rds-to-csv.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Read an rds (R) data file into pandas and filter to reduce size of dataset \n",
    "Export to csv "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import dependencies\n",
    "# import pyreadr\n",
    "import rdata\n",
    "import pandas as pd\n",
    "import datetime\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/envs/dev/lib/python3.10/site-packages/rdata/parser/_parser.py:1217: UserWarning: Unknown file type: assumed RDS\n",
      "  warnings.warn(\"Unknown file type: assumed RDS\")  # noqa: B028\n",
      "/opt/anaconda3/envs/dev/lib/python3.10/site-packages/rdata/parser/_parser.py:1220: UserWarning: Wrong extension .rda for file in RDS format\n",
      "  warnings.warn(f\"Wrong extension {extension} for file in RDS format\")  # noqa: B028\n"
     ]
    },
    {
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       "      <th></th>\n",
       "      <th>StCoFIPS</th>\n",
       "      <th>Date</th>\n",
       "      <th>Tmin_C</th>\n",
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       "      <th>UTCImin_C</th>\n",
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       "      <td>16.52</td>\n",
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       "      <td>8.10</td>\n",
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       "      <td>18.80</td>\n",
       "      <td>15.82</td>\n",
       "      <td>18.43</td>\n",
       "      <td>17.18</td>\n",
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       "      <td>20.09</td>\n",
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       "      <td>16.28</td>\n",
       "      <td>14.97</td>\n",
       "      <td>7.29</td>\n",
       "      <td>14.83</td>\n",
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       "      <td>11.59</td>\n",
       "      <td>23.10</td>\n",
       "      <td>15.76</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
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       "      <td>13.57</td>\n",
       "      <td>21.02</td>\n",
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       "      <th>5</th>\n",
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      ],
      "text/plain": [
       "         StCoFIPS     Date  Tmin_C  Tmax_C  Tmean_C  TDmin_C  TDmax_C  \\\n",
       "1           01001  10958.0   14.62   21.63    17.28    14.45    16.52   \n",
       "2           01003  10958.0   16.26   22.61    18.80    15.82    18.43   \n",
       "3           01005  10958.0   13.88   20.09    16.23    13.80    16.28   \n",
       "4           01007  10958.0   13.57   21.02    16.62    13.46    16.68   \n",
       "5           01009  10958.0   13.49   18.49    15.29    13.35    15.80   \n",
       "...           ...      ...     ...     ...      ...      ...      ...   \n",
       "23835248    56037  18626.0  -18.96   -6.53   -12.46   -22.55   -11.14   \n",
       "23835249    56039  18626.0  -20.90  -11.78   -15.73   -23.23   -14.33   \n",
       "23835250    56041  18626.0  -17.40   -4.62   -11.12   -21.91   -10.23   \n",
       "23835251    56043  18626.0  -14.40   -1.32    -8.46   -18.79   -11.98   \n",
       "23835252    56045  18626.0  -10.17    1.02    -5.55   -16.53   -10.28   \n",
       "\n",
       "          TDmean_C  NETmin_C  NETmax_C  ...  UTCImin_C  UTCImax_C  UTCImean_C  \\\n",
       "1            15.38      8.10     15.61  ...      11.98      24.88       16.57   \n",
       "2            17.18     10.10     15.88  ...      13.32      25.46       17.92   \n",
       "3            14.97      7.29     14.83  ...      11.59      23.10       15.76   \n",
       "4            15.04      6.52     15.05  ...       9.71      24.62       15.55   \n",
       "5            14.52      5.84     12.15  ...       9.77      21.11       13.55   \n",
       "...            ...       ...       ...  ...        ...        ...         ...   \n",
       "23835248    -16.63    -34.66    -19.94  ...     -34.78      -5.29      -22.96   \n",
       "23835249    -18.45    -28.82    -17.07  ...     -26.26      -3.41      -16.93   \n",
       "23835250    -15.98    -31.11    -15.47  ...     -31.59      -0.86      -18.83   \n",
