 | \n 0 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 1204 | \n 84 | \n 1120 | \n 1044 | \n 801 | \n 10 | \n 214 | \n 12 | \n 0 | \n 7 | \n 76 | \n 56 | \n 5 | \n 10 | \n 4 | \n 1 | \n 25 | \n 5 | \n 0 | \n 1 | \n 0 | \n 1 | \n 0 | \n 1 | \n 2 | \n 1 | \n 0 | \n 15 | \n 2 | \n 0 | \n 3 | \n 0 | \n 0 | \n 2 | \n 0 | \n 0 | \n 4 | \n 1 | \n 0 | \n 0 | \n 1 | \n 1 | \n 0 | \n 0 | \n 0 | \n 1 | \n 0 | \n 0 | \n 4 | \n 2 | \n 0 | \n 0 | \n 0 | \n 1 | \n 0 | \n 0 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 1 | \n 0 | \n 0 | \n 0 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 2 | \n 1009 | \n 941 | \n 736 | \n 9 | \n 174 | \n 11 | \n 0 | \n 11 | \n 68 | \n 54 | \n 5 | \n 1 | \n 2 | \n 1 | \n 40 | \n 0 | \n 2 | \n 0 | \n 0 | \n 0 | \n 1 | \n 1 | \n 0 | \n 1 | \n 0 | \n 8 | \n 1 | \n 0 | \n 1 | \n 0 | \n 0 | \n 0 | \n 2 | \n 0 | \n 3 | \n 0 | \n 0 | \n 0 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 6 | \n 0 | \n 0 | \n 0 | \n 0 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 5 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 1009 | \n 62 | \n 947 | \n 915 | \n 726 | \n 9 | \n 162 | \n 11 | \n 0 | \n 7 | \n 32 | \n 26 | \n 5 | \n 1 | \n 0 | \n 1 | \n 18 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 1 | \n 0 | \n 5 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 3 | \n 0 | \n 0 | \n 0 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 1540 | \n 530 | \n 1010 | \n 3 | \n 52 | \n 1 | \n 1 | \n 0 | \n 0 | \n 0 | \n 51 | \n 0 | \n 0 | \n 51 | \n
\n \n | 2 | \n PLST | \n CA | \n 50 | \n 00 | \n 0 | \n 0 | \n 0 | \n 4 | \n 0500000US06005 | \n 06005 | \n 4 | \n 9 | \n 6 | \n 1779778 | \n 5.0 | \n H1 | \n 1675841.0 | \n NaN | \n None | \n NaN | \n None | \n None | \n None | \n None | \n None | \n None | \n NaN | \n NaN | \n NaN | \n NaN | \n None | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n None | \n NaN | \n None | \n NaN | \n NaN | \n NaN | \n None | \n NaN | \n None | \n None | \n NaN | \n NaN | \n NaN | \n 99999.0 | \n 9.0 | \n 999.0 | \n 99999.0 | \n NaN | \n NaN | \n NaN | \n NaN | \n None | \n None | \n None | \n None | \n None | \n NaN | \n None | \n None | \n None | \n None | \n NaN | \n None | \n None | \n None | \n None | \n NaN | \n None | \n None | \n None | \n None | \n None | \n None | \n None | \n NaN | \n NaN | \n NaN | \n None | \n 1539965777 | \n 29438413 | \n Amador | \n Amador County | \n A | \n None | \n 40474 | \n 18805 | \n 38.443549 | \n -120.653858 | \n 06 | \n None | \n NaN | \n 1 | \n 40474 | \n 36596 | \n 31104 | \n 1236 | \n 757 | \n 582 | \n 82 | \n 2835 | \n 3878 | \n 3591 | \n 163 | \n 1123 | \n 307 | \n 59 | \n 1804 | \n 20 | \n 5 | \n 0 | \n 6 | \n 18 | \n 2 | \n 15 | \n 59 | \n 6 | \n 4 | \n 261 | \n 28 | \n 7 | \n 4 | \n 12 | \n 34 | \n 11 | \n 87 | \n 26 | \n 19 | \n 5 | \n 2 | \n 1 | \n 1 | \n 8 | \n 1 | \n 7 | \n 0 | \n 0 | \n 0 | \n 8 | \n 17 | \n 0 | \n 2 | \n 4 | \n 1 | \n 4 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 5 | \n 0 | \n 0 | \n 0 | \n 0 | \n 9 | \n 5 | \n 3 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 40474 | \n 6014 | \n 34460 | \n 32393 | \n 29725 | \n 1215 | \n 577 | \n 554 | \n 73 | \n 249 | \n 2067 | \n 1948 | \n 139 | \n 977 | \n 263 | \n 52 | \n 417 | \n 13 | \n 5 | \n 0 | \n 2 | \n 9 | \n 2 | \n 9 | \n 59 | \n 1 | \n 0 | \n 107 | \n 24 | \n 4 | \n 0 | \n 6 | \n 31 | \n 7 | \n 2 | \n 22 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 8 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 2 | \n 9 | \n 0 | \n 2 | \n 0 | \n 1 | \n 0 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 5 | \n 0 | \n 0 | \n 0 | \n 0 | \n 3 | \n 0 | \n 2 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 2 | \n 34042 | \n 31277 | \n 26465 | \n 1193 | \n 578 | \n 498 | \n 60 | \n 2483 | \n 2765 | \n 2617 | \n 99 | \n 831 | \n 185 | \n 42 | \n 1353 | \n 9 | \n 0 | \n 0 | \n 2 | \n 16 | \n 0 | \n 15 | \n 59 | \n 6 | \n 0 | \n 133 | \n 13 | \n 1 | \n 0 | \n 6 | \n 15 | \n 7 | \n 56 | \n 12 | \n 10 | \n 0 | \n 2 | \n 0 | \n 1 | \n 5 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 4 | \n 10 | \n 0 | \n 2 | \n 4 | \n 0 | \n 0 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 3 | \n 0 | \n 0 | \n 0 | \n 0 | \n 5 | \n 1 | \n 3 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 34042 | \n 4550 | \n 29492 | \n 27953 | \n 25572 | \n 1184 | \n 450 | \n 478 | \n 53 | \n 216 | \n 1539 | \n 1471 | \n 87 | \n 755 | \n 160 | \n 40 | \n 343 | \n 9 | \n 0 | \n 0 | \n 1 | \n 7 | \n 0 | \n 9 | \n 59 | \n 1 | \n 0 | \n 59 | \n 13 | \n 1 | \n 0 | \n 6 | \n 12 | \n 7 | \n 0 | \n 12 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 5 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 2 | \n 6 | \n 0 | \n 2 | \n 0 | \n 0 | \n 0 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 3 | \n 0 | \n 0 | \n 0 | \n 0 | \n 3 | \n 0 | \n 2 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 18805 | \n 15678 | \n 3127 | \n 3 | \n 4311 | \n 4098 | \n 4045 | \n 2 | \n 51 | \n 0 | \n 213 | \n 0 | \n 0 | \n 213 | \n
\n \n | 3 | \n PLST | \n CA | \n 50 | \n 00 | \n 0 | \n 0 | \n 0 | \n 5 | \n 0500000US06007 | \n 06007 | \n 4 | \n 9 | \n 6 | \n 1779778 | \n 7.0 | \n H1 | \n 1675842.0 | \n NaN | \n None | \n NaN | \n None | \n None | \n None | \n None | \n None | \n None | \n NaN | \n NaN | \n NaN | \n NaN | \n None | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n None | \n NaN | \n None | \n NaN | \n NaN | \n NaN | \n None | \n NaN | \n None | \n None | \n NaN | \n NaN | \n NaN | \n 17020.0 | \n 1.0 | \n 999.0 | \n 99999.0 | \n NaN | \n NaN | \n NaN | \n NaN | \n None | \n None | \n None | \n None | \n None | \n NaN | \n None | \n None | \n None | \n None | \n NaN | \n None | \n None | \n None | \n None | \n NaN | \n None | \n None | \n None | \n None | \n None | \n None | \n None | \n NaN | \n NaN | \n NaN | \n None | \n 4238488698 | \n 105260548 | \n Butte | \n Butte County | \n A | \n None | \n 211632 | \n 90133 | \n 39.665336 | \n -121.603209 | \n 06 | \n None | \n NaN | \n 1 | \n 211632 | \n 186947 | \n 149557 | \n 3644 | \n 4492 | \n 10533 | \n 573 | \n 18148 | \n 24685 | \n 22849 | \n 1764 | \n 6709 | \n 2396 | \n 388 | \n 10402 | \n 177 | \n 93 | \n 24 | \n 157 | \n 69 | \n 22 | \n 374 | \n 172 | \n 84 | \n 18 | \n 1652 | \n 345 | \n 97 | \n 16 | \n 124 | \n 162 | \n 61 | \n 480 | \n 182 | \n 87 | \n 21 | \n 16 | \n 1 | \n 21 | \n 4 | \n 7 | \n 0 | \n 5 | \n 16 | \n 1 | \n 6 | \n 156 | \n 30 | \n 7 | \n 41 | \n 1 | \n 6 | \n 7 | \n 29 | \n 23 | \n 2 | \n 7 | \n 0 | \n 2 | \n 0 | \n 0 | \n 1 | \n 28 | \n 12 | \n 11 | \n 2 | \n 3 | \n 0 | \n 0 | \n 0 | \n 0 | \n 211632 | \n 40112 | \n 171520 | \n 158046 | \n 139651 | \n 3320 | \n 3050 | \n 10333 | \n 508 | \n 1184 | \n 13474 | \n 12581 | \n 1537 | \n 5837 | \n 2174 | \n 348 | \n 2129 | \n 127 | \n 80 | \n 22 | \n 55 | \n 50 | \n 21 | \n 21 | \n 154 | \n 25 | \n 1 | \n 824 | \n 263 | \n 87 | \n 16 | \n 37 | \n 122 | \n 45 | \n 31 | \n 170 | \n 15 | \n 2 | \n 6 | \n 0 | \n 16 | \n 4 | \n 2 | \n 0 | \n 5 | \n 0 | \n 0 | \n 3 | \n 55 | \n 23 | \n 2 | \n 10 | \n 1 | \n 0 | \n 0 | \n 16 | \n 3 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 14 | \n 5 | \n 6 | \n 0 | \n 3 | \n 0 | \n 0 | \n 0 | \n 0 | \n 2 | \n 168339 | \n 151623 | \n 123122 | \n 2773 | \n 3324 | \n 7963 | \n 464 | \n 13977 | \n 16716 | \n 15688 | \n 852 | \n 4862 | \n 1444 | \n 259 | \n 7450 | \n 105 | \n 56 | \n 13 | \n 112 | \n 41 | \n 19 | \n 270 | \n 132 | \n 65 | \n 8 | \n 921 | \n 181 | \n 50 | \n 1 | \n 59 | \n 56 | \n 26 | \n 325 | \n 107 | \n 50 | \n 18 | \n 5 | \n 0 | \n 16 | \n 4 | \n 4 | \n 0 | \n 5 | \n 8 | \n 0 | \n 6 | \n 86 | \n 7 | \n 6 | \n 19 | \n 1 | \n 6 | \n 7 | \n 20 | \n 13 | \n 2 | \n 3 | \n 0 | \n 2 | \n 0 | \n 0 | \n 0 | \n 21 | \n 12 | \n 8 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 168339 | \n 28425 | \n 139914 | \n 130683 | \n 116628 | \n 2606 | \n 2317 | \n 7828 | \n 416 | \n 888 | \n 9231 | \n 8761 | \n 776 | \n 4390 | \n 1334 | \n 234 | \n 1637 | \n 79 | \n 50 | \n 11 | \n 39 | \n 31 | \n 18 | \n 18 | \n 120 | \n 23 | \n 1 | \n 443 | \n 144 | \n 44 | \n 1 | \n 24 | \n 49 | \n 26 | \n 25 | \n 100 | \n 4 | \n 2 | \n 0 | \n 0 | \n 12 | \n 4 | \n 0 | \n 0 | \n 5 | \n 0 | \n 0 | \n 3 | \n 19 | \n 5 | \n 1 | \n 5 | \n 1 | \n 0 | \n 0 | \n 7 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 8 | \n 5 | \n 3 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 90133 | \n 83268 | \n 6865 | \n 3 | \n 4941 | \n 1449 | \n 496 | \n 31 | \n 902 | \n 20 | \n 3492 | \n 2234 | \n 0 | \n 1258 | \n
\n \n | 4 | \n PLST | \n CA | \n 50 | \n 00 | \n 0 | \n 0 | \n 0 | \n 6 | \n 0500000US06009 | \n 06009 | \n 4 | \n 9 | \n 6 | \n 1779778 | \n 9.0 | \n H1 | \n 1675885.0 | \n NaN | \n None | \n NaN | \n None | \n None | \n None | \n None | \n None | \n None | \n NaN | \n NaN | \n NaN | \n NaN | \n None | \n NaN | \n NaN | \n NaN | \n NaN | \n NaN | \n None | \n NaN | \n None | \n NaN | \n NaN | \n NaN | \n None | \n NaN | \n None | \n None | \n NaN | \n NaN | \n NaN | \n 99999.0 | \n 9.0 | \n 999.0 | \n 99999.0 | \n NaN | \n NaN | \n NaN | \n NaN | \n None | \n None | \n None | \n None | \n None | \n NaN | \n None | \n None | \n None | \n None | \n NaN | \n None | \n None | \n None | \n None | \n NaN | \n None | \n None | \n None | \n None | \n None | \n None | \n None | \n NaN | \n NaN | \n NaN | \n None | \n 2641837359 | \n 43789489 | \n Calaveras | \n Calaveras County | \n A | \n None | \n 45292 | \n 27422 | \n 38.191068 | \n -120.554106 | \n 06 | \n None | \n NaN | \n 1 | \n 45292 | \n 40264 | \n 36315 | \n 364 | \n 747 | \n 743 | \n 100 | \n 1995 | \n 5028 | \n 4706 | \n 195 | \n 1513 | \n 428 | \n 110 | \n 2285 | \n 13 | \n 13 | \n 0 | \n 24 | \n 6 | \n 6 | \n 43 | \n 39 | \n 28 | \n 3 | \n 285 | \n 15 | \n 8 | \n 2 | \n 28 | \n 25 | \n 24 | \n 104 | \n 39 | \n 21 | \n 0 | \n 8 | \n 0 | \n 2 | \n 0 | \n 0 | \n 0 | \n 0 | \n 5 | \n 0 | \n 4 | \n 31 | \n 6 | \n 1 | \n 4 | \n 0 | \n 7 | \n 0 | \n 4 | \n 0 | \n 6 | \n 3 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 5 | \n 3 | \n 0 | \n 0 | \n 1 | \n 1 | \n 0 | \n 1 | \n 1 | \n 45292 | \n 5865 | \n 39427 | \n 36548 | \n 34668 | \n 334 | \n 497 | \n 706 | \n 75 | \n 268 | \n 2879 | \n 2748 | \n 182 | \n 1370 | \n 385 | \n 109 | \n 618 | \n 13 | \n 5 | \n 0 | \n 2 | \n 0 | \n 6 | \n 5 | \n 39 | \n 11 | \n 3 | \n 112 | \n 15 | \n 6 | \n 0 | \n 10 | \n 25 | \n 8 | \n 8 | \n 36 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 3 | \n 0 | \n 0 | \n 15 | \n 3 | \n 1 | \n 4 | \n 0 | \n 0 | \n 0 | \n 4 | \n 0 | \n 0 | \n 3 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 4 | \n 3 | \n 0 | \n 0 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 2 | \n 37337 | \n 33724 | \n 30591 | \n 278 | \n 613 | \n 652 | \n 82 | \n 1508 | \n 3613 | \n 3411 | \n 105 | \n 1163 | \n 237 | \n 80 | \n 1694 | \n 11 | \n 5 | \n 0 | \n 22 | \n 1 | \n 6 | \n 36 | \n 35 | \n 13 | \n 3 | \n 184 | \n 11 | \n 6 | \n 2 | \n 20 | \n 18 | \n 15 | \n 67 | \n 24 | \n 14 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 5 | \n 0 | \n 2 | \n 16 | \n 5 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 4 | \n 0 | \n 3 | \n 3 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 2 | \n 0 | \n 0 | \n 0 | \n 1 | \n 1 | \n 0 | \n 0 | \n 0 | \n 37337 | \n 4153 | \n 33184 | \n 31086 | \n 29518 | \n 254 | \n 422 | \n 621 | \n 66 | \n 205 | \n 2098 | \n 2006 | \n 101 | \n 1058 | \n 221 | \n 80 | \n 474 | \n 11 | \n 5 | \n 0 | \n 2 | \n 0 | \n 6 | \n 5 | \n 35 | \n 5 | \n 3 | \n 81 | \n 11 | \n 6 | \n 0 | \n 10 | \n 18 | \n 4 | \n 8 | \n 21 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 3 | \n 0 | \n 0 | \n 10 | \n 2 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 4 | \n 0 | \n 0 | \n 3 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 1 | \n 0 | \n 0 | \n 0 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 27422 | \n 18758 | \n 8664 | \n 3 | \n 461 | \n 311 | \n 170 | \n 40 | \n 101 | \n 0 | \n 150 | \n 0 | \n 0 | \n 150 | \n
\n \n
\n
Out[13]:
",
"type": "htmlSandbox"
}
},
"output_type": "display_data"
}
],
"source": [
"import databricks.koalas as ks\n",
"\n",
"census_ks = census_df_sp.to_koalas()\n",
"census_ks.head()"
]
},
{
"cell_type": "markdown",
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "fe0b39c8-f91d-462c-98cb-83acaaaba6b2",
"showTitle": false,
"title": ""
}
},
"source": [
"### Read csv file with Koalas"
]
},
{
"cell_type": "markdown",
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "c9d51ece-ba71-4767-88e6-cc5c0b190acf",
"showTitle": false,
"title": ""
}
},
"source": [
"Koalas is an open-source Python package that implements the pandas API on top of Apache Spark, to make the pandas API scalable to big data."
