jupyter_notebooks/COVID_LEX.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/james/anaconda3/lib/python3.7/site-packages/matplotlib/__init__.py:886: MatplotlibDeprecationWarning: \n",
      "examples.directory is deprecated; in the future, examples will be found relative to the 'datapath' directory.\n",
      "  \"found relative to the 'datapath' directory.\".format(key))\n"
     ]
    }
   ],
   "source": [
    "import gc, argparse, sys, os, errno\n",
    "%pylab inline\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "#sns.set()\n",
    "#sns.set_style('whitegrid')\n",
    "import h5py\n",
    "from PIL import Image\n",
    "import os\n",
    "from tqdm import tqdm_notebook as tqdm\n",
    "import scipy\n",
    "import sklearn\n",
    "from scipy.stats import pearsonr\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "url = 'https://github.com/COVIDExposureIndices/COVIDExposureIndices/blob/master/lex_data/county_lex_2020-01-20.csv.gz?raw=true'\n",
    "df = pd.read_csv(url, compression='gzip', header=0)\n",
    "countys = df.columns.values[1:]\n",
    "col_names = dict(zip(countys, [\"a\" + lab for lab in countys]  ))\n",
    "df \t= df.rename(columns = col_names)\n",
    "df_long\t= pd.wide_to_long(df, stubnames=\"a\", i=['COUNTY_PRE'], j='col')\n",
    "df_long = df_long.reset_index(drop=False)\n",
    "df_long = df_long.rename(columns = {\"col\" : \"COUNTY\", \"a\" : \"LEX\"})\n",
    "df_long.to_csv(r'reshaped.csv',index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>COUNTY_PRE</th>\n",
       "      <th>COUNTY</th>\n",
       "      <th>LEX</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1001</td>\n",
       "      <td>1001</td>\n",
       "      <td>0.904768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1003</td>\n",
       "      <td>1001</td>\n",
       "      <td>0.017834</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1005</td>\n",
       "      <td>1001</td>\n",
       "      <td>0.006539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1007</td>\n",
       "      <td>1001</td>\n",
       "      <td>0.019260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1009</td>\n",
       "      <td>1001</td>\n",
       "      <td>0.006182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4072319</th>\n",
       "      <td>56029</td>\n",
       "      <td>56041</td>\n",
       "      <td>0.002431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4072320</th>\n",
       "      <td>56033</td>\n",
       "      <td>56041</td>\n",
       "      <td>0.004861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4072321</th>\n",
       "      <td>56037</td>\n",
       "      <td>56041</td>\n",
       "      <td>0.235780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4072322</th>\n",
       "      <td>56039</td>\n",
       "      <td>56041</td>\n",
       "      <td>0.010209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4072323</th>\n",
       "      <td>56041</td>\n",
       "      <td>56041</td>\n",
       "      <td>0.765678</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4072324 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         COUNTY_PRE  COUNTY       LEX\n",
       "0              1001    1001  0.904768\n",
       "1              1003    1001  0.017834\n",
       "2              1005    1001  0.006539\n",
       "3              1007    1001  0.019260\n",
       "4              1009    1001  0.006182\n",
       "...             ...     ...       ...\n",
       "4072319       56029   56041  0.002431\n",
       "4072320       56033   56041  0.004861\n",
       "4072321       56037   56041  0.235780\n",
       "4072322       56039   56041  0.010209\n",
       "4072323       56041   56041  0.765678\n",
       "\n",
       "[4072324 rows x 3 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_long"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.6"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}