       "23835251    -15.82    -23.91     -4.22  ...     -23.88      12.10      -10.11   \n",
       "23835252    -13.64    -23.05     -6.86  ...     -25.03       3.48      -14.24   \n",
       "\n",
       "          Flag_T  Flag_TD  Flag_NET  Flag_HI  Flag_HX  Flag_WBGT  Flag_UTCI  \n",
       "1            0.0      0.0       0.0      0.0      0.0        0.0        0.0  \n",
       "2            0.0      0.0       0.0      0.0      0.0        0.0        0.0  \n",
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       "\n",
       "[23835252 rows x 30 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Read in file\n",
    "#data format is .rds \n",
    "\n",
    "# data= pyreadr.list_objects('/Users/geoffmaitland/Documents/aibootcamp/Git- Local-Repositories/Project-2/resources/UNWEIGHTED_Heatvars.Rds')\n",
    "\n",
    "\n",
    "df_all_0 = rdata.read_rda(rdata.TESTDATA_PATH / \"/Users/geoffmaitland/Documents/aibootcamp/Git- Local-Repositories/Project-2/daily-temps-2000-2020/archive csv/resources/UNWEIGHTED_Heatvars.Rds\")\n",
    "df_all_0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 23835252 entries, 1 to 23835252\n",
      "Data columns (total 30 columns):\n",
      " #   Column      Dtype   \n",
      "---  ------      -----   \n",
      " 0   StCoFIPS    category\n",
      " 1   Date        float64 \n",
      " 2   Tmin_C      float64 \n",
      " 3   Tmax_C      float64 \n",
      " 4   Tmean_C     float64 \n",
      " 5   TDmin_C     float64 \n",
      " 6   TDmax_C     float64 \n",
      " 7   TDmean_C    float64 \n",
      " 8   NETmin_C    float64 \n",
      " 9   NETmax_C    float64 \n",
      " 10  NETmean_C   float64 \n",
      " 11  HImin_C     float64 \n",
      " 12  HImax_C     float64 \n",
      " 13  HImean_C    float64 \n",
      " 14  HXmin_C     float64 \n",
      " 15  HXmax_C     float64 \n",
      " 16  HXmean_C    float64 \n",
      " 17  WBGTmin_C   float64 \n",
      " 18  WBGTmax_C   float64 \n",
      " 19  WBGTmean_C  float64 \n",
      " 20  UTCImin_C   float64 \n",
      " 21  UTCImax_C   float64 \n",
      " 22  UTCImean_C  float64 \n",
      " 23  Flag_T      float64 \n",
      " 24  Flag_TD     float64 \n",
      " 25  Flag_NET    float64 \n",
      " 26  Flag_HI     float64 \n",
      " 27  Flag_HX     float64 \n",
      " 28  Flag_WBGT   float64 \n",
      " 29  Flag_UTCI   float64 \n",
      "dtypes: category(1), float64(29)\n",
      "memory usage: 5.2 GB\n"
     ]
    }
   ],
   "source": [
    "#check data types\n",
    "\n",
    "df_all_0.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/envs/dev/lib/python3.10/site-packages/pandas/core/dtypes/astype.py:133: RuntimeWarning: invalid value encountered in cast\n",
      "  return arr.astype(dtype, copy=True)\n",
      "/opt/anaconda3/envs/dev/lib/python3.10/site-packages/pandas/core/dtypes/astype.py:133: RuntimeWarning: invalid value encountered in cast\n",
      "  return arr.astype(dtype, copy=True)\n",
      "/opt/anaconda3/envs/dev/lib/python3.10/site-packages/pandas/core/dtypes/astype.py:133: RuntimeWarning: invalid value encountered in cast\n",
      "  return arr.astype(dtype, copy=True)\n",
      "/opt/anaconda3/envs/dev/lib/python3.10/site-packages/pandas/core/dtypes/astype.py:133: RuntimeWarning: invalid value encountered in cast\n",
      "  return arr.astype(dtype, copy=True)\n",
      "/opt/anaconda3/envs/dev/lib/python3.10/site-packages/pandas/core/dtypes/astype.py:133: RuntimeWarning: invalid value encountered in cast\n",
      "  return arr.astype(dtype, copy=True)\n",
      "/opt/anaconda3/envs/dev/lib/python3.10/site-packages/pandas/core/dtypes/astype.py:133: RuntimeWarning: invalid value encountered in cast\n",
      "  return arr.astype(dtype, copy=True)\n",
      "/opt/anaconda3/envs/dev/lib/python3.10/site-packages/pandas/core/dtypes/astype.py:133: RuntimeWarning: invalid value encountered in cast\n",
      "  return arr.astype(dtype, copy=True)\n",
      "/opt/anaconda3/envs/dev/lib/python3.10/site-packages/pandas/core/dtypes/astype.py:133: RuntimeWarning: invalid value encountered in cast\n",
      "  return arr.astype(dtype, copy=True)\n",
      "/opt/anaconda3/envs/dev/lib/python3.10/site-packages/pandas/core/dtypes/astype.py:133: RuntimeWarning: invalid value encountered in cast\n",