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "d3ef6fc8-a354-405c-a7b1-ae5def9390e0",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
""
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"import databricks.koalas as ks\n",
"data_ks = ks.read_csv(\"/FileStore/tables/tables/skum_test/ca_2020_census/California_CA.csv\", header=0)"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "7d6e102b-ed0d-489d-aa1b-513e4107af0c",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
""
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"#display(data_ks)"
]
},
{
"cell_type": "markdown",
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "9e006359-d572-4137-9164-55cc951b035a",
"showTitle": false,
"title": ""
}
},
"source": [
"### Time to read 721 MB csv file during one of the runs\n",
"\n",
"| Pandas | Spark | Spark with inferSchema option | Koalas | \n",
"| :------: | :-------: | :-------: | :-------: |\n",
"| 24.44 secs | 7.14 secs | 5.44 secs | 3.22 secs |"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "7f494832-cb2a-49a2-be27-38e3c03e0796",
"showTitle": false,
"title": ""
}
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "135f0496-4c94-4d14-83bd-9c5966646f3f",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
""
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"#data_ks.info()"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "e2de91b5-f20b-4dec-8d81-00c48320fad8",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"Out[17]: (669171, 401)
"
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "Out[17]: (669171, 401)
",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"data_ks.shape"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "98e50fc9-6800-4400-9b06-efa0f85afc7a",
"showTitle": false,
"title": ""
}
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "0c624610-437d-47ef-b353-b5a6d63b5d65",
"showTitle": false,
"title": ""
}
},
"source": [
"### Selecting 104 columns for analysis"
]
},
{
"cell_type": "markdown",
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "db4c1b2a-e414-45f4-b030-5f48ad5b4f96",
"showTitle": false,
"title": ""
}
},
"source": [
"The following 104 columns of data will be used for analysis:
\n",
"\n",
"REGION Region
\n",
"DIVISION Division
\n",
"COUNTY County (FIPS)
\n",
"CBSA Metropolitan Statistical Area/Micropolitan Statistical Area
\n",
"MEMI Metropolitan/Micropolitan Indicator
\n",
"CSA Combined Statistical Area
\n",
"METDIV Metropolitan Division
\n",
"AREALAND Area (Land)
\n",
"AREAWATR Area (Water)
\n",
"BASENAME Area Base Name
\n",
"NAME Area Name-Legal/Statistical Area Description (LSAD) Term-Part Indicator
\n",
"FUNCSTAT Functional Status Code
\n",
"POP100 Population Count (100%)
\n",
"HU100 Housing Unit Count (100%)
\n",
"INTPTLAT Internal Point (Latitude)
\n",
"INTPTLON Internal Point (Longitude)
\n",
"LSADC Legal/Statistical Area Description Code
\n",
"P0010001 Total:
\n",
"P0010002 Population of one race:
\n",
"P0010003 White alone
\n",
"P0010004 Black or African American alone
\n",
"P0010005 American Indian and Alaska Native alone
\n",
"P0010006 Asian alone
\n",
"P0010007 Native Hawaiian and Other Pacific Islander alone
\n",
"P0010008 Some Other Race alone
\n",
"P0010009 Population of two or more races:
\n",
"P0010010 Population of two races:
\n",
"P0010011 White; Black or African American
\n",
"P0010012 White; American Indian and Alaska Native
\n",
"P0010013 White; Asian
\n",
"P0010014 White; Native Hawaiian and Other Pacific Islander
\n",
"P0010015 White; Some Other Race
\n",
"P0010016 Black or African American; American Indian and Alaska Native
\n",
"P0010017 Black or African American; Asian
\n",
"P0010018 Black or African American; Native Hawaiian and Other Pacific Islander
\n",
"P0010019 Black or African American; Some Other Race
\n",
"P0010020 American Indian and Alaska Native; Asian
\n",
"P0010021 American Indian and Alaska Native; Native Hawaiian and Other Pacific Islander
\n",
"P0010022 American Indian and Alaska Native; Some Other Race
\n",
"P0010023 Asian; Native Hawaiian and Other Pacific Islander
\n",
"P0010024 Asian; Some Other Race
\n",
"P0010025 Native Hawaiian and Other Pacific Islander; Some Other Race
\n",
"P0010026 Population of three races:
\n",
"P0010027 White; Black or African American; American Indian and Alaska Native
\n",
"P0010028 White; Black or African American; Asian
\n",
"P0010029 White; Black or African American; Native Hawaiian and Other Pacific Islander
\n",
"P0010030 White; Black or African American; Some Other Race
\n",
"P0010031 White; American Indian and Alaska Native; Asian
\n",
"P0010032 White; American Indian and Alaska Native; Native Hawaiian and Other Pacific Islander
\n",
"P0010033 White; American Indian and Alaska Native; Some Other Race
\n",
"P0010034 White; Asian; Native Hawaiian and Other Pacific Islander
\n",
"P0010035 White; Asian; Some Other Race
\n",
"P0010036 White; Native Hawaiian and Other Pacific Islander; Some Other Race
\n",
"P0010037 Black or African American; American Indian and Alaska Native; Asian
\n",
"P0010038 Black or African American; American Indian and Alaska Native; Native Hawaiian and Other Pacific Islander
\n",
"P0010039 Black or African American; American Indian and Alaska Native; Some Other Race
\n",
"P0010040 Black or African American; Asian; Native Hawaiian and Other Pacific Islander
\n",
"P0010041 Black or African American; Asian; Some Other Race
\n",
"P0010042 Black or African American; Native Hawaiian and Other Pacific Islander; Some Other Race
\n",
"P0010043 American Indian and Alaska Native; Asian; Native Hawaiian and Other Pacific Islander
\n",
"P0010044 American Indian and Alaska Native; Asian; Some Other Race
\n",
"P0010045 American Indian and Alaska Native; Native Hawaiian and Other Pacific Islander; Some Other Race
\n",
"P0010046 Asian; Native Hawaiian and Other Pacific Islander; Some Other Race
\n",
"P0010047 Population of four races:
\n",
"P0010048 White; Black or African American; American Indian and Alaska Native; Asian
\n",
"P0010049 White; Black or African American; American Indian and Alaska Native; Native Hawaiian and Other Pacific Islander
\n",
"P0010050 White; Black or African American; American Indian and Alaska Native; Some Other Race
\n",
"P0010051 White; Black or African American; Asian; Native Hawaiian and Other Pacific Islander
\n",
"P0010052 White; Black or African American; Asian; Some Other Race
\n",
"P0010053 White; Black or African American; Native Hawaiian and Other Pacific Islander; Some Other Race
\n",
"P0010054 White; American Indian and Alaska Native; Asian; Native Hawaiian and Other Pacific Islander
\n",
"P0010055 White; American Indian and Alaska Native; Asian; Some Other Race
\n",
"P0010056 White; American Indian and Alaska Native; Native Hawaiian and Other Pacific Islander; Some Other Race
\n",
"P0010057 White; Asian; Native Hawaiian and Other Pacific Islander; Some Other Race
\n",
"P0010058 Black or African American; American Indian and Alaska Native; Asian; Native Hawaiian and Other Pacific Islander
\n",
"P0010059 Black or African American; American Indian and Alaska Native; Asian; Some Other Race
\n",
"P0010060 Black or African American; American Indian and Alaska Native; Native Hawaiian and Other Pacific Islander; Some Other Race
\n",
"P0010061 Black or African American; Asian; Native Hawaiian and Other Pacific Islander; Some Other Race
\n",
"P0010062 American Indian and Alaska Native; Asian; Native Hawaiian and Other Pacific Islander; Some Other Race
\n",
"P0010063 Population of five races:
\n",
"P0010064 White; Black or African American; American Indian and Alaska Native; Asian; Native Hawaiian and Other Pacific Islander
\n",
"P0010065 White; Black or African American; American Indian and Alaska Native; Asian; Some Other Race
\n",
"P0010066 White; Black or African American; American Indian and Alaska Native; Native Hawaiian and Other Pacific Islander; Some Other Race
\n",
"P0010067 White; Black or African American; Asian; Native Hawaiian and Other Pacific Islander; Some Other Race
\n",
"P0010068 White; American Indian and Alaska Native; Asian; Native Hawaiian and Other Pacific Islander; Some Other Race
\n",
"P0010069 Black or African American; American Indian and Alaska Native; Asian; Native Hawaiian and Other Pacific Islander; Some Other Race
\n",
"P0010070 Population of six races:
\n",
"P0010071 White; Black or African American; American Indian and Alaska Native; Asian; Native Hawaiian and Other Pacific Islander; Some Other Race
\n",
"P0020002 Hispanic or Latino
\n",
"P0020003 Not Hispanic or Latino:
\n",
"H0010001 H1-1: Total
\n",
"H0010002 H1-2: Occupied
\n",
"H0010003 H1-3: Vacant
\n",
"P0050001 Total:
\n",
"P0050002 Institutionalized population:
\n",
"P0050003 Correctional facilities for adults
\n",
"P0050004 Juvenile facilities
\n",
"P0050005 Nursing facilities/Skilled-nursing facilities
\n",
"P0050006 Other institutional facilities
\n",
"P0050007 Noninstitutionalized population:
\n",
"P0050008 College/University student housing
\n",
"P0050009 Military quarters
\n",
"P0050010 Other noninstitutional facilities
"
]
},
{
"cell_type": "markdown",
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "a5fcb29f-834c-4e3d-9091-2b50dec781bf",
"showTitle": false,
"title": ""
}
},
"source": [
"### Subsetting from Spark dataframe"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "32d64300-85f0-44f0-88b6-580cbbb6f6e2",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
""
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "",
"datasetInfos": [
{
"name": "census_df_sp_sub",
"schema": {
"fields": [
{
"metadata": {},
"name": "REGION",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "DIVISION",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "COUNTY",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "CBSA",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "MEMI",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "CSA",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "METDIV",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "AREALAND",
"nullable": true,
"type": "long"
},
{
"metadata": {},
"name": "AREAWATR",
"nullable": true,
"type": "long"
},
{
"metadata": {},
"name": "BASENAME",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "Name",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "POP100",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "HU100",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "INTPTLAT",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "INTPTLON",
"nullable": true,
"type": "double"
},
{
"metadata": {},
"name": "LSADC",
"nullable": true,
"type": "string"
},
{
"metadata": {},
"name": "P0010001",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010002",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010003",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010004",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010005",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010006",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010007",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010008",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010009",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010010",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010011",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010012",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010013",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010014",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010015",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010016",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010017",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010018",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010019",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010020",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010021",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010022",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010023",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010024",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010025",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010026",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010027",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010028",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010029",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010030",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010031",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010032",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010033",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010034",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010035",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010036",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010037",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010038",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010039",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010040",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010041",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010042",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010043",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010044",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010045",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010046",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010047",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010048",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010049",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010050",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010051",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010052",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010053",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010054",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010055",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010056",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010057",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010058",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010059",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010060",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010061",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010062",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010063",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010064",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010065",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010066",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010067",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010068",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010069",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010070",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0010071",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020002",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0020003",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "H0010001",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "H0010002",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "H0010003",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0050001",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0050002",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0050003",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0050004",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0050005",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0050006",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0050007",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0050008",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0050009",
"nullable": true,
"type": "integer"
},
{
"metadata": {},
"name": "P0050010",
"nullable": true,
"type": "integer"
}
],
"type": "struct"
},
"tableIdentifier": null,
"typeStr": "pyspark.sql.dataframe.DataFrame"
}
],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"census_df_sp_sub = census_df_sp.select([\"REGION\",\"DIVISION\",\"COUNTY\",\"CBSA\",\"MEMI\",\"CSA\",\"METDIV\",\"AREALAND\",\"AREAWATR\",\"BASENAME\",\"Name\",\"POP100\",\"HU100\",\"INTPTLAT\",\"INTPTLON\",\"LSADC\",\"P0010001\", \"P0010002\", \"P0010003\", \"P0010004\", \"P0010005\", \"P0010006\", \"P0010007\", \"P0010008\", \"P0010009\", \"P0010010\", \"P0010011\", \"P0010012\", \"P0010013\", \"P0010014\", \"P0010015\", \"P0010016\", \"P0010017\", \"P0010018\", \"P0010019\", \"P0010020\", \"P0010021\", \"P0010022\", \"P0010023\", \"P0010024\", \"P0010025\", \"P0010026\", \"P0010027\", \"P0010028\", \"P0010029\", \"P0010030\", \"P0010031\", \"P0010032\", \"P0010033\", \"P0010034\", \"P0010035\", \"P0010036\", \"P0010037\", \"P0010038\", \"P0010039\", \"P0010040\", \"P0010041\", \"P0010042\", \"P0010043\", \"P0010044\", \"P0010045\", \"P0010046\", \"P0010047\", \"P0010048\", \"P0010049\", \"P0010050\", \"P0010051\", \"P0010052\", \"P0010053\", \"P0010054\", \"P0010055\", \"P0010056\", \"P0010057\", \"P0010058\", \"P0010059\", \"P0010060\", \"P0010061\", \"P0010062\", \"P0010063\", \"P0010064\", \"P0010065\", \"P0010066\", \"P0010067\", \"P0010068\", \"P0010069\", \"P0010070\", \"P0010071\", \"P0020002\", \"P0020003\", \"H0010001\", \"H0010002\", \"H0010003\", \"P0050001\", \"P0050002\", \"P0050003\", \"P0050004\", \"P0050005\", \"P0050006\", \"P0050007\", \"P0050008\", \"P0050009\", \"P0050010\"])\n",
"#display(census_df_sp_sub)"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "bcb410b1-33bd-4248-b989-e9231f85c7c5",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
""
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"#df.colRegex(\"P001\")"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "ae039ff7-9cdb-4baa-b575-a89e2802137c",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"| summary | REGION | DIVISION | COUNTY | CBSA | MEMI | CSA | METDIV | AREALAND | AREAWATR | BASENAME | Name | POP100 | HU100 | INTPTLAT | INTPTLON | LSADC | P0010001 | P0010002 | P0010003 | P0010004 | P0010005 | P0010006 | P0010007 | P0010008 | P0010009 | P0010010 | P0010011 | P0010012 | P0010013 | P0010014 | P0010015 | P0010016 | P0010017 | P0010018 | P0010019 | P0010020 | P0010021 | P0010022 | P0010023 | P0010024 | P0010025 | P0010026 | P0010027 | P0010028 | P0010029 | P0010030 | P0010031 | P0010032 | P0010033 | P0010034 | P0010035 | P0010036 | P0010037 | P0010038 | P0010039 | P0010040 | P0010041 | P0010042 | P0010043 | P0010044 | P0010045 | P0010046 | P0010047 | P0010048 | P0010049 | P0010050 | P0010051 | P0010052 | P0010053 | P0010054 | P0010055 | P0010056 | P0010057 | P0010058 | P0010059 | P0010060 | P0010061 | P0010062 | P0010063 | P0010064 | P0010065 | P0010066 | P0010067 | P0010068 | P0010069 | P0010070 | P0010071 | P0020002 | P0020003 | H0010001 | H0010002 | H0010003 | P0050001 | P0050002 | P0050003 | P0050004 | P0050005 | P0050006 | P0050007 | P0050008 | P0050009 | P0050010 |
|---|
| count | 669171 | 669171 | 650290 | 650290 | 650290 | 650290 | 650290 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 | 669171 |
| mean | 4.0 | 9.0 | 56.366931676636575 | 38679.26071752603 | 1.3898522197788679 | 554.2995555828937 | 76237.78717956605 | 2.8677515498694655E7 | 1445348.4535836133 | 1832.536732234136 | null | 3059.615147697674 | 1113.5215647420464 | 36.032115277906854 | -119.64066830452249 | 26.733684030450775 | 3059.615147697674 | 2613.714258388364 | 1258.4589409881778 | 173.5204469410659 | 48.9568824709977 | 472.2799613252816 | 12.19083612409982 | 648.3071905387412 | 445.9008893093096 | 416.4643730825155 | 19.981495013979984 | 29.66331176933848 | 48.420317078893135 | 3.5101820013120713 | 280.72336816747884 | 2.8957964406706207 | 4.014609120837574 | 0.6792180175171967 | 6.895657462741212 | 1.020704722709143 | 0.19860244989696207 | 8.816177030983113 | 3.9774721259588355 | 4.740206912732321 | 0.9272547674660139 | 26.405721407532603 | 3.201568806777341 | 1.8671311219404307 | 0.2581283408874563 | 2.5513657943933614 | 1.7074604249138112 | 0.2554354567068806 | 9.24852093112224 | 2.400646471529699 | 3.273394991713628 | 0.328717173936109 | 0.2000086674407588 | 0.04289635982431994 | 0.2618583291864112 | 0.20435733168353082 | 0.20147466043806442 | 0.04687889941434999 | 0.07420076482692764 | 0.113359664420604 | 0.024413789599369965 | 0.14390342677731102 | 2.6784095545084887 | 0.503422891906553 | 0.0758356234803959 | 0.9203895566305175 | 0.15077909831717154 | 0.2116663752613308 | 0.02595001875454854 | 0.19549860947351275 | 0.33209598144569924 | 0.03252681302686458 | 0.16080941941596394 | 0.020153294150523558 | 0.021743321213860134 | 0.005952140783148104 | 0.01316703802167159 | 0.008419372626727697 | 0.31766768135498996 | 0.103903187675497 | 0.1549753351534959 | 0.018213580684159954 | 0.016043731721787108 | 0.02205265918576866 | 0.002479186934281372 | 0.034717583397965546 | 0.034717583397965546 | 1206.5007987494976 | 1853.1143489481763 | 1113.5215647420464 | 1042.8784271882673 | 70.64313755377923 | 70.68672282570523 | 26.4018389918272 | 15.296785126671658 | 0.6814057991156222 | 9.684245133157294 | 0.7394029328826264 | 44.284883833878034 | 17.845792779424094 | 4.347791521150797 | 22.091299533303147 |
| stddev | 0.0 | 0.0 | 28.31755854283744 | 15294.999450959238 | 1.623580576183806 | 270.1235591357882 | 33581.03897460754 | 7.881045914630078E8 | 4.494612437568705E7 | 1362.64644400938 | null | 66405.47319871612 | 24431.340821414025 | 2.3066087112499662 | 2.0902436730725986 | 25.362129522066663 | 66405.47319871612 | 56853.01741716403 | 26526.04242970642 | 4595.227009682515 | 1060.2947009505854 | 11095.468936577807 | 278.1856483724344 | 15286.754026573077 | 9606.180301680255 | 8971.494547229793 | 448.8439672083964 | 590.8450733585147 | 1074.9128948779255 | 72.65506501955869 | 6136.860344046799 | 71.65700168239906 | 94.854026160174 | 15.98677244280636 | 179.10509565816344 | 22.166134660665143 | 4.2246339388363285 | 206.5055051043879 | 87.47833887109377 | 106.04737114758841 | 21.221856045450323 | 573.1525791990103 | 72.15967177677882 | 42.057610874354104 | 5.747666701614405 | 57.86506363067629 | 35.35640895983642 | 5.169246161049264 | 204.17508670962263 | 51.408998717980424 | 70.47563280844962 | 6.91416990943495 | 4.636601663755835 | 1.102240632199946 | 6.325829834166733 | 4.855388638690167 | 4.731520760612667 | 1.1410024230780134 | 1.5805620556340394 | 2.4675008146077446 | 0.5354034287121976 | 3.1674736799695964 | 59.43995607021075 | 11.468646987613933 | 1.7201859377688478 | 21.449689415311948 | 3.4206981519379043 | 4.873442687524608 | 0.5832214962803234 | 4.109139259114911 | 7.215087980828405 | 0.6897207574776267 | 3.441005165520258 | 0.5021498570588202 | 0.49869988729761555 | 0.17870930429585002 | 0.2965270764180188 | 0.20318667124143872 | 7.078996390196105 | 2.3648623549130847 | 3.568688830888468 | 0.3975957995646648 | 0.3813182936499723 | 0.5296301026671097 | 0.0831706430900629 | 0.8453477335540394 | 0.8453477335540394 | 27432.786453061643 | 40094.052441055195 | 24431.340821414025 | 22903.924030413393 | 1604.306770712246 | 1662.1753646137315 | 577.9366182088413 | 372.60041352603315 | 16.466467763815917 | 227.47278374446967 | 25.182709662978187 | 1168.0248620705302 | 555.4863597123475 | 221.16130607469864 | 568.7430289189296 |
| min | 4 | 9 | 1.0 | 12540.0 | 1.0 | 260.0 | 11244.0 | 0 | 0 | 0 | ABC Unified School District | 0 | 0 | 32.5395511 | -124.4136928 | 00 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 25% | 4 | 9 | 37.0 | 31080.0 | 1.0 | 348.0 | 36084.0 | 16661 | 0 | 1007.0 | null | 7 | 2 | 34.0052005 | -121.6376844 | 0.0 | 7 | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 50% | 4 | 9 | 59.0 | 40140.0 | 1.0 | 472.0 | 99999.0 | 51601 | 0 | 2001.0 | null | 61 | 21 | 35.4357468 | -119.2696632 | 22.0 | 61 | 50 | 23 | 0 | 0 | 2 | 0 | 5 | 9 | 8 | 0 | 0 | 0 | 0 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 15 | 33 | 21 | 19 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 75% | 4 | 9 | 75.0 | 41860.0 | 1.0 | 999.0 | 99999.0 | 638110 | 0 | 3000.0 | null | 246 | 93 | 37.866253799999996 | -117.930457 | 57.0 | 246 | 213 | 105 | 10 | 4 | 29 | 1 | 48 | 36 | 34 | 2 | 3 | 4 | 0 | 24 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 96 | 148 | 93 | 87 | 7 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| max | 4 | 9 | 115.0 | 99999.0 | 9.0 | 999.0 | 99999.0 | 282055294521 | 15719629492 | Zayante | Zayante CDP | 28573858 | 10571847 | 42.0074191 | -114.13926399999998 | OT | 28573858 | 24485003 | 11576460 | 1799185 | 447548 | 4474283 | 115115 | 6072412 | 4088855 | 3811637 | 194177 | 262089 | 459478 | 31625 | 2532955 | 29671 | 40474 | 6789 | 69354 | 9699 | 1847 | 82008 | 37940 | 44752 | 8779 | 247939 | 31244 | 18189 | 2467 | 24478 | 15573 | 2273 | 85549 | 22286 | 29988 | 2983 | 1983 | 455 | 2648 | 2083 | 1976 | 475 | 682 | 1045 | 211 | 1351 | 25817 | 5001 | 746 | 8969 | 1473 | 2086 | 243 | 1780 | 3058 | 293 | 1507 | 209 | 206 | 64 | 105 | 77 | 3120 | 1043 | 1529 | 164 | 153 | 208 | 23 | 342 | 342 | 11128716 | 17445142 | 10571847 | 9866472 | 705375 | 696051 | 234511 | 126683 | 6408 | 93493 | 7927 | 461540 | 197511 | 39597 | 226824 |
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" REGION | \n",
" DIVISION | \n",
" COUNTY | \n",
" CBSA | \n",
" MEMI | \n",
" CSA | \n",
" METDIV | \n",
" AREALAND | \n",
" AREAWATR | \n",
" BASENAME | \n",
" NAME | \n",
" POP100 | \n",
" HU100 | \n",
" INTPTLAT | \n",
" INTPTLON | \n",
" LSADC | \n",
" P0010001 | \n",
" P0010002 | \n",
" P0010003 | \n",
" P0010004 | \n",
" P0010005 | \n",
" P0010006 | \n",
" P0010007 | \n",
" P0010008 | \n",
" P0010009 | \n",
" P0010010 | \n",
" P0010011 | \n",
" P0010012 | \n",
" P0010013 | \n",
" P0010014 | \n",
" P0010015 | \n",
" P0010016 | \n",
" P0010017 | \n",
" P0010018 | \n",
" P0010019 | \n",
" P0010020 | \n",
" P0010021 | \n",
" P0010022 | \n",
" P0010023 | \n",
" P0010024 | \n",
" P0010025 | \n",
" P0010026 | \n",
" P0010027 | \n",
" P0010028 | \n",
" P0010029 | \n",
" P0010030 | \n",
" P0010031 | \n",
" P0010032 | \n",
" P0010033 | \n",
" P0010034 | \n",
" P0010035 | \n",
" P0010036 | \n",
" P0010037 | \n",
" P0010038 | \n",
" P0010039 | \n",
" P0010040 | \n",
" P0010041 | \n",
" P0010042 | \n",
" P0010043 | \n",
" P0010044 | \n",
" P0010045 | \n",
" P0010046 | \n",
" P0010047 | \n",
" P0010048 | \n",
" P0010049 | \n",
" P0010050 | \n",
" P0010051 | \n",
" P0010052 | \n",
" P0010053 | \n",
" P0010054 | \n",
" P0010055 | \n",
" P0010056 | \n",
" P0010057 | \n",
" P0010058 | \n",
" P0010059 | \n",
" P0010060 | \n",
" P0010061 | \n",
" P0010062 | \n",
" P0010063 | \n",
" P0010064 | \n",
" P0010065 | \n",
" P0010066 | \n",
" P0010067 | \n",
" P0010068 | \n",
" P0010069 | \n",
" P0010070 | \n",
" P0010071 | \n",
" P0020002 | \n",
" P0020003 | \n",
" H0010001 | \n",
" H0010002 | \n",
" H0010003 | \n",
" P0050001 | \n",
" P0050002 | \n",
" P0050003 | \n",
" P0050004 | \n",
" P0050005 | \n",
" P0050006 | \n",
" P0050007 | \n",
" P0050008 | \n",
" P0050009 | \n",
" P0050010 | \n",
"
\n",
" \n",
" \n",
" \n",
" | 0 | \n",
" 4 | \n",
" 9 | \n",
" 1.0 | \n",
" 41860.0 | \n",
" 1.0 | \n",
" 488.0 | \n",
" 36084.0 | \n",
" 1910017353 | \n",
" 216902808 | \n",
" Alameda | \n",
" Alameda County | \n",
" 1682353 | \n",
" 621958 | \n",
" 37.647139 | \n",
" -121.912488 | \n",
" 06 | \n",
" 1682353 | \n",
" 1491537 | \n",
" 523836 | \n",
" 164879 | \n",
" 19659 | \n",
" 545261 | \n",
" 14123 | \n",
" 223779 | \n",
" 190816 | \n",
" 171703 | \n",
" 13579 | \n",
" 10768 | \n",
" 39888 | \n",
" 2293 | \n",
" 81119 | \n",
" 2682 | \n",
" 4125 | \n",
" 640 | \n",
" 4182 | \n",
" 707 | \n",
" 151 | \n",
" 3685 | \n",
" 3684 | \n",
" 3285 | \n",
" 915 | \n",
" 16711 | \n",
" 2460 | \n",
" 1652 | \n",
" 154 | \n",
" 1551 | \n",
" 1066 | \n",
" 137 | \n",
" 4502 | \n",
" 1704 | \n",
" 2121 | \n",
" 206 | \n",
" 176 | \n",
" 34 | \n",
" 231 | \n",
" 205 | \n",
" 194 | \n",
" 30 | \n",