      "  return arr.astype(dtype, copy=True)\n",
      "/opt/anaconda3/envs/dev/lib/python3.10/site-packages/pandas/core/dtypes/astype.py:133: RuntimeWarning: invalid value encountered in cast\n",
      "  return arr.astype(dtype, copy=True)\n",
      "/opt/anaconda3/envs/dev/lib/python3.10/site-packages/pandas/core/dtypes/astype.py:133: RuntimeWarning: invalid value encountered in cast\n",
      "  return arr.astype(dtype, copy=True)\n",
      "/opt/anaconda3/envs/dev/lib/python3.10/site-packages/pandas/core/dtypes/astype.py:133: RuntimeWarning: invalid value encountered in cast\n",
      "  return arr.astype(dtype, copy=True)\n",
      "/opt/anaconda3/envs/dev/lib/python3.10/site-packages/pandas/core/dtypes/astype.py:133: RuntimeWarning: invalid value encountered in cast\n",
      "  return arr.astype(dtype, copy=True)\n",
      "/opt/anaconda3/envs/dev/lib/python3.10/site-packages/pandas/core/dtypes/astype.py:133: RuntimeWarning: invalid value encountered in cast\n",
      "  return arr.astype(dtype, copy=True)\n",
      "/opt/anaconda3/envs/dev/lib/python3.10/site-packages/pandas/core/dtypes/astype.py:133: RuntimeWarning: invalid value encountered in cast\n",
      "  return arr.astype(dtype, copy=True)\n",
      "/opt/anaconda3/envs/dev/lib/python3.10/site-packages/pandas/core/dtypes/astype.py:133: RuntimeWarning: invalid value encountered in cast\n",
      "  return arr.astype(dtype, copy=True)\n",
      "/opt/anaconda3/envs/dev/lib/python3.10/site-packages/pandas/core/dtypes/astype.py:133: RuntimeWarning: invalid value encountered in cast\n",
      "  return arr.astype(dtype, copy=True)\n",
      "/opt/anaconda3/envs/dev/lib/python3.10/site-packages/pandas/core/dtypes/astype.py:133: RuntimeWarning: invalid value encountered in cast\n",
      "  return arr.astype(dtype, copy=True)\n",
      "/opt/anaconda3/envs/dev/lib/python3.10/site-packages/pandas/core/dtypes/astype.py:133: RuntimeWarning: invalid value encountered in cast\n",
      "  return arr.astype(dtype, copy=True)\n",
      "/opt/anaconda3/envs/dev/lib/python3.10/site-packages/pandas/core/dtypes/astype.py:133: RuntimeWarning: invalid value encountered in cast\n",
      "  return arr.astype(dtype, copy=True)\n",
      "/opt/anaconda3/envs/dev/lib/python3.10/site-packages/pandas/core/dtypes/astype.py:133: RuntimeWarning: invalid value encountered in cast\n",
      "  return arr.astype(dtype, copy=True)\n"
     ]
    }
   ],
   "source": [
    "# convert data to int32\n",
    "df_all_0 = df_all_0.astype({col: 'float32' for col in df_all_0.select_dtypes(include=['float64']).columns})\n",
    "\n",
    "# To save the DataFrame, for example as a CSV:\n",
    "# df.to_csv('filename.csv', index=False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 23835252 entries, 1 to 23835252\n",
      "Data columns (total 30 columns):\n",
      " #   Column      Dtype   \n",
      "---  ------      -----   \n",
      " 0   StCoFIPS    category\n",
      " 1   Date        float32 \n",
      " 2   Tmin_C      float32 \n",
      " 3   Tmax_C      float32 \n",
      " 4   Tmean_C     float32 \n",
      " 5   TDmin_C     float32 \n",
      " 6   TDmax_C     float32 \n",
      " 7   TDmean_C    float32 \n",
      " 8   NETmin_C    float32 \n",
      " 9   NETmax_C    float32 \n",
      " 10  NETmean_C   float32 \n",
      " 11  HImin_C     float32 \n",
      " 12  HImax_C     float32 \n",
      " 13  HImean_C    float32 \n",
      " 14  HXmin_C     float32 \n",
      " 15  HXmax_C     float32 \n",
      " 16  HXmean_C    float32 \n",
      " 17  WBGTmin_C   float32 \n",
      " 18  WBGTmax_C   float32 \n",
      " 19  WBGTmean_C  float32 \n",
      " 20  UTCImin_C   float32 \n",
      " 21  UTCImax_C   float32 \n",
      " 22  UTCImean_C  float32 \n",
      " 23  Flag_T      float32 \n",
      " 24  Flag_TD     float32 \n",
      " 25  Flag_NET    float32 \n",
      " 26  Flag_HI     float32 \n",
      " 27  Flag_HX     float32 \n",
      " 28  Flag_WBGT   float32 \n",
      " 29  Flag_UTCI   float32 \n",
      "dtypes: category(1), float32(29)\n",
      "memory usage: 2.6 GB\n"
     ]
    }
   ],
   "source": [