" 64 | \n",
" 77 | \n",
" 20 | \n",
" 127 | \n",
" 2112 | \n",
" 404 | \n",
" 49 | \n",
" 819 | \n",
" 110 | \n",
" 159 | \n",
" 22 | \n",
" 124 | \n",
" 257 | \n",
" 21 | \n",
" 105 | \n",
" 25 | \n",
" 8 | \n",
" 0 | \n",
" 6 | \n",
" 3 | \n",
" 262 | \n",
" 95 | \n",
" 129 | \n",
" 14 | \n",
" 12 | \n",
" 12 | \n",
" 0 | \n",
" 28 | \n",
" 28 | \n",
" 393749 | \n",
" 1288604 | \n",
" 621958 | \n",
" 591636 | \n",
" 30322 | \n",
" 53833 | \n",
" 10130 | \n",
" 3406 | \n",
" 397 | \n",
" 6218 | \n",
" 109 | \n",
" 43703 | \n",
" 17463 | \n",
" 421 | \n",
" 25819 | \n",
"
\n",
" \n",
" | 1 | \n",
" 4 | \n",
" 9 | \n",
" 3.0 | \n",
" 99999.0 | \n",
" 9.0 | \n",
" 999.0 | \n",
" 99999.0 | \n",
" 1912292607 | \n",
" 12557304 | \n",
" Alpine | \n",
" Alpine County | \n",
" 1204 | \n",
" 1540 | \n",
" 38.621783 | \n",
" -119.798352 | \n",
" 06 | \n",
" 1204 | \n",
" 1085 | \n",
" 814 | \n",
" 10 | \n",
" 236 | \n",
" 12 | \n",
" 0 | \n",
" 13 | \n",
" 119 | \n",
" 89 | \n",
" 5 | \n",
" 10 | \n",
" 6 | \n",
" 1 | \n",
" 50 | \n",
" 5 | \n",
" 2 | \n",
" 1 | \n",
" 0 | \n",
" 1 | \n",
" 1 | \n",
" 3 | \n",
" 2 | \n",
" 2 | \n",
" 0 | \n",
" 20 | \n",
" 2 | \n",
" 0 | \n",
" 4 | \n",
" 0 | \n",
" 0 | \n",
" 2 | \n",
" 3 | \n",
" 0 | \n",
" 4 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 1 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 9 | \n",
" 2 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 5 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 84 | \n",
" 1120 | \n",
" 1540 | \n",
" 530 | \n",
" 1010 | \n",
" 52 | \n",
" 1 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 51 | \n",
" 0 | \n",
" 0 | \n",
" 51 | \n",
"
\n",
" \n",
" | 2 | \n",
" 4 | \n",
" 9 | \n",
" 5.0 | \n",
" 99999.0 | \n",
" 9.0 | \n",
" 999.0 | \n",
" 99999.0 | \n",
" 1539965777 | \n",
" 29438413 | \n",
" Amador | \n",
" Amador County | \n",
" 40474 | \n",
" 18805 | \n",
" 38.443549 | \n",
" -120.653858 | \n",
" 06 | \n",
" 40474 | \n",
" 36596 | \n",
" 31104 | \n",
" 1236 | \n",
" 757 | \n",
" 582 | \n",
" 82 | \n",
" 2835 | \n",
" 3878 | \n",
" 3591 | \n",
" 163 | \n",
" 1123 | \n",
" 307 | \n",
" 59 | \n",
" 1804 | \n",
" 20 | \n",
" 5 | \n",
" 0 | \n",
" 6 | \n",
" 18 | \n",
" 2 | \n",
" 15 | \n",
" 59 | \n",
" 6 | \n",
" 4 | \n",
" 261 | \n",
" 28 | \n",
" 7 | \n",
" 4 | \n",
" 12 | \n",
" 34 | \n",
" 11 | \n",
" 87 | \n",
" 26 | \n",
" 19 | \n",
" 5 | \n",
" 2 | \n",
" 1 | \n",
" 1 | \n",
" 8 | \n",
" 1 | \n",
" 7 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 8 | \n",
" 17 | \n",
" 0 | \n",
" 2 | \n",
" 4 | \n",
" 1 | \n",
" 4 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 5 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 9 | \n",
" 5 | \n",
" 3 | \n",
" 1 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 6014 | \n",
" 34460 | \n",
" 18805 | \n",
" 15678 | \n",
" 3127 | \n",
" 4311 | \n",
" 4098 | \n",
" 4045 | \n",
" 2 | \n",
" 51 | \n",
" 0 | \n",
" 213 | \n",
" 0 | \n",
" 0 | \n",
" 213 | \n",
"
\n",
" \n",
" | 3 | \n",
" 4 | \n",
" 9 | \n",
" 7.0 | \n",
" 17020.0 | \n",
" 1.0 | \n",
" 999.0 | \n",
" 99999.0 | \n",
" 4238488698 | \n",
" 105260548 | \n",
" Butte | \n",
" Butte County | \n",
" 211632 | \n",
" 90133 | \n",
" 39.665336 | \n",
" -121.603209 | \n",
" 06 | \n",
" 211632 | \n",
" 186947 | \n",
" 149557 | \n",
" 3644 | \n",
" 4492 | \n",
" 10533 | \n",
" 573 | \n",
" 18148 | \n",
" 24685 | \n",
" 22849 | \n",
" 1764 | \n",
" 6709 | \n",
" 2396 | \n",
" 388 | \n",
" 10402 | \n",
" 177 | \n",
" 93 | \n",
" 24 | \n",
" 157 | \n",
" 69 | \n",
" 22 | \n",
" 374 | \n",
" 172 | \n",
" 84 | \n",
" 18 | \n",
" 1652 | \n",
" 345 | \n",
" 97 | \n",
" 16 | \n",
" 124 | \n",
" 162 | \n",
" 61 | \n",
" 480 | \n",
" 182 | \n",
" 87 | \n",
" 21 | \n",
" 16 | \n",
" 1 | \n",
" 21 | \n",
" 4 | \n",
" 7 | \n",
" 0 | \n",
" 5 | \n",
" 16 | \n",
" 1 | \n",
" 6 | \n",
" 156 | \n",
" 30 | \n",
" 7 | \n",
" 41 | \n",
" 1 | \n",
" 6 | \n",
" 7 | \n",
" 29 | \n",
" 23 | \n",
" 2 | \n",
" 7 | \n",
" 0 | \n",
" 2 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 28 | \n",
" 12 | \n",
" 11 | \n",
" 2 | \n",
" 3 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 40112 | \n",
" 171520 | \n",
" 90133 | \n",
" 83268 | \n",
" 6865 | \n",
" 4941 | \n",
" 1449 | \n",
" 496 | \n",
" 31 | \n",
" 902 | \n",
" 20 | \n",
" 3492 | \n",
" 2234 | \n",
" 0 | \n",
" 1258 | \n",
"
\n",
" \n",
" | 4 | \n",
" 4 | \n",
" 9 | \n",
" 9.0 | \n",
" 99999.0 | \n",
" 9.0 | \n",
" 999.0 | \n",
" 99999.0 | \n",
" 2641837359 | \n",
" 43789489 | \n",
" Calaveras | \n",
" Calaveras County | \n",
" 45292 | \n",
" 27422 | \n",
" 38.191068 | \n",
" -120.554106 | \n",
" 06 | \n",
" 45292 | \n",
" 40264 | \n",
" 36315 | \n",
" 364 | \n",
" 747 | \n",
" 743 | \n",
" 100 | \n",
" 1995 | \n",
" 5028 | \n",
" 4706 | \n",
" 195 | \n",
" 1513 | \n",
" 428 | \n",
" 110 | \n",
" 2285 | \n",
" 13 | \n",
" 13 | \n",
" 0 | \n",
" 24 | \n",
" 6 | \n",
" 6 | \n",
" 43 | \n",
" 39 | \n",
" 28 | \n",
" 3 | \n",
" 285 | \n",
" 15 | \n",
" 8 | \n",
" 2 | \n",
" 28 | \n",
" 25 | \n",
" 24 | \n",
" 104 | \n",
" 39 | \n",
" 21 | \n",
" 0 | \n",
" 8 | \n",
" 0 | \n",
" 2 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 5 | \n",
" 0 | \n",
" 4 | \n",
" 31 | \n",
" 6 | \n",
" 1 | \n",
" 4 | \n",
" 0 | \n",
" 7 | \n",
" 0 | \n",
" 4 | \n",
" 0 | \n",
" 6 | \n",
" 3 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 5 | \n",
" 3 | \n",
" 0 | \n",
" 0 | \n",
" 1 | \n",
" 1 | \n",
" 0 | \n",
" 1 | \n",
" 1 | \n",
" 5865 | \n",
" 39427 | \n",
" 27422 | \n",
" 18758 | \n",
" 8664 | \n",
" 461 | \n",
" 311 | \n",
" 170 | \n",
" 40 | \n",
" 101 | \n",
" 0 | \n",
" 150 | \n",
" 0 | \n",
" 0 | \n",
" 150 | \n",
"
\n",
" \n",
"
\n",
"
\n\n
\n \n \n | \n REGION | \n DIVISION | \n COUNTY | \n CBSA | \n MEMI | \n CSA | \n METDIV | \n AREALAND | \n AREAWATR | \n BASENAME | \n NAME | \n POP100 | \n HU100 | \n INTPTLAT | \n INTPTLON | \n LSADC | \n P0010001 | \n P0010002 | \n P0010003 | \n P0010004 | \n P0010005 | \n P0010006 | \n P0010007 | \n P0010008 | \n P0010009 | \n P0010010 | \n P0010011 | \n P0010012 | \n P0010013 | \n P0010014 | \n P0010015 | \n P0010016 | \n P0010017 | \n P0010018 | \n P0010019 | \n P0010020 | \n P0010021 | \n P0010022 | \n P0010023 | \n P0010024 | \n P0010025 | \n P0010026 | \n P0010027 | \n P0010028 | \n P0010029 | \n P0010030 | \n P0010031 | \n P0010032 | \n P0010033 | \n P0010034 | \n P0010035 | \n P0010036 | \n P0010037 | \n P0010038 | \n P0010039 | \n P0010040 | \n P0010041 | \n P0010042 | \n P0010043 | \n P0010044 | \n P0010045 | \n P0010046 | \n P0010047 | \n P0010048 | \n P0010049 | \n P0010050 | \n P0010051 | \n P0010052 | \n P0010053 | \n P0010054 | \n P0010055 | \n P0010056 | \n P0010057 | \n P0010058 | \n P0010059 | \n P0010060 | \n P0010061 | \n P0010062 | \n P0010063 | \n P0010064 | \n P0010065 | \n P0010066 | \n P0010067 | \n P0010068 | \n P0010069 | \n P0010070 | \n P0010071 | \n P0020002 | \n P0020003 | \n H0010001 | \n H0010002 | \n H0010003 | \n P0050001 | \n P0050002 | \n P0050003 | \n P0050004 | \n P0050005 | \n P0050006 | \n P0050007 | \n P0050008 | \n P0050009 | \n P0050010 | \n
\n \n \n \n | 0 | \n 4 | \n 9 | \n 1.0 | \n 41860.0 | \n 1.0 | \n 488.0 | \n 36084.0 | \n 1910017353 | \n 216902808 | \n Alameda | \n Alameda County | \n 1682353 | \n 621958 | \n 37.647139 | \n -121.912488 | \n 06 | \n 1682353 | \n 1491537 | \n 523836 | \n 164879 | \n 19659 | \n 545261 | \n 14123 | \n 223779 | \n 190816 | \n 171703 | \n 13579 | \n 10768 | \n 39888 | \n 2293 | \n 81119 | \n 2682 | \n 4125 | \n 640 | \n 4182 | \n 707 | \n 151 | \n 3685 | \n 3684 | \n 3285 | \n 915 | \n 16711 | \n 2460 | \n 1652 | \n 154 | \n 1551 | \n 1066 | \n 137 | \n 4502 | \n 1704 | \n 2121 | \n 206 | \n 176 | \n 34 | \n 231 | \n 205 | \n 194 | \n 30 | \n 64 | \n 77 | \n 20 | \n 127 | \n 2112 | \n 404 | \n 49 | \n 819 | \n 110 | \n 159 | \n 22 | \n 124 | \n 257 | \n 21 | \n 105 | \n 25 | \n 8 | \n 0 | \n 6 | \n 3 | \n 262 | \n 95 | \n 129 | \n 14 | \n 12 | \n 12 | \n 0 | \n 28 | \n 28 | \n 393749 | \n 1288604 | \n 621958 | \n 591636 | \n 30322 | \n 53833 | \n 10130 | \n 3406 | \n 397 | \n 6218 | \n 109 | \n 43703 | \n 17463 | \n 421 | \n 25819 | \n
\n \n | 1 | \n 4 | \n 9 | \n 3.0 | \n 99999.0 | \n 9.0 | \n 999.0 | \n 99999.0 | \n 1912292607 | \n 12557304 | \n Alpine | \n Alpine County | \n 1204 | \n 1540 | \n 38.621783 | \n -119.798352 | \n 06 | \n 1204 | \n 1085 | \n 814 | \n 10 | \n 236 | \n 12 | \n 0 | \n 13 | \n 119 | \n 89 | \n 5 | \n 10 | \n 6 | \n 1 | \n 50 | \n 5 | \n 2 | \n 1 | \n 0 | \n 1 | \n 1 | \n 3 | \n 2 | \n 2 | \n 0 | \n 20 | \n 2 | \n 0 | \n 4 | \n 0 | \n 0 | \n 2 | \n 3 | \n 0 | \n 4 | \n 1 | \n 0 | \n 0 | \n 1 | \n 1 | \n 0 | \n 1 | \n 0 | \n 1 | \n 0 | \n 0 | \n 9 | \n 2 | \n 0 | \n 0 | \n 0 | \n 1 | \n 0 | \n 0 | \n 1 | \n 0 | \n 5 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 1 | \n 0 | \n 0 | \n 0 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 84 | \n 1120 | \n 1540 | \n 530 | \n 1010 | \n 52 | \n 1 | \n 1 | \n 0 | \n 0 | \n 0 | \n 51 | \n 0 | \n 0 | \n 51 | \n
\n \n | 2 | \n 4 | \n 9 | \n 5.0 | \n 99999.0 | \n 9.0 | \n 999.0 | \n 99999.0 | \n 1539965777 | \n 29438413 | \n Amador | \n Amador County | \n 40474 | \n 18805 | \n 38.443549 | \n -120.653858 | \n 06 | \n 40474 | \n 36596 | \n 31104 | \n 1236 | \n 757 | \n 582 | \n 82 | \n 2835 | \n 3878 | \n 3591 | \n 163 | \n 1123 | \n 307 | \n 59 | \n 1804 | \n 20 | \n 5 | \n 0 | \n 6 | \n 18 | \n 2 | \n 15 | \n 59 | \n 6 | \n 4 | \n 261 | \n 28 | \n 7 | \n 4 | \n 12 | \n 34 | \n 11 | \n 87 | \n 26 | \n 19 | \n 5 | \n 2 | \n 1 | \n 1 | \n 8 | \n 1 | \n 7 | \n 0 | \n 0 | \n 0 | \n 8 | \n 17 | \n 0 | \n 2 | \n 4 | \n 1 | \n 4 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 5 | \n 0 | \n 0 | \n 0 | \n 0 | \n 9 | \n 5 | \n 3 | \n 1 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 6014 | \n 34460 | \n 18805 | \n 15678 | \n 3127 | \n 4311 | \n 4098 | \n 4045 | \n 2 | \n 51 | \n 0 | \n 213 | \n 0 | \n 0 | \n 213 | \n
\n \n | 3 | \n 4 | \n 9 | \n 7.0 | \n 17020.0 | \n 1.0 | \n 999.0 | \n 99999.0 | \n 4238488698 | \n 105260548 | \n Butte | \n Butte County | \n 211632 | \n 90133 | \n 39.665336 | \n -121.603209 | \n 06 | \n 211632 | \n 186947 | \n 149557 | \n 3644 | \n 4492 | \n 10533 | \n 573 | \n 18148 | \n 24685 | \n 22849 | \n 1764 | \n 6709 | \n 2396 | \n 388 | \n 10402 | \n 177 | \n 93 | \n 24 | \n 157 | \n 69 | \n 22 | \n 374 | \n 172 | \n 84 | \n 18 | \n 1652 | \n 345 | \n 97 | \n 16 | \n 124 | \n 162 | \n 61 | \n 480 | \n 182 | \n 87 | \n 21 | \n 16 | \n 1 | \n 21 | \n 4 | \n 7 | \n 0 | \n 5 | \n 16 | \n 1 | \n 6 | \n 156 | \n 30 | \n 7 | \n 41 | \n 1 | \n 6 | \n 7 | \n 29 | \n 23 | \n 2 | \n 7 | \n 0 | \n 2 | \n 0 | \n 0 | \n 1 | \n 28 | \n 12 | \n 11 | \n 2 | \n 3 | \n 0 | \n 0 | \n 0 | \n 0 | \n 40112 | \n 171520 | \n 90133 | \n 83268 | \n 6865 | \n 4941 | \n 1449 | \n 496 | \n 31 | \n 902 | \n 20 | \n 3492 | \n 2234 | \n 0 | \n 1258 | \n
\n \n | 4 | \n 4 | \n 9 | \n 9.0 | \n 99999.0 | \n 9.0 | \n 999.0 | \n 99999.0 | \n 2641837359 | \n 43789489 | \n Calaveras | \n Calaveras County | \n 45292 | \n 27422 | \n 38.191068 | \n -120.554106 | \n 06 | \n 45292 | \n 40264 | \n 36315 | \n 364 | \n 747 | \n 743 | \n 100 | \n 1995 | \n 5028 | \n 4706 | \n 195 | \n 1513 | \n 428 | \n 110 | \n 2285 | \n 13 | \n 13 | \n 0 | \n 24 | \n 6 | \n 6 | \n 43 | \n 39 | \n 28 | \n 3 | \n 285 | \n 15 | \n 8 | \n 2 | \n 28 | \n 25 | \n 24 | \n 104 | \n 39 | \n 21 | \n 0 | \n 8 | \n 0 | \n 2 | \n 0 | \n 0 | \n 0 | \n 0 | \n 5 | \n 0 | \n 4 | \n 31 | \n 6 | \n 1 | \n 4 | \n 0 | \n 7 | \n 0 | \n 4 | \n 0 | \n 6 | \n 3 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 5 | \n 3 | \n 0 | \n 0 | \n 1 | \n 1 | \n 0 | \n 1 | \n 1 | \n 5865 | \n 39427 | \n 27422 | \n 18758 | \n 8664 | \n 461 | \n 311 | \n 170 | \n 40 | \n 101 | \n 0 | \n 150 | \n 0 | \n 0 | \n 150 | \n
\n \n
\n
Out[23]:
",
"type": "htmlSandbox"
}
},
"output_type": "display_data"
}
],
"source": [
"data_ks_sub.head()"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "db61abe5-a2e0-46d5-b719-7a70cb59ddd9",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" REGION | \n",
" DIVISION | \n",
" COUNTY | \n",
" CBSA | \n",
" MEMI | \n",
" CSA | \n",
" METDIV | \n",
" AREALAND | \n",
" AREAWATR | \n",
" POP100 | \n",
" HU100 | \n",
" INTPTLAT | \n",
" INTPTLON | \n",
" P0010001 | \n",
" P0010002 | \n",
" P0010003 | \n",
" P0010004 | \n",
" P0010005 | \n",
" P0010006 | \n",
" P0010007 | \n",
" P0010008 | \n",
" P0010009 | \n",
" P0010010 | \n",
" P0010011 | \n",
" P0010012 | \n",
" P0010013 | \n",
" P0010014 | \n",
" P0010015 | \n",
" P0010016 | \n",
" P0010017 | \n",
" P0010018 | \n",
" P0010019 | \n",
" P0010020 | \n",
" P0010021 | \n",
" P0010022 | \n",
" P0010023 | \n",
" P0010024 | \n",
" P0010025 | \n",
" P0010026 | \n",
" P0010027 | \n",
" P0010028 | \n",
" P0010029 | \n",
" P0010030 | \n",
" P0010031 | \n",
" P0010032 | \n",
" P0010033 | \n",
" P0010034 | \n",
" P0010035 | \n",
" P0010036 | \n",
" P0010037 | \n",
" P0010038 | \n",
" P0010039 | \n",
" P0010040 | \n",
" P0010041 | \n",
" P0010042 | \n",
" P0010043 | \n",
" P0010044 | \n",
" P0010045 | \n",
" P0010046 | \n",
" P0010047 | \n",
" P0010048 | \n",
" P0010049 | \n",
" P0010050 | \n",
" P0010051 | \n",
" P0010052 | \n",
" P0010053 | \n",
" P0010054 | \n",
" P0010055 | \n",
" P0010056 | \n",
" P0010057 | \n",
" P0010058 | \n",
" P0010059 | \n",
" P0010060 | \n",
" P0010061 | \n",
" P0010062 | \n",
" P0010063 | \n",
" P0010064 | \n",
" P0010065 | \n",
" P0010066 | \n",
" P0010067 | \n",
" P0010068 | \n",
" P0010069 | \n",
" P0010070 | \n",
" P0010071 | \n",
" P0020002 | \n",
" P0020003 | \n",
" H0010001 | \n",
" H0010002 | \n",
" H0010003 | \n",
" P0050001 | \n",
" P0050002 | \n",
" P0050003 | \n",
" P0050004 | \n",
" P0050005 | \n",
" P0050006 | \n",
" P0050007 | \n",
" P0050008 | \n",
" P0050009 | \n",
" P0050010 | \n",
"
\n",
" \n",
" \n",
" \n",
" | count | \n",
" 669171.0 | \n",
" 669171.0 | \n",
" 650290.000000 | \n",
" 650290.000000 | \n",