    "df_all_0.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since we want to use StCoFIPS column to sort, need to convert it from categorical data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# Convert the dtype from categorical to integer to be able to sort\n",
    "df_all_0['StCoFIPS'] = df_all_0['StCoFIPS'].astype('int32')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 23835252 entries, 1 to 23835252\n",
      "Data columns (total 30 columns):\n",
      " #   Column      Dtype  \n",
      "---  ------      -----  \n",
      " 0   StCoFIPS    int32  \n",
      " 1   Date        float32\n",
      " 2   Tmin_C      float32\n",
      " 3   Tmax_C      float32\n",
      " 4   Tmean_C     float32\n",
      " 5   TDmin_C     float32\n",
      " 6   TDmax_C     float32\n",
      " 7   TDmean_C    float32\n",
      " 8   NETmin_C    float32\n",
      " 9   NETmax_C    float32\n",
      " 10  NETmean_C   float32\n",
      " 11  HImin_C     float32\n",
      " 12  HImax_C     float32\n",
      " 13  HImean_C    float32\n",
      " 14  HXmin_C     float32\n",
      " 15  HXmax_C     float32\n",
      " 16  HXmean_C    float32\n",
      " 17  WBGTmin_C   float32\n",
      " 18  WBGTmax_C   float32\n",
      " 19  WBGTmean_C  float32\n",
      " 20  UTCImin_C   float32\n",
      " 21  UTCImax_C   float32\n",
      " 22  UTCImean_C  float32\n",
      " 23  Flag_T      float32\n",
      " 24  Flag_TD     float32\n",
      " 25  Flag_NET    float32\n",
      " 26  Flag_HI     float32\n",
      " 27  Flag_HX     float32\n",
      " 28  Flag_WBGT   float32\n",
      " 29  Flag_UTCI   float32\n",
      "dtypes: float32(29), int32(1)\n",
      "memory usage: 2.7 GB\n"
     ]
    }
   ],
   "source": [
    "df_all_0.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Sample code to filter dataset by use case"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>StCoFIPS</th>\n",
       "      <th>Date</th>\n",
       "      <th>Tmin_C</th>\n",
       "      <th>Tmax_C</th>\n",
       "      <th>Tmean_C</th>\n",
       "      <th>TDmin_C</th>\n",
       "      <th>TDmax_C</th>\n",
       "      <th>TDmean_C</th>\n",
       "      <th>NETmin_C</th>\n",
       "      <th>NETmax_C</th>\n",
       "      <th>...</th>\n",
       "      <th>UTCImin_C</th>\n",
       "      <th>UTCImax_C</th>\n",
       "      <th>UTCImean_C</th>\n",
       "      <th>Flag_T</th>\n",
       "      <th>Flag_TD</th>\n",
       "      <th>Flag_NET</th>\n",
       "      <th>Flag_HI</th>\n",
       "      <th>Flag_HX</th>\n",
       "      <th>Flag_WBGT</th>\n",
       "      <th>Flag_UTCI</th>\n",
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       "      <td>10958.0</td>\n",
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       "    <tr>\n",
       "      <th>2492</th>\n",
       "      <td>48005</td>\n",
       "      <td>10958.0</td>\n",
       "      <td>17.860001</td>\n",
       "      <td>23.350000</td>\n",
       "      <td>19.870001</td>\n",
       "      <td>16.650000</td>\n",
       "      <td>18.750000</td>\n",
       "      <td>17.700001</td>\n",
       "      <td>10.24</td>\n",
       "      <td>17.209999</td>\n",
       "      <td>...</td>\n",
       "      <td>12.56</td>\n",
       "      <td>25.110001</td>\n",
       "      <td>17.629999</td>\n",
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       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>2493</th>\n",
       "      <td>48007</td>\n",
       "      <td>10958.0</td>\n",
       "      <td>20.200001</td>\n",
       "      <td>24.070000</td>\n",
       "      <td>21.410000</td>\n",
       "      <td>18.219999</td>\n",
       "      <td>18.990000</td>\n",
       "      <td>18.629999</td>\n",
       "      <td>11.46</td>\n",
       "      <td>16.230000</td>\n",
       "      <td>...</td>\n",
       "      <td>10.18</td>\n",
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       "    <tr>\n",
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       "      <td>10958.0</td>\n",
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       "    <tr>\n",
       "      <th>23834884</th>\n",
       "      <td>48501</td>\n",
       "      <td>18626.0</td>\n",
       "      <td>0.150000</td>\n",