" 650290.000000 | \n",
" 650290.000000 | \n",
" 650290.000000 | \n",
" 6.691710e+05 | \n",
" 6.691710e+05 | \n",
" 6.691710e+05 | \n",
" 6.691710e+05 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 6.691710e+05 | \n",
" 6.691710e+05 | \n",
" 6.691710e+05 | \n",
" 6.691710e+05 | \n",
" 669171.000000 | \n",
" 6.691710e+05 | \n",
" 669171.000000 | \n",
" 6.691710e+05 | \n",
" 6.691710e+05 | \n",
" 6.691710e+05 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 6.691710e+05 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 6.691710e+05 | \n",
" 6.691710e+05 | \n",
" 6.691710e+05 | \n",
" 6.691710e+05 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
" 669171.000000 | \n",
"
\n",
" \n",
" | mean | \n",
" 4.0 | \n",
" 9.0 | \n",
" 56.366932 | \n",
" 38679.260718 | \n",
" 1.389852 | \n",
" 554.299556 | \n",
" 76237.787180 | \n",
" 2.867752e+07 | \n",
" 1.445348e+06 | \n",
" 3.059615e+03 | \n",
" 1.113522e+03 | \n",
" 36.032115 | \n",
" -119.640668 | \n",
" 3.059615e+03 | \n",
" 2.613714e+03 | \n",
" 1.258459e+03 | \n",
" 1.735204e+02 | \n",
" 48.956882 | \n",
" 4.722800e+02 | \n",
" 12.190836 | \n",
" 6.483072e+02 | \n",
" 4.459009e+02 | \n",
" 4.164644e+02 | \n",
" 19.981495 | \n",
" 29.663312 | \n",
" 48.420317 | \n",
" 3.510182 | \n",
" 2.807234e+02 | \n",
" 2.895796 | \n",
" 4.014609 | \n",
" 0.679218 | \n",
" 6.895657 | \n",
" 1.020705 | \n",
" 0.198602 | \n",
" 8.816177 | \n",
" 3.977472 | \n",
" 4.740207 | \n",
" 0.927255 | \n",
" 26.405721 | \n",
" 3.201569 | \n",
" 1.867131 | \n",
" 0.258128 | \n",
" 2.551366 | \n",
" 1.707460 | \n",
" 0.255435 | \n",
" 9.248521 | \n",
" 2.400646 | \n",
" 3.273395 | \n",
" 0.328717 | \n",
" 0.200009 | \n",
" 0.042896 | \n",
" 0.261858 | \n",
" 0.204357 | \n",
" 0.201475 | \n",
" 0.046879 | \n",
" 0.074201 | \n",
" 0.113360 | \n",
" 0.024414 | \n",
" 0.143903 | \n",
" 2.678410 | \n",
" 0.503423 | \n",
" 0.075836 | \n",
" 0.920390 | \n",
" 0.150779 | \n",
" 0.211666 | \n",
" 0.025950 | \n",
" 0.195499 | \n",
" 0.332096 | \n",
" 0.032527 | \n",
" 0.160809 | \n",
" 0.020153 | \n",
" 0.021743 | \n",
" 0.005952 | \n",
" 0.013167 | \n",
" 0.008419 | \n",
" 0.317668 | \n",
" 0.103903 | \n",
" 0.154975 | \n",
" 0.018214 | \n",
" 0.016044 | \n",
" 0.022053 | \n",
" 0.002479 | \n",
" 0.034718 | \n",
" 0.034718 | \n",
" 1.206501e+03 | \n",
" 1.853114e+03 | \n",
" 1.113522e+03 | \n",
" 1.042878e+03 | \n",
" 70.643138 | \n",
" 70.686723 | \n",
" 26.401839 | \n",
" 15.296785 | \n",
" 0.681406 | \n",
" 9.684245 | \n",
" 0.739403 | \n",
" 44.284884 | \n",
" 17.845793 | \n",
" 4.347792 | \n",
" 22.091300 | \n",
"
\n",
" \n",
" | std | \n",
" 0.0 | \n",
" 0.0 | \n",
" 28.317559 | \n",
" 15294.999451 | \n",
" 1.623581 | \n",
" 270.123559 | \n",
" 33581.038975 | \n",
" 7.881046e+08 | \n",
" 4.494612e+07 | \n",
" 6.640547e+04 | \n",
" 2.443134e+04 | \n",
" 2.306609 | \n",
" 2.090244 | \n",
" 6.640547e+04 | \n",
" 5.685302e+04 | \n",
" 2.652604e+04 | \n",
" 4.595227e+03 | \n",
" 1060.294701 | \n",
" 1.109547e+04 | \n",
" 278.185648 | \n",
" 1.528675e+04 | \n",
" 9.606180e+03 | \n",
" 8.971495e+03 | \n",
" 448.843967 | \n",
" 590.845073 | \n",
" 1074.912895 | \n",
" 72.655065 | \n",
" 6.136860e+03 | \n",
" 71.657002 | \n",
" 94.854026 | \n",
" 15.986772 | \n",
" 179.105096 | \n",
" 22.166135 | \n",
" 4.224634 | \n",
" 206.505505 | \n",
" 87.478339 | \n",
" 106.047371 | \n",
" 21.221856 | \n",
" 573.152579 | \n",
" 72.159672 | \n",
" 42.057611 | \n",
" 5.747667 | \n",
" 57.865064 | \n",
" 35.356409 | \n",
" 5.169246 | \n",
" 204.175087 | \n",
" 51.408999 | \n",
" 70.475633 | \n",
" 6.914170 | \n",
" 4.636602 | \n",
" 1.102241 | \n",
" 6.325830 | \n",
" 4.855389 | \n",
" 4.731521 | \n",
" 1.141002 | \n",
" 1.580562 | \n",
" 2.467501 | \n",
" 0.535403 | \n",
" 3.167474 | \n",
" 59.439956 | \n",
" 11.468647 | \n",
" 1.720186 | \n",
" 21.449689 | \n",
" 3.420698 | \n",
" 4.873443 | \n",
" 0.583221 | \n",
" 4.109139 | \n",
" 7.215088 | \n",
" 0.689721 | \n",
" 3.441005 | \n",
" 0.502150 | \n",
" 0.498700 | \n",
" 0.178709 | \n",
" 0.296527 | \n",
" 0.203187 | \n",
" 7.078996 | \n",
" 2.364862 | \n",
" 3.568689 | \n",
" 0.397596 | \n",
" 0.381318 | \n",
" 0.529630 | \n",
" 0.083171 | \n",
" 0.845348 | \n",
" 0.845348 | \n",
" 2.743279e+04 | \n",
" 4.009405e+04 | \n",
" 2.443134e+04 | \n",
" 2.290392e+04 | \n",
" 1604.306771 | \n",
" 1662.175365 | \n",
" 577.936618 | \n",
" 372.600414 | \n",
" 16.466468 | \n",
" 227.472784 | \n",
" 25.182710 | \n",
" 1168.024862 | \n",
" 555.486360 | \n",
" 221.161306 | \n",
" 568.743029 | \n",
"
\n",
" \n",
" | min | \n",
" 4.0 | \n",
" 9.0 | \n",
" 1.000000 | \n",
" 12540.000000 | \n",
" 1.000000 | \n",
" 260.000000 | \n",
" 11244.000000 | \n",
" 0.000000e+00 | \n",
" 0.000000e+00 | \n",
" 0.000000e+00 | \n",
" 0.000000e+00 | \n",
" 32.539551 | \n",
" -124.413693 | \n",
" 0.000000e+00 | \n",
" 0.000000e+00 | \n",
" 0.000000e+00 | \n",
" 0.000000e+00 | \n",
" 0.000000 | \n",
" 0.000000e+00 | \n",
" 0.000000 | \n",
" 0.000000e+00 | \n",
" 0.000000e+00 | \n",
" 0.000000e+00 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000e+00 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000e+00 | \n",
" 0.000000e+00 | \n",
" 0.000000e+00 | \n",
" 0.000000e+00 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
"
\n",
" \n",
" | 25% | \n",
" 4.0 | \n",
" 9.0 | \n",
" 37.000000 | \n",
" 31080.000000 | \n",
" 1.000000 | \n",
" 348.000000 | \n",
" 36084.000000 | \n",
" 1.665900e+04 | \n",
" 0.000000e+00 | \n",
" 7.000000e+00 | \n",
" 2.000000e+00 | \n",
" 34.005323 | \n",
" -121.637698 | \n",
" 7.000000e+00 | \n",
" 5.000000e+00 | \n",
" 1.000000e+00 | \n",
" 0.000000e+00 | \n",
" 0.000000 | \n",
" 0.000000e+00 | \n",
" 0.000000 | \n",
" 0.000000e+00 | \n",
" 0.000000e+00 | \n",
" 0.000000e+00 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000e+00 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000e+00 | \n",
" 2.000000e+00 | \n",
" 2.000000e+00 | \n",
" 1.000000e+00 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
"
\n",
" \n",
" | 50% | \n",
" 4.0 | \n",
" 9.0 | \n",
" 59.000000 | \n",
" 40140.000000 | \n",
" 1.000000 | \n",
" 472.000000 | \n",
" 99999.000000 | \n",
" 5.159000e+04 | \n",
" 0.000000e+00 | \n",
" 6.100000e+01 | \n",
" 2.100000e+01 | \n",
" 35.434519 | \n",
" -119.269756 | \n",
" 6.100000e+01 | \n",
" 5.000000e+01 | \n",
" 2.300000e+01 | \n",
" 0.000000e+00 | \n",
" 0.000000 | \n",
" 2.000000e+00 | \n",
" 0.000000 | \n",
" 5.000000e+00 | \n",
" 9.000000e+00 | \n",
" 8.000000e+00 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 4.000000e+00 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 1.500000e+01 | \n",
" 3.300000e+01 | \n",
" 2.100000e+01 | \n",
" 1.900000e+01 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
"
\n",
" \n",
" | 75% | \n",
" 4.0 | \n",
" 9.0 | \n",
" 75.000000 | \n",
" 41860.000000 | \n",
" 1.000000 | \n",
" 999.000000 | \n",
" 99999.000000 | \n",
" 6.380330e+05 | \n",
" 0.000000e+00 | \n",
" 2.460000e+02 | \n",
" 9.300000e+01 | \n",
" 37.866010 | \n",
" -117.930126 | \n",
" 2.460000e+02 | \n",
" 2.130000e+02 | \n",
" 1.050000e+02 | \n",
" 1.000000e+01 | \n",
" 4.000000 | \n",
" 2.900000e+01 | \n",
" 1.000000 | \n",
" 4.800000e+01 | \n",
" 3.600000e+01 | \n",
" 3.400000e+01 | \n",
" 2.000000 | \n",
" 3.000000 | \n",
" 4.000000 | \n",
" 0.000000 | \n",
" 2.400000e+01 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 3.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 1.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 9.600000e+01 | \n",
" 1.480000e+02 | \n",
" 9.300000e+01 | \n",
" 8.700000e+01 | \n",
" 7.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
"
\n",
" \n",
" | max | \n",
" 4.0 | \n",
" 9.0 | \n",
" 115.000000 | \n",
" 99999.000000 | \n",
" 9.000000 | \n",
" 999.000000 | \n",
" 99999.000000 | \n",
" 2.820553e+11 | \n",
" 1.571963e+10 | \n",
" 2.857386e+07 | \n",
" 1.057185e+07 | \n",
" 42.007419 | \n",
" -114.139264 | \n",
" 2.857386e+07 | \n",
" 2.448500e+07 | \n",
" 1.157646e+07 | \n",
" 1.799185e+06 | \n",
" 447548.000000 | \n",
" 4.474283e+06 | \n",
" 115115.000000 | \n",
" 6.072412e+06 | \n",
" 4.088855e+06 | \n",
" 3.811637e+06 | \n",
" 194177.000000 | \n",
" 262089.000000 | \n",
" 459478.000000 | \n",
" 31625.000000 | \n",
" 2.532955e+06 | \n",
" 29671.000000 | \n",
" 40474.000000 | \n",
" 6789.000000 | \n",
" 69354.000000 | \n",
" 9699.000000 | \n",
" 1847.000000 | \n",
" 82008.000000 | \n",
" 37940.000000 | \n",
" 44752.000000 | \n",
" 8779.000000 | \n",
" 247939.000000 | \n",
" 31244.000000 | \n",
" 18189.000000 | \n",
" 2467.000000 | \n",
" 24478.000000 | \n",
" 15573.000000 | \n",
" 2273.000000 | \n",
" 85549.000000 | \n",
" 22286.000000 | \n",
" 29988.000000 | \n",
" 2983.000000 | \n",
" 1983.000000 | \n",
" 455.000000 | \n",
" 2648.000000 | \n",
" 2083.000000 | \n",
" 1976.000000 | \n",
" 475.000000 | \n",
" 682.000000 | \n",
" 1045.000000 | \n",
" 211.000000 | \n",
" 1351.000000 | \n",
" 25817.000000 | \n",
" 5001.000000 | \n",
" 746.000000 | \n",
" 8969.000000 | \n",
" 1473.000000 | \n",
" 2086.000000 | \n",
" 243.000000 | \n",
" 1780.000000 | \n",
" 3058.000000 | \n",
" 293.000000 | \n",
" 1507.000000 | \n",
" 209.000000 | \n",
" 206.000000 | \n",
" 64.000000 | \n",
" 105.000000 | \n",
" 77.000000 | \n",
" 3120.000000 | \n",
" 1043.000000 | \n",
" 1529.000000 | \n",
" 164.000000 | \n",
" 153.000000 | \n",
" 208.000000 | \n",
" 23.000000 | \n",
" 342.000000 | \n",
" 342.000000 | \n",
" 1.112872e+07 | \n",
" 1.744514e+07 | \n",
" 1.057185e+07 | \n",
" 9.866472e+06 | \n",
" 705375.000000 | \n",
" 696051.000000 | \n",
" 234511.000000 | \n",
" 126683.000000 | \n",
" 6408.000000 | \n",
" 93493.000000 | \n",
" 7927.000000 | \n",
" 461540.000000 | \n",
" 197511.000000 | \n",
" 39597.000000 | \n",
" 226824.000000 | \n",
"
\n",
" \n",
"
\n",
"
\n\n
\n \n \n | \n REGION | \n DIVISION | \n COUNTY | \n CBSA | \n MEMI | \n CSA | \n METDIV | \n AREALAND | \n AREAWATR | \n POP100 | \n HU100 | \n INTPTLAT | \n INTPTLON | \n P0010001 | \n P0010002 | \n P0010003 | \n P0010004 | \n P0010005 | \n P0010006 | \n P0010007 | \n P0010008 | \n P0010009 | \n P0010010 | \n P0010011 | \n P0010012 | \n P0010013 | \n P0010014 | \n P0010015 | \n P0010016 | \n P0010017 | \n P0010018 | \n P0010019 | \n P0010020 | \n P0010021 | \n P0010022 | \n P0010023 | \n P0010024 | \n P0010025 | \n P0010026 | \n P0010027 | \n P0010028 | \n P0010029 | \n P0010030 | \n P0010031 | \n P0010032 | \n P0010033 | \n P0010034 | \n P0010035 | \n P0010036 | \n P0010037 | \n P0010038 | \n P0010039 | \n P0010040 | \n P0010041 | \n P0010042 | \n P0010043 | \n P0010044 | \n P0010045 | \n P0010046 | \n P0010047 | \n P0010048 | \n P0010049 | \n P0010050 | \n P0010051 | \n P0010052 | \n P0010053 | \n P0010054 | \n P0010055 | \n P0010056 | \n P0010057 | \n P0010058 | \n P0010059 | \n P0010060 | \n P0010061 | \n P0010062 | \n P0010063 | \n P0010064 | \n P0010065 | \n P0010066 | \n P0010067 | \n P0010068 | \n P0010069 | \n P0010070 | \n P0010071 | \n P0020002 | \n P0020003 | \n H0010001 | \n H0010002 | \n H0010003 | \n P0050001 | \n P0050002 | \n P0050003 | \n P0050004 | \n P0050005 | \n P0050006 | \n P0050007 | \n P0050008 | \n P0050009 | \n P0050010 | \n
\n \n \n \n | count | \n 669171.0 | \n 669171.0 | \n 650290.000000 | \n 650290.000000 | \n 650290.000000 | \n 650290.000000 | \n 650290.000000 | \n 6.691710e+05 | \n 6.691710e+05 | \n 6.691710e+05 | \n 6.691710e+05 | \n 669171.000000 | \n 669171.000000 | \n 6.691710e+05 | \n 6.691710e+05 | \n 6.691710e+05 | \n 6.691710e+05 | \n 669171.000000 | \n 6.691710e+05 | \n 669171.000000 | \n 6.691710e+05 | \n 6.691710e+05 | \n 6.691710e+05 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 6.691710e+05 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 6.691710e+05 | \n 6.691710e+05 | \n 6.691710e+05 | \n 6.691710e+05 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n 669171.000000 | \n
\n \n | mean | \n 4.0 | \n 9.0 | \n 56.366932 | \n 38679.260718 | \n 1.389852 | \n 554.299556 | \n 76237.787180 | \n 2.867752e+07 | \n 1.445348e+06 | \n 3.059615e+03 | \n 1.113522e+03 | \n 36.032115 | \n -119.640668 | \n 3.059615e+03 | \n 2.613714e+03 | \n 1.258459e+03 | \n 1.735204e+02 | \n 48.956882 | \n 4.722800e+02 | \n 12.190836 | \n 6.483072e+02 | \n 4.459009e+02 | \n 4.164644e+02 | \n 19.981495 | \n 29.663312 | \n 48.420317 | \n 3.510182 | \n 2.807234e+02 | \n 2.895796 | \n 4.014609 | \n 0.679218 | \n 6.895657 | \n 1.020705 | \n 0.198602 | \n 8.816177 | \n 3.977472 | \n 4.740207 | \n 0.927255 | \n 26.405721 | \n 3.201569 | \n 1.867131 | \n 0.258128 | \n 2.551366 | \n 1.707460 | \n 0.255435 | \n 9.248521 | \n 2.400646 | \n 3.273395 | \n 0.328717 | \n 0.200009 | \n 0.042896 | \n 0.261858 | \n 0.204357 | \n 0.201475 | \n 0.046879 | \n 0.074201 | \n 0.113360 | \n 0.024414 | \n 0.143903 | \n 2.678410 | \n 0.503423 | \n 0.075836 | \n 0.920390 | \n 0.150779 | \n 0.211666 | \n 0.025950 | \n 0.195499 | \n 0.332096 | \n 0.032527 | \n 0.160809 | \n 0.020153 | \n 0.021743 | \n 0.005952 | \n 0.013167 | \n 0.008419 | \n 0.317668 | \n 0.103903 | \n 0.154975 | \n 0.018214 | \n 0.016044 | \n 0.022053 | \n 0.002479 | \n 0.034718 | \n 0.034718 | \n 1.206501e+03 | \n 1.853114e+03 | \n 1.113522e+03 | \n 1.042878e+03 | \n 70.643138 | \n 70.686723 | \n 26.401839 | \n 15.296785 | \n 0.681406 | \n 9.684245 | \n 0.739403 | \n 44.284884 | \n 17.845793 | \n 4.347792 | \n 22.091300 | \n
\n \n | std | \n 0.0 | \n 0.0 | \n 28.317559 | \n 15294.999451 | \n 1.623581 | \n 270.123559 | \n 33581.038975 | \n 7.881046e+08 | \n 4.494612e+07 | \n 6.640547e+04 | \n 2.443134e+04 | \n 2.306609 | \n 2.090244 | \n 6.640547e+04 | \n 5.685302e+04 | \n 2.652604e+04 | \n 4.595227e+03 | \n 1060.294701 | \n 1.109547e+04 | \n 278.185648 | \n 1.528675e+04 | \n 9.606180e+03 | \n 8.971495e+03 | \n 448.843967 | \n 590.845073 | \n 1074.912895 | \n 72.655065 | \n 6.136860e+03 | \n 71.657002 | \n 94.854026 | \n 15.986772 | \n 179.105096 | \n 22.166135 | \n 4.224634 | \n 206.505505 | \n 87.478339 | \n 106.047371 | \n 21.221856 | \n 573.152579 | \n 72.159672 | \n 42.057611 | \n 5.747667 | \n 57.865064 | \n 35.356409 | \n 5.169246 | \n 204.175087 | \n 51.408999 | \n 70.475633 | \n 6.914170 | \n 4.636602 | \n 1.102241 | \n 6.325830 | \n 4.855389 | \n 4.731521 | \n 1.141002 | \n 1.580562 | \n 2.467501 | \n 0.535403 | \n 3.167474 | \n 59.439956 | \n 11.468647 | \n 1.720186 | \n 21.449689 | \n 3.420698 | \n 4.873443 | \n 0.583221 | \n 4.109139 | \n 7.215088 | \n 0.689721 | \n 3.441005 | \n 0.502150 | \n 0.498700 | \n 0.178709 | \n 0.296527 | \n 0.203187 | \n 7.078996 | \n 2.364862 | \n 3.568689 | \n 0.397596 | \n 0.381318 | \n 0.529630 | \n 0.083171 | \n 0.845348 | \n 0.845348 | \n 2.743279e+04 | \n 4.009405e+04 | \n 2.443134e+04 | \n 2.290392e+04 | \n 1604.306771 | \n 1662.175365 | \n 577.936618 | \n 372.600414 | \n 16.466468 | \n 227.472784 | \n 25.182710 | \n 1168.024862 | \n 555.486360 | \n 221.161306 | \n 568.743029 | \n
\n \n | min | \n 4.0 | \n 9.0 | \n 1.000000 | \n 12540.000000 | \n 1.000000 | \n 260.000000 | \n 11244.000000 | \n 0.000000e+00 | \n 0.000000e+00 | \n 0.000000e+00 | \n 0.000000e+00 | \n 32.539551 | \n -124.413693 | \n 0.000000e+00 | \n 0.000000e+00 | \n 0.000000e+00 | \n 0.000000e+00 | \n 0.000000 | \n 0.000000e+00 | \n 0.000000 | \n 0.000000e+00 | \n 0.000000e+00 | \n 0.000000e+00 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000e+00 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000e+00 | \n 0.000000e+00 | \n 0.000000e+00 | \n 0.000000e+00 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n
\n \n | 25% | \n 4.0 | \n 9.0 | \n 37.000000 | \n 31080.000000 | \n 1.000000 | \n 348.000000 | \n 36084.000000 | \n 1.665900e+04 | \n 0.000000e+00 | \n 7.000000e+00 | \n 2.000000e+00 | \n 34.005323 | \n -121.637698 | \n 7.000000e+00 | \n 5.000000e+00 | \n 1.000000e+00 | \n 0.000000e+00 | \n 0.000000 | \n 0.000000e+00 | \n 0.000000 | \n 0.000000e+00 | \n 0.000000e+00 | \n 0.000000e+00 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000e+00 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000e+00 | \n 2.000000e+00 | \n 2.000000e+00 | \n 1.000000e+00 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n
\n \n | 50% | \n 4.0 | \n 9.0 | \n 59.000000 | \n 40140.000000 | \n 1.000000 | \n 472.000000 | \n 99999.000000 | \n 5.159000e+04 | \n 0.000000e+00 | \n 6.100000e+01 | \n 2.100000e+01 | \n 35.434519 | \n -119.269756 | \n 6.100000e+01 | \n 5.000000e+01 | \n 2.300000e+01 | \n 0.000000e+00 | \n 0.000000 | \n 2.000000e+00 | \n 0.000000 | \n 5.000000e+00 | \n 9.000000e+00 | \n 8.000000e+00 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 4.000000e+00 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 1.500000e+01 | \n 3.300000e+01 | \n 2.100000e+01 | \n 1.900000e+01 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n
\n \n | 75% | \n 4.0 | \n 9.0 | \n 75.000000 | \n 41860.000000 | \n 1.000000 | \n 999.000000 | \n 99999.000000 | \n 6.380330e+05 | \n 0.000000e+00 | \n 2.460000e+02 | \n 9.300000e+01 | \n 37.866010 | \n -117.930126 | \n 2.460000e+02 | \n 2.130000e+02 | \n 1.050000e+02 | \n 1.000000e+01 | \n 4.000000 | \n 2.900000e+01 | \n 1.000000 | \n 4.800000e+01 | \n 3.600000e+01 | \n 3.400000e+01 | \n 2.000000 | \n 3.000000 | \n 4.000000 | \n 0.000000 | \n 2.400000e+01 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 3.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 1.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 9.600000e+01 | \n 1.480000e+02 | \n 9.300000e+01 | \n 8.700000e+01 | \n 7.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n 0.000000 | \n
\n \n | max | \n 4.0 | \n 9.0 | \n 115.000000 | \n 99999.000000 | \n 9.000000 | \n 999.000000 | \n 99999.000000 | \n 2.820553e+11 | \n 1.571963e+10 | \n 2.857386e+07 | \n 1.057185e+07 | \n 42.007419 | \n -114.139264 | \n 2.857386e+07 | \n 2.448500e+07 | \n 1.157646e+07 | \n 1.799185e+06 | \n 447548.000000 | \n 4.474283e+06 | \n 115115.000000 | \n 6.072412e+06 | \n 4.088855e+06 | \n 3.811637e+06 | \n 194177.000000 | \n 262089.000000 | \n 459478.000000 | \n 31625.000000 | \n 2.532955e+06 | \n 29671.000000 | \n 40474.000000 | \n 6789.000000 | \n 69354.000000 | \n 9699.000000 | \n 1847.000000 | \n 82008.000000 | \n 37940.000000 | \n 44752.000000 | \n 8779.000000 | \n 247939.000000 | \n 31244.000000 | \n 18189.000000 | \n 2467.000000 | \n 24478.000000 | \n 15573.000000 | \n 2273.000000 | \n 85549.000000 | \n 22286.000000 | \n 29988.000000 | \n 2983.000000 | \n 1983.000000 | \n 455.000000 | \n 2648.000000 | \n 2083.000000 | \n 1976.000000 | \n 475.000000 | \n 682.000000 | \n 1045.000000 | \n 211.000000 | \n 1351.000000 | \n 25817.000000 | \n 5001.000000 | \n 746.000000 | \n 8969.000000 | \n 1473.000000 | \n 2086.000000 | \n 243.000000 | \n 1780.000000 | \n 3058.000000 | \n 293.000000 | \n 1507.000000 | \n 209.000000 | \n 206.000000 | \n 64.000000 | \n 105.000000 | \n 77.000000 | \n 3120.000000 | \n 1043.000000 | \n 1529.000000 | \n 164.000000 | \n 153.000000 | \n 208.000000 | \n 23.000000 | \n 342.000000 | \n 342.000000 | \n 1.112872e+07 | \n 1.744514e+07 | \n 1.057185e+07 | \n 9.866472e+06 | \n 705375.000000 | \n 696051.000000 | \n 234511.000000 | \n 126683.000000 | \n 6408.000000 | \n 93493.000000 | \n 7927.000000 | \n 461540.000000 | \n 197511.000000 | \n 39597.000000 | \n 226824.000000 | \n
\n \n
\n
/local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages/databricks/koalas/typedef/typehints.py:107: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\nDeprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n elif tpe in (int, "int", np.int, np.int32):\n/local_disk0/.ephemeral_nfs/envs/pythonEnv-bd1e69b1-2fa0-4958-8425-91e81ed1d661/lib/python3.7/site-packages/databricks/koalas/typedef/typehints.py:111: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.\nDeprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n elif tpe in (float, "float", np.float):\nOut[24]:
",
"type": "htmlSandbox"
}
},
"output_type": "display_data"
}
],
"source": [
"data_ks_sub.describe()"
]
},
{
"cell_type": "markdown",
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "9ceb7b70-4add-4851-ae33-95596f06e1e8",
"showTitle": false,
"title": ""
}
},
"source": [
"Noticing the following issues from the 'describe' table:\n",
"Some counties have 0 value for POP100 (population count 100%), HU100 (Housing count 100%), H0010001 (Total) ????"
]
},
{
"cell_type": "markdown",
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "32350a25-6786-457e-b87a-86557ba07b6a",
"showTitle": false,
"title": ""
}
},
"source": [
"### Plot population be city / county / school district / census tract"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "727258ab-2a63-4555-8b16-f958b976610a",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" NAME | \n",
" Total Population | \n",
" INTPTLAT | \n",
" INTPTLON | \n",
"
\n",
" \n",
" \n",
" \n",
" | 0 | \n",
" Alameda County | \n",
" 1682353 | \n",
" 37.647139 | \n",
" -121.912488 | \n",
"
\n",
" \n",
" | 1 | \n",
" Alpine County | \n",
" 1204 | \n",
" 38.621783 | \n",
" -119.798352 | \n",
"
\n",
" \n",
" | 2 | \n",
" Amador County | \n",
" 40474 | \n",
" 38.443549 | \n",
" -120.653858 | \n",
"
\n",
" \n",
" | 3 | \n",
" Butte County | \n",
" 211632 | \n",
" 39.665336 | \n",
" -121.603209 | \n",
"
\n",
" \n",
" | 4 | \n",
" Calaveras County | \n",
" 45292 | \n",
" 38.191068 | \n",
" -120.554106 | \n",
"
\n",
" \n",
"
\n",
"
\n\n
\n \n \n | \n NAME | \n Total Population | \n INTPTLAT | \n INTPTLON | \n
\n \n \n \n | 0 | \n Alameda County | \n 1682353 | \n 37.647139 | \n -121.912488 | \n
\n \n | 1 | \n Alpine County | \n 1204 | \n 38.621783 | \n -119.798352 | \n
\n \n | 2 | \n Amador County | \n 40474 | \n 38.443549 | \n -120.653858 | \n
\n \n | 3 | \n Butte County | \n 211632 | \n 39.665336 | \n -121.603209 | \n
\n \n | 4 | \n Calaveras County | \n 45292 | \n 38.191068 | \n -120.554106 | \n
\n \n
\n
Out[25]:
",
"type": "htmlSandbox"
}
},
"output_type": "display_data"
}
],
"source": [
"# Plot NAME vs POP100\n",
"\n",
"plot_df = data_ks_sub[[\"NAME\",\"POP100\",\"INTPTLAT\",\"INTPTLON\"]]\n",
"plot_df.rename(columns={\"POP100\":\"Total Population\"}, inplace=True)\n",
"plot_df.head()"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "82f2c46c-57f3-492e-808c-871346ca4f09",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"Out[26]: NAME object\n",
"Total Population int32\n",
"INTPTLAT float64\n",
"INTPTLON float64\n",
"dtype: object
"
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "Out[26]: NAME object\nTotal Population int32\nINTPTLAT float64\nINTPTLON float64\ndtype: object
",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"plot_df.dtypes"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "034508a1-8e5f-441e-85f7-9af186cbf09c",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
""
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"#plot_df[\"NAME\"].value_counts()"
]
},
{
"cell_type": "markdown",
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "660d4ac3-ba4c-46f0-8138-d9258906d206",
"showTitle": false,
"title": ""
}
},
"source": [
"The NAME column has County / City / Block / Census Tract / School District.\n",
"Separating County data"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "49006f08-f57c-416f-93d6-67a92129c41c",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
""
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"pd_temp = plot_df.toPandas()\n",
"pd_temp_city = pd_temp[pd_temp[\"NAME\"].str.contains('city', regex=False)].drop_duplicates(subset=[\"NAME\"])\n",
"pd_temp_county = pd_temp[pd_temp[\"NAME\"].str.contains('County', regex=False)].drop_duplicates(subset=[\"NAME\"])\n",
"pd_temp_school_district = pd_temp[pd_temp[\"NAME\"].str.contains('School District', regex=False)].drop_duplicates(subset=[\"NAME\"])\n",
"pd_temp_census_tract = pd_temp[pd_temp[\"NAME\"].str.contains('Census Tract', regex=False)].drop_duplicates(subset=[\"NAME\"])\n",
"pd_temp_block = pd_temp[pd_temp[\"NAME\"].str.contains('Block', regex=False)].drop_duplicates(subset=[\"NAME\"])"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "f02159e3-3208-44d8-84ca-27db383a7b7c",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"image/png": "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"
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "/plots/c10557ac-89bf-4871-878a-4de3e4b48268.png",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "image"
}
},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(25,10))\n",
"\n",
"splot = sns.barplot(x=\"NAME\",y=\"Total Population\", palette=\"viridis\", data=pd_temp_city.sample(n=50, random_state=1))\n",
"splot.axes.set_title(\"City population\",fontsize=40)\n",
"splot.set_xlabel(\"Cities\",fontsize=20)\n",
"splot.tick_params(labelsize=13)\n",
"\n",
"for item in splot.get_xticklabels():\n",
" item.set_rotation(90)"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "16401caf-e302-4cfd-888c-37bae0105a63",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"image/png": "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"
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "/plots/ec50ccad-4ce8-4744-a507-4745c31425b9.png",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "image"
}
},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(25,10))\n",
"\n",
"splot = sns.barplot(x=\"NAME\",y=\"Total Population\", palette=\"viridis\", data=pd_temp_county.sample(n=100, random_state=1))\n",
"splot.axes.set_title(\"County population\",fontsize=40)\n",
"splot.set_xlabel(\"Counties\",fontsize=20)\n",
"splot.tick_params(labelsize=13)\n",
"\n",
"for item in splot.get_xticklabels():\n",
" item.set_rotation(90)"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "922c317e-f027-4f2f-be07-e2993166e195",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"image/png": "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"
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "/plots/6b0695ba-9601-468c-bfc2-a6f71057b266.png",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "image"
}
},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(25,10))\n",
"\n",
"splot = sns.barplot(x=\"NAME\",y=\"Total Population\", palette=\"viridis\", data=pd_temp_school_district.sample(n=50, random_state=1))\n",
"splot.axes.set_title(\"School District population\",fontsize=40)\n",
"splot.set_xlabel(\"School Districts\",fontsize=20)\n",
"splot.tick_params(labelsize=13)\n",
"\n",
"for item in splot.get_xticklabels():\n",
" item.set_rotation(90)"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "2df6dc43-7ef9-43a8-8bf1-2ebe5c806ff4",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"image/png": "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"
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "/plots/5f85215d-4503-4155-b83b-7e0a5ea83fe7.png",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "image"
}
},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(25,10))\n",
"\n",
"splot = sns.barplot(x=\"NAME\",y=\"Total Population\", palette=\"viridis\", data=pd_temp_census_tract.sample(n=50, random_state=1))\n",
"splot.axes.set_title(\"Census Tract - population\",fontsize=40)\n",
"splot.set_xlabel(\"Census Tracts\",fontsize=20)\n",
"splot.tick_params(labelsize=13)\n",
"\n",
"for item in splot.get_xticklabels():\n",
" item.set_rotation(90)"
]
},
{
"cell_type": "markdown",
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "ae52c465-257b-488e-9b03-cf276908e7cc",
"showTitle": false,
"title": ""
}
},
"source": [
"### Plot population distribution by ethnicity in San Diego County"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "f5ac27c8-1b1c-46b8-9ff2-04aad4404161",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" NAME | \n",
" White | \n",
" Black or African American | \n",
" American Indian and Alaska Native | \n",
" Asian | \n",
" Native Hawaiian and Other Pacific Islander | \n",
" Some Other Race | \n",
" Hispanic or Latino | \n",
"
\n",
" \n",
" \n",
" \n",
" | 0 | \n",
" Alameda County | \n",
" 523836 | \n",
" 164879 | \n",
" 19659 | \n",
" 545261 | \n",
" 14123 | \n",
" 223779 | \n",
" 393749 | \n",
"
\n",
" \n",
" | 1 | \n",
" Alpine County | \n",
" 814 | \n",
" 10 | \n",
" 236 | \n",
" 12 | \n",
" 0 | \n",
" 13 | \n",
" 84 | \n",
"
\n",
" \n",
" | 2 | \n",
" Amador County | \n",
" 31104 | \n",
" 1236 | \n",
" 757 | \n",
" 582 | \n",
" 82 | \n",
" 2835 | \n",
" 6014 | \n",
"
\n",
" \n",
" | 3 | \n",
" Butte County | \n",
" 149557 | \n",
" 3644 | \n",
" 4492 | \n",
" 10533 | \n",
" 573 | \n",
" 18148 | \n",
" 40112 | \n",
"
\n",
" \n",
" | 4 | \n",
" Calaveras County | \n",
" 36315 | \n",
" 364 | \n",
" 747 | \n",
" 743 | \n",
" 100 | \n",
" 1995 | \n",
" 5865 | \n",
"
\n",
" \n",
"
\n",
"
\n\n
\n \n \n | \n NAME | \n White | \n Black or African American | \n American Indian and Alaska Native | \n Asian | \n Native Hawaiian and Other Pacific Islander | \n Some Other Race | \n Hispanic or Latino | \n
\n \n \n \n | 0 | \n Alameda County | \n 523836 | \n 164879 | \n 19659 | \n 545261 | \n 14123 | \n 223779 | \n 393749 | \n
\n \n | 1 | \n Alpine County | \n 814 | \n 10 | \n 236 | \n 12 | \n 0 | \n 13 | \n 84 | \n
\n \n | 2 | \n Amador County | \n 31104 | \n 1236 | \n 757 | \n 582 | \n 82 | \n 2835 | \n 6014 | \n
\n \n | 3 | \n Butte County | \n 149557 | \n 3644 | \n 4492 | \n 10533 | \n 573 | \n 18148 | \n 40112 | \n
\n \n | 4 | \n Calaveras County | \n 36315 | \n 364 | \n 747 | \n 743 | \n 100 | \n 1995 | \n 5865 | \n
\n \n
\n
Out[33]:
",
"type": "htmlSandbox"
}
},
"output_type": "display_data"
}
],
"source": [
"# For a NAME, check the distribution of population by one race\n",
"# P0010001 Total:\n",
"# P0010002 Population of one race:\n",
"# P0010003 White alone\n",
"# P0010004 Black or African American alone\n",
"# P0010005 American Indian and Alaska Native alone\n",
"# P0010006 Asian alone\n",
"# P0010007 Native Hawaiian and Other Pacific Islander alone\n",
"# P0010008 Some Other Race alone\n",
"# P0020002 Hispanic or Latino\n",
"\n",
"plot_df2 = data_ks_sub[[\"NAME\",\"P0010003\",\"P0010004\",\"P0010005\",\"P0010006\",\"P0010007\",\"P0010008\",\"P0020002\"]]\n",
"plot_df2.rename(columns={\"P0010003\":\"White\",\"P0010004\":\"Black or African American\",\"P0010005\":\"American Indian and Alaska Native\",\"P0010006\":\"Asian\",\"P0010007\":\"Native Hawaiian and Other Pacific Islander\",\"P0010008\":\"Some Other Race\",\"P0020002\":\"Hispanic or Latino\"}, inplace=True)\n",
"plot_df2.head()"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "86f80e43-ad79-447b-8735-dd0f8718c9f9",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" NAME | \n",
" White | \n",
" Black or African American | \n",
" American Indian and Alaska Native | \n",
" Asian | \n",
" Native Hawaiian and Other Pacific Islander | \n",
" Some Other Race | \n",
" Hispanic or Latino | \n",
"
\n",
" \n",
" \n",
" \n",
" | 36 | \n",
" San Diego County | \n",
" 1633129 | \n",
" 155813 | \n",
" 40968 | \n",
" 410752 | \n",
" 15286 | \n",
" 520994 | \n",
" 1119629 | \n",
"
\n",
" \n",
"
\n",
"
\n\n
\n \n \n | \n NAME | \n White | \n Black or African American | \n American Indian and Alaska Native | \n Asian | \n Native Hawaiian and Other Pacific Islander | \n Some Other Race | \n Hispanic or Latino | \n
\n \n \n \n | 36 | \n San Diego County | \n 1633129 | \n 155813 | \n 40968 | \n 410752 | \n 15286 | \n 520994 | \n 1119629 | \n
\n \n
\n
Out[34]:
",
"type": "htmlSandbox"
}
},
"output_type": "display_data"
}
],
"source": [
"pd_temp2 = plot_df2.toPandas()\n",
"pd_temp_SD = pd_temp2[pd_temp2[\"NAME\"] == 'San Diego County']\n",
"pd_temp_SD"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "08320b38-fc8f-4a66-956b-5df8e33c24dc",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" NAME | \n",
" White | \n",
" Black or African American | \n",
" American Indian and Alaska Native | \n",
" Asian | \n",
" Native Hawaiian and Other Pacific Islander | \n",
" Some Other Race | \n",
" Hispanic or Latino | \n",
"
\n",
" \n",
" \n",
" \n",
" | 0 | \n",
" San Diego County | \n",
" 1633129 | \n",
" 155813 | \n",
" 40968 | \n",
" 410752 | \n",
" 15286 | \n",
" 520994 | \n",
" 1119629 | \n",
"
\n",
" \n",
"
\n",
"
\n\n
\n \n \n | \n NAME | \n White | \n Black or African American | \n American Indian and Alaska Native | \n Asian | \n Native Hawaiian and Other Pacific Islander | \n Some Other Race | \n Hispanic or Latino | \n
\n \n \n \n | 0 | \n San Diego County | \n 1633129 | \n 155813 | \n 40968 | \n 410752 | \n 15286 | \n 520994 | \n 1119629 | \n
\n \n
\n
Out[35]:
",
"type": "htmlSandbox"
}
},
"output_type": "display_data"
}
],
"source": [
"pd_temp_SD = pd_temp_SD.reset_index(drop=True)\n",
"pd_temp_SD"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "20b86a2f-198b-42a5-acf5-eeb953bd88e0",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" White | \n",
" Black or African American | \n",
" American Indian and Alaska Native | \n",
" Asian | \n",
" Native Hawaiian and Other Pacific Islander | \n",
" Some Other Race | \n",
" Hispanic or Latino | \n",
"
\n",
" \n",
" \n",
" \n",
" | 0 | \n",
" 1633129 | \n",
" 155813 | \n",
" 40968 | \n",
" 410752 | \n",
" 15286 | \n",
" 520994 | \n",
" 1119629 | \n",
"
\n",
" \n",
"
\n",
"
\n\n
\n \n \n | \n White | \n Black or African American | \n American Indian and Alaska Native | \n Asian | \n Native Hawaiian and Other Pacific Islander | \n Some Other Race | \n Hispanic or Latino | \n
\n \n \n \n | 0 | \n 1633129 | \n 155813 | \n 40968 | \n 410752 | \n 15286 | \n 520994 | \n 1119629 | \n
\n \n
\n
Out[36]:
",
"type": "htmlSandbox"
}
},
"output_type": "display_data"
}
],
"source": [
"pd_temp_SD = pd_temp_SD.drop([\"NAME\"], axis=1)\n",
"pd_temp_SD"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "3ef2b53a-b0c2-43c8-933d-878e4ac922ae",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" 0 | \n",
"
\n",
" \n",
" \n",
" \n",
" | White | \n",
" 1633129 | \n",
"
\n",
" \n",
" | Black or African American | \n",
" 155813 | \n",
"
\n",
" \n",
" | American Indian and Alaska Native | \n",
" 40968 | \n",
"
\n",
" \n",
" | Asian | \n",
" 410752 | \n",
"
\n",
" \n",
" | Native Hawaiian and Other Pacific Islander | \n",
" 15286 | \n",
"
\n",
" \n",
" | Some Other Race | \n",
" 520994 | \n",
"
\n",
" \n",
" | Hispanic or Latino | \n",
" 1119629 | \n",
"
\n",
" \n",
"
\n",
"
\n\n
\n \n \n | \n 0 | \n
\n \n \n \n | White | \n 1633129 | \n
\n \n | Black or African American | \n 155813 | \n
\n \n | American Indian and Alaska Native | \n 40968 | \n
\n \n | Asian | \n 410752 | \n
\n \n | Native Hawaiian and Other Pacific Islander | \n 15286 | \n
\n \n | Some Other Race | \n 520994 | \n
\n \n | Hispanic or Latino | \n 1119629 | \n
\n \n
\n
Out[37]:
",
"type": "htmlSandbox"
}
},
"output_type": "display_data"
}
],
"source": [
"pd_temp_SD_T = pd_temp_SD.T\n",
"#pd_temp_SD_T = pd_temp_SD_T.rename(columns={\"Population\"})\n",
"pd_temp_SD_T"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "1c1b1144-d482-4e76-9c37-b90b58aa788f",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"image/png": "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"
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "/plots/6a68f179-a480-458b-8f38-3e0d7a2193e4.png",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "image"
}
},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(35,10))\n",
"ax = pd_temp_SD_T.plot.bar()\n",
"plt.title(\"San Diego Population distribution by ethnicity\")"
]
},
{
"cell_type": "markdown",
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "e092c890-0391-412c-bd7b-af4da13a5d20",
"showTitle": false,
"title": ""
}
},
"source": [
"### Use Geopandas to show population bubbles on a Map"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "80c5723c-b6c3-418c-a1cd-c3129c8c77eb",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" NAME | \n",
" Total Population | \n",
" INTPTLAT | \n",
" INTPTLON | \n",
"
\n",
" \n",
" \n",
" \n",
" | 36816 | \n",
" Adelanto city | \n",
" 38046 | \n",
" 34.580902 | \n",
" -117.439458 | \n",
"
\n",
" \n",
" | 36818 | \n",
" Agoura Hills city | \n",
" 20299 | \n",
" 34.148942 | \n",
" -118.763930 | \n",
"
\n",
" \n",
" | 36823 | \n",
" Alameda city | \n",
" 78280 | \n",
" 37.741911 | \n",
" -122.259914 | \n",
"
\n",
" \n",
" | 36825 | \n",
" Albany city | \n",
" 20271 | \n",
" 37.890650 | \n",
" -122.318116 | \n",
"
\n",
" \n",
" | 36828 | \n",
" Alhambra city | \n",
" 82868 | \n",
" 34.083571 | \n",
" -118.136444 | \n",
"
\n",
" \n",
"
\n",
"
\n\n
\n \n \n | \n NAME | \n Total Population | \n INTPTLAT | \n INTPTLON | \n
\n \n \n \n | 36816 | \n Adelanto city | \n 38046 | \n 34.580902 | \n -117.439458 | \n
\n \n | 36818 | \n Agoura Hills city | \n 20299 | \n 34.148942 | \n -118.763930 | \n
\n \n | 36823 | \n Alameda city | \n 78280 | \n 37.741911 | \n -122.259914 | \n
\n \n | 36825 | \n Albany city | \n 20271 | \n 37.890650 | \n -122.318116 | \n
\n \n | 36828 | \n Alhambra city | \n 82868 | \n 34.083571 | \n -118.136444 | \n
\n \n
\n
Out[39]:
",
"type": "htmlSandbox"
}
},
"output_type": "display_data"
}
],
"source": [
"pd_temp_city.head()"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "eaa79a80-11d6-4a9a-be5d-75eb24236009",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"Out[40]: (675, 4)
"
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "Out[40]: (675, 4)
",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"pd_temp_city.shape"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "34d2b3eb-229b-4152-98d2-e3d53b977a60",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" Total Population | \n",
" INTPTLAT | \n",
" INTPTLON | \n",
"
\n",
" \n",
" \n",
" \n",
" | count | \n",
" 6.750000e+02 | \n",
" 675.000000 | \n",
" 675.000000 | \n",
"
\n",
" \n",
" | mean | \n",
" 6.075501e+04 | \n",
" 35.913016 | \n",
" -119.678155 | \n",
"
\n",
" \n",
" | std | \n",
" 1.791500e+05 | \n",
" 2.252842 | \n",
" 2.139734 | \n",
"
\n",
" \n",
" | min | \n",
" 0.000000e+00 | \n",
" 32.569140 | \n",
" -124.261239 | \n",
"
\n",
" \n",
" | 25% | \n",
" 7.344000e+03 | \n",
" 33.930746 | \n",
" -121.826875 | \n",
"
\n",
" \n",
" | 50% | \n",
" 2.703800e+04 | \n",
" 35.194361 | \n",
" -119.318750 | \n",
"
\n",
" \n",
" | 75% | \n",
" 6.898100e+04 | \n",
" 37.830509 | \n",
" -117.869322 | \n",
"
\n",
" \n",
" | max | \n",
" 3.898747e+06 | \n",
" 41.964965 | \n",
" -114.593545 | \n",
"
\n",
" \n",
"
\n",
"
\n\n
\n \n \n | \n Total Population | \n INTPTLAT | \n INTPTLON | \n
\n \n \n \n | count | \n 6.750000e+02 | \n 675.000000 | \n 675.000000 | \n
\n \n | mean | \n 6.075501e+04 | \n 35.913016 | \n -119.678155 | \n
\n \n | std | \n 1.791500e+05 | \n 2.252842 | \n 2.139734 | \n
\n \n | min | \n 0.000000e+00 | \n 32.569140 | \n -124.261239 | \n
\n \n | 25% | \n 7.344000e+03 | \n 33.930746 | \n -121.826875 | \n
\n \n | 50% | \n 2.703800e+04 | \n 35.194361 | \n -119.318750 | \n
\n \n | 75% | \n 6.898100e+04 | \n 37.830509 | \n -117.869322 | \n
\n \n | max | \n 3.898747e+06 | \n 41.964965 | \n -114.593545 | \n
\n \n
\n
Out[41]:
",
"type": "htmlSandbox"
}
},
"output_type": "display_data"
}
],
"source": [
"pd_temp_city_summary = pd_temp_city.describe()\n",
"pd_temp_city_summary"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "5202201e-a1b5-42eb-a0fe-58a11fecb971",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"Out[42]: (8, 3)
"
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "Out[42]: (8, 3)
",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"pd_temp_city_summary.shape"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "cf5b21cc-2b59-428d-b01b-b8b9d918846d",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"Out[43]: 3898747.0
"
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "Out[43]: 3898747.0
",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"max_pop_val = pd_temp_city_summary[\"Total Population\"][\"max\"]\n",
"max_pop_val"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "3def3cfe-3b3b-4b1e-adb3-e02b00e7661f",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" NAME | \n",
" Total Population | \n",
" INTPTLAT | \n",
" INTPTLON | \n",
" Circle_radius | \n",
"
\n",
" \n",
" \n",
" \n",
" | 36816 | \n",
" Adelanto city | \n",
" 38046 | \n",
" 34.580902 | \n",
" -117.439458 | \n",
" 0.009759 | \n",
"
\n",
" \n",
" | 36818 | \n",
" Agoura Hills city | \n",
" 20299 | \n",
" 34.148942 | \n",
" -118.763930 | \n",
" 0.005207 | \n",
"
\n",
" \n",
" | 36823 | \n",
" Alameda city | \n",
" 78280 | \n",
" 37.741911 | \n",
" -122.259914 | \n",
" 0.020078 | \n",
"
\n",
" \n",
" | 36825 | \n",
" Albany city | \n",
" 20271 | \n",
" 37.890650 | \n",
" -122.318116 | \n",
" 0.005199 | \n",
"
\n",
" \n",
" | 36828 | \n",
" Alhambra city | \n",
" 82868 | \n",
" 34.083571 | \n",
" -118.136444 | \n",
" 0.021255 | \n",
"
\n",
" \n",
"
\n",
"
\n\n
\n \n \n | \n NAME | \n Total Population | \n INTPTLAT | \n INTPTLON | \n Circle_radius | \n
\n \n \n \n | 36816 | \n Adelanto city | \n 38046 | \n 34.580902 | \n -117.439458 | \n 0.009759 | \n
\n \n | 36818 | \n Agoura Hills city | \n 20299 | \n 34.148942 | \n -118.763930 | \n 0.005207 | \n
\n \n | 36823 | \n Alameda city | \n 78280 | \n 37.741911 | \n -122.259914 | \n 0.020078 | \n
\n \n | 36825 | \n Albany city | \n 20271 | \n 37.890650 | \n -122.318116 | \n 0.005199 | \n
\n \n | 36828 | \n Alhambra city | \n 82868 | \n 34.083571 | \n -118.136444 | \n 0.021255 | \n
\n \n
\n
Out[44]:
",
"type": "htmlSandbox"
}
},
"output_type": "display_data"
}
],
"source": [
"pd_temp_city[\"Circle_radius\"] = pd_temp_city[\"Total Population\"].apply(lambda x: x / max_pop_val)\n",
"pd_temp_city.head()"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "5053d26b-9b17-4d7d-9ec5-b2562b663e74",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"Out[45]: (675, 5)
"
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "Out[45]: (675, 5)
",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"pd_temp_city = pd_temp_city.drop_duplicates(subset=[\"NAME\"])\n",
"pd_temp_city.shape"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "dc592876-d548-436c-8c79-d4fcec065ec1",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"Out[46]: count 6.750000e+02\n",
"mean 6.075501e+04\n",
"std 1.791500e+05\n",
"min 0.000000e+00\n",
"25% 7.344000e+03\n",
"50% 2.703800e+04\n",
"75% 6.898100e+04\n",
"max 3.898747e+06\n",
"Name: Total Population, dtype: float64
"
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "Out[46]: count 6.750000e+02\nmean 6.075501e+04\nstd 1.791500e+05\nmin 0.000000e+00\n25% 7.344000e+03\n50% 2.703800e+04\n75% 6.898100e+04\nmax 3.898747e+06\nName: Total Population, dtype: float64
",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"pd_temp_city[\"Total Population\"].describe()"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "c26a947b-f3e4-45fe-aee4-2e555a35e3a5",
"showTitle": false,
"title": ""
}
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "4e3231e6-f73f-4ca5-a05f-5f7b2ba71b68",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" NAME | \n",
" Total Population | \n",
" INTPTLAT | \n",
" INTPTLON | \n",
" Circle_radius | \n",
"
\n",
" \n",
" \n",
" \n",
" | 38103 | \n",
" Santa Barbara city | \n",
" 88665 | \n",
" 34.400601 | \n",
" -119.712954 | \n",
" 0.022742 | \n",
"
\n",
" \n",
"
\n",
"
\n\n
\n \n \n | \n NAME | \n Total Population | \n INTPTLAT | \n INTPTLON | \n Circle_radius | \n
\n \n \n \n | 38103 | \n Santa Barbara city | \n 88665 | \n 34.400601 | \n -119.712954 | \n 0.022742 | \n
\n \n
\n
Out[47]:
",
"type": "htmlSandbox"
}
},
"output_type": "display_data"
}
],
"source": [
"pd_temp_city[pd_temp_city[\"NAME\"] == 'Santa Barbara city']"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "12d77277-0076-4ff2-a834-ca1af806a094",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
""
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"#import folium as f\n",
"\n",
"# Make an empty map\n",
"#mp = f.Map(location=[37,-119], tiles=\"OpenStreetMap\", zoom_start=6)\n",
"#mp = f.Map(location=[37,-119], control_scale=True, zoom_start=6)\n",
"#mp"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "0560e968-fa91-4829-9ff7-dc63267ad0be",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"Make this Notebook Trusted to load map: File -> Trust Notebook
Make this Notebook Trusted to load map: File -> Trust Notebook
Out[82]:
",
"type": "htmlSandbox"
}
},
"output_type": "display_data"
}
],
"source": [
"import folium as f\n",
"\n",
"# Make an empty map\n",
"mp = f.Map(location=[37,-119], control_scale=True, zoom_start=7)\n",
"\n",
"#data_m=pd_temp_city.sample(n=500, random_state=1)\n",
"data_m=pd_temp_city\n",
"for i in range(0,data_m.shape[0]): \n",
" popup = \"\"\"\n",
" #City Name : %s
\n",
" #Population : %s
\n",
" \"\"\" % (data_m.iloc[i][\"NAME\"], \n",
" data_m.iloc[i][\"Total Population\"]) \n",
" f.Circle(\n",
" location=[data_m.iloc[i]['INTPTLAT'], data_m.iloc[i]['INTPTLON']],\n",
" tooltip=popup,\n",
" #popup=data_m.iloc[i]['NAME'],\n",
" radius=float(data_m.iloc[i]['Circle_radius'])*50000,\n",
" color='blue',\n",
" fill=True,\n",
" #fill_color='blue'\n",
" ).add_to(mp)\n",
"mp\n",
"\n",
"#import webbrowser\n",
"#map_osm = folium.Map(location=[45.5236, -122.6750])\n",
"#mp.save('map.html')\n",
"#webbrowser.open('map.html')\n",
"\n",
"#html_map = mp._repr_html_()\n",
"#displayHTML(html_map)\n",
"\n",
"from IPython.core.display import HTML\n",
"\n",
"HTML(mp._repr_html_())"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "b3472c54-787f-44d4-8e01-d328b5fb1c90",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
""
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"#mp.save(\"/FileStore/sukumar/Ca_census_map.html\")\n",
"\n",
"#dbutils.fs.put(\"/FileStore/sukumar/Ca_census_map.html\", mp)"
]
},
{
"cell_type": "markdown",
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "d05f7640-11b5-4498-8e4c-7abc2e9d5718",
"showTitle": false,
"title": ""
}
},
"source": [
"### Institutionalized and non institutionalized population"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "4e8ab78e-84c4-40b7-9e97-22e4f40c5024",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
""
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"#P0050002 Institutionalized population:\n",
"#P0050003 Correctional facilities for adults\n",
"#P0050004 Juvenile facilities\n",
"#P0050005 Nursing facilities/Skilled-nursing facilities\n",
"#P0050006 Other institutional facilities\n",
"#P0050007 Noninstitutionalized population:"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "ed596828-d535-477f-af86-f8837a4c05a3",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" NAME | \n",
" Institutionalized population | \n",
" Correctional facilities for adults | \n",
" Juvenile facilities | \n",
" Nursing facilities/Skilled-nursing facilities | \n",
" Other institutional facilities | \n",
" Noninstitutionalized population | \n",
"
\n",
" \n",
" \n",
" \n",
" | 36816 | \n",
" Adelanto city | \n",
" 2674 | \n",
" 2674 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
" 77 | \n",
"
\n",
" \n",
" | 36818 | \n",
" Agoura Hills city | \n",
" 148 | \n",
" 0 | \n",
" 0 | \n",
" 148 | \n",
" 0 | \n",
" 0 | \n",
"
\n",
" \n",
" | 36823 | \n",
" Alameda city | \n",
" 916 | \n",
" 0 | \n",
" 0 | \n",
" 916 | \n",
" 0 | \n",
" 614 | \n",
"
\n",
" \n",
" | 36825 | \n",
" Albany city | \n",
" 10 | \n",
" 0 | \n",
" 0 | \n",
" 10 | \n",
" 0 | \n",
" 1385 | \n",
"
\n",
" \n",
" | 36828 | \n",
" Alhambra city | \n",
" 691 | \n",
" 21 | \n",
" 37 | \n",
" 547 | \n",
" 86 | \n",
" 212 | \n",
"
\n",
" \n",
"
\n",
"
\n\n
\n \n \n | \n NAME | \n Institutionalized population | \n Correctional facilities for adults | \n Juvenile facilities | \n Nursing facilities/Skilled-nursing facilities | \n Other institutional facilities | \n Noninstitutionalized population | \n
\n \n \n \n | 36816 | \n Adelanto city | \n 2674 | \n 2674 | \n 0 | \n 0 | \n 0 | \n 77 | \n
\n \n | 36818 | \n Agoura Hills city | \n 148 | \n 0 | \n 0 | \n 148 | \n 0 | \n 0 | \n
\n \n | 36823 | \n Alameda city | \n 916 | \n 0 | \n 0 | \n 916 | \n 0 | \n 614 | \n
\n \n | 36825 | \n Albany city | \n 10 | \n 0 | \n 0 | \n 10 | \n 0 | \n 1385 | \n
\n \n | 36828 | \n Alhambra city | \n 691 | \n 21 | \n 37 | \n 547 | \n 86 | \n 212 | \n
\n \n
\n
Out[51]:
",
"type": "htmlSandbox"
}
},
"output_type": "display_data"
}
],
"source": [
"df_k_means = data_ks_sub[[\"NAME\",\"P0050002\",\"P0050003\",\"P0050004\",\"P0050005\",\"P0050006\",\"P0050007\"]].toPandas()\n",
"df_k_means.rename(columns={\"P0050002\":\"Institutionalized population\",\"P0050003\":\"Correctional facilities for adults\",\"P0050004\":\"Juvenile facilities\",\"P0050005\":\"Nursing facilities/Skilled-nursing facilities\",\"P0050006\":\"Other institutional facilities\",\"P0050007\":\"Noninstitutionalized population\"}, inplace=True)\n",
"df_k_means = df_k_means[df_k_means[\"NAME\"].str.contains('city', regex=False)].drop_duplicates(subset=[\"NAME\"])\n",
"df_k_means.head()"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "6747f353-b34b-4bab-9623-36ea07e153be",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"Out[52]: (675, 7)
"
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "Out[52]: (675, 7)
",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"df_k_means.shape"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "7bbfbbc5-2277-4709-a35d-6cef198f6273",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"Out[53]: NAME object\n",
"Institutionalized population int32\n",
"Correctional facilities for adults int32\n",
"Juvenile facilities int32\n",
"Nursing facilities/Skilled-nursing facilities int32\n",
"Other institutional facilities int32\n",
"Noninstitutionalized population int32\n",
"dtype: object
"
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "Out[53]: NAME object\nInstitutionalized population int32\nCorrectional facilities for adults int32\nJuvenile facilities int32\nNursing facilities/Skilled-nursing facilities int32\nOther institutional facilities int32\nNoninstitutionalized population int32\ndtype: object
",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"df_k_means.dtypes"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "b5066ced-15f9-4621-9122-1ad052466a1f",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"Out[54]: count 675.000000\n",
"mean 206.779259\n",
"std 657.850524\n",
"min 0.000000\n",
"25% 0.000000\n",
"50% 60.000000\n",
"75% 229.000000\n",
"max 14609.000000\n",
"Name: Nursing facilities/Skilled-nursing facilities, dtype: float64
"
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "Out[54]: count 675.000000\nmean 206.779259\nstd 657.850524\nmin 0.000000\n25% 0.000000\n50% 60.000000\n75% 229.000000\nmax 14609.000000\nName: Nursing facilities/Skilled-nursing facilities, dtype: float64
",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"df_k_means[\"Nursing facilities/Skilled-nursing facilities\"].describe()"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "fa4b0661-f88f-4cfb-9693-14d8bfcaee42",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
""
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"df_k_means_sub = df_k_means[(df_k_means[\"Nursing facilities/Skilled-nursing facilities\"] < 1000) & (df_k_means[\"Nursing facilities/Skilled-nursing facilities\"] > 0)]"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "31f3558b-9c66-4071-925a-66dcf450e311",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"image/png": "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"
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "/plots/3a1face7-366d-4cdc-9cb4-dde2708fd0e0.png",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "image"
}
},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(25,10))\n",
"\n",
"splot = sns.histplot(data = df_k_means_sub, x=\"Nursing facilities/Skilled-nursing facilities\",palette=\"viridis\")\n",
"splot.axes.set_title(\"Histogram of population in Nursing facilities/Skilled-nursing facilities excluding outliers\",fontsize=40)\n",
"splot.set_xlabel(\"Nursing facilities/Skilled-nursing facilities\",fontsize=20)\n",
"splot.tick_params(labelsize=13)"
]
},
{
"cell_type": "markdown",
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "4aad37c9-b248-499f-9900-9b5b10598785",
"showTitle": false,
"title": ""
}
},
"source": [
"### K Means clustering of institutionalized and non institutionalized population"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "f20133d8-75d4-4d08-b9e9-8f9a7136b2e0",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"Out[57]: (400, 2)
"
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "Out[57]: (400, 2)
",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"X_df = df_k_means_sub[[\"Institutionalized population\",\"Noninstitutionalized population\"]]\n",
"X_df = X_df.dropna()\n",
"X_df.shape"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "b2d2b997-f58d-4bb5-b3e9-9e5e44b6e561",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
""
]
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "html"
}
},
"output_type": "display_data"
}
],
"source": [
"X = X_df.values"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "edae713f-0731-44c8-9119-ae733d674420",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"image/png": "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"
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "/plots/2a4f51bf-e676-462d-879f-8ced966328b1.png",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "image"
}
},
"output_type": "display_data"
}
],
"source": [
"from sklearn.cluster import KMeans\n",
"\n",
"Error = []\n",
"for i in range(1, 12):\n",
" kmeans = KMeans(n_clusters = i)\n",
" kmeans.fit(X)\n",
" Error.append(kmeans.inertia_)\n",
" \n",
"plt.plot(range(1,12), Error)\n",
"plt.title(\"Elbow method\")\n",
"plt.xlabel(\"Number of clusters\")\n",
"plt.ylabel(\"Error\")"
]
},
{
"cell_type": "markdown",
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "314cc9a4-3d3c-42da-9e63-a45f9a740b10",
"showTitle": false,
"title": ""
}
},
"source": [
"Based on Elbow method, choosing n_clusters = 4"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "ec7175b7-7db6-422c-afdb-ef7fd3919ecb",
"showTitle": false,
"title": ""
}
},
"outputs": [
{
"data": {
"image/png": "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"
},
"metadata": {
"application/vnd.databricks.v1+output": {
"addedWidgets": {},
"arguments": {},
"data": "/plots/e5b17c57-412a-457f-a812-f12edd91b625.png",
"datasetInfos": [],
"metadata": {},
"removedWidgets": [],
"type": "image"
}
},
"output_type": "display_data"
}
],
"source": [
"from sklearn.cluster import KMeans\n",
"\n",
"Kmean = KMeans(n_clusters=4)\n",
"y = Kmean.fit_predict(X)\n",
"\n",
"plt.figsize=(25,10)\n",
"frame = plt.scatter(X[:,0], X[:,1], c=y, s=50, cmap='viridis')\n",
"frame.axes.get_xaxis().set_visible(False)\n"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "4b97242e-00b2-4eb8-a3c3-759a2ac5dc9e",
"showTitle": false,
"title": ""
}
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "77bd7478-40da-4d6c-92f6-64162fc85d37",
"showTitle": false,
"title": ""
}
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "6919a029-baf2-4304-8678-d4436aacbd1a",
"showTitle": false,
"title": ""
}
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "ca8b5b50-2a25-4aa7-a2b5-ce9e5fc7fc2f",
"showTitle": false,
"title": ""
}
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "ddfba09f-fabe-41bf-b3d5-8e78d8ace480",
"showTitle": false,
"title": ""
}
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "5aa14bb6-5f0e-44e7-9855-1b44c7f76f0b",
"showTitle": false,
"title": ""
}
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"application/vnd.databricks.v1+cell": {
"inputWidgets": {},
"nuid": "076aba06-909f-4c99-ac38-621d75cd1f44",
"showTitle": false,
"title": ""
}
},
"outputs": [],
"source": []
}
],
"metadata": {
"application/vnd.databricks.v1+notebook": {
"dashboards": [],
"language": "python",
"notebookMetadata": {
"pythonIndentUnit": 2
},
"notebookName": "California_2020_census",
"notebookOrigID": 7029261,
"widgets": {}
},
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.7"
}
},
"nbformat": 4,
"nbformat_minor": 1
}