       "      <td>8.590000</td>\n",
       "      <td>3.610000</td>\n",
       "      <td>-13.660000</td>\n",
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       "      <td>-7.510000</td>\n",
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       "      <td>-0.520000</td>\n",
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       "    <tr>\n",
       "      <th>23834885</th>\n",
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       "      <td>18626.0</td>\n",
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       "    <tr>\n",
       "      <th>23834886</th>\n",
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       "      <td>18626.0</td>\n",
       "      <td>17.290001</td>\n",
       "      <td>27.870001</td>\n",
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       "      <td>14.020000</td>\n",
       "      <td>8.13</td>\n",
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       "      <td>...</td>\n",
       "      <td>6.77</td>\n",
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       "    <tr>\n",
       "      <th>23834887</th>\n",
       "      <td>48507</td>\n",
       "      <td>18626.0</td>\n",
       "      <td>9.880000</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1947926 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          StCoFIPS     Date     Tmin_C     Tmax_C    Tmean_C    TDmin_C  \\\n",
       "2490         48001  10958.0  17.969999  22.020000  19.469999  16.639999   \n",
       "2491         48003  10958.0   3.730000  17.750000  11.380000  -7.530000   \n",
       "2492         48005  10958.0  17.860001  23.350000  19.870001  16.650000   \n",
       "2493         48007  10958.0  20.200001  24.070000  21.410000  18.219999   \n",
       "2494         48009  10958.0  10.840000  20.840000  15.860000  -4.590000   \n",
       "...            ...      ...        ...        ...        ...        ...   \n",
       "23834883     48499  18626.0   5.990000  16.790001  12.100000   5.670000   \n",
       "23834884     48501  18626.0   0.150000   8.590000   3.610000 -13.660000   \n",
       "23834885     48503  18626.0   4.150000  17.070000   7.140000  -5.090000   \n",
       "23834886     48505  18626.0  17.290001  27.870001  22.090000  11.340000   \n",
       "23834887     48507  18626.0   9.880000  23.240000  17.330000   4.830000   \n",
       "\n",
       "            TDmax_C   TDmean_C  NETmin_C   NETmax_C  ...  UTCImin_C  \\\n",
       "2490      18.709999  17.549999      9.58  15.810000  ...      10.64   \n",
       "2491       0.110000  -5.020000     -4.42   8.370000  ...     -15.64   \n",
       "2492      18.750000  17.700001     10.24  17.209999  ...      12.56   \n",
       "2493      18.990000  18.629999     11.46  16.230000  ...      10.18   \n",
       "2494      10.990000   3.660000      3.67  13.370000  ...       4.01   \n",
       "...             ...        ...       ...        ...  ...        ...   \n",
       "23834883  16.740000  11.390000     -5.94  12.220000  ...      -2.94   \n",
       "23834884   1.370000  -7.510000    -14.77   0.190000  ...     -19.98   \n",
       "23834885  14.960000   3.750000    -10.44   9.020000  ...     -11.22   \n",
       "23834886  16.190001  14.020000      8.13  21.730000  ...       6.77   \n",
       "23834887  15.710000  12.140000     -1.51  17.309999  ...      -1.89   \n",
       "\n",
       "          UTCImax_C  UTCImean_C  Flag_T  Flag_TD  Flag_NET  Flag_HI  Flag_HX  \\\n",
       "2490      25.030001   16.680000     0.0      0.0       0.0      0.0      0.0   \n",
       "2491      17.870001    2.060000     0.0      0.0       0.0      0.0      0.0   \n",
       "2492      25.110001   17.629999     0.0      0.0       0.0      0.0      0.0   \n",
       "2493      24.280001   15.300000     0.0      0.0       0.0      0.0      0.0   \n",
       "2494      25.650000   12.210000     0.0      0.0       0.0      0.0      0.0   \n",
       "...             ...         ...     ...      ...       ...      ...      ...   \n",
       "23834883  19.270000    6.780000     0.0      0.0       0.0      0.0      0.0   \n",
       "23834884  -0.520000  -10.680000     0.0      0.0       0.0      0.0      0.0   \n",
       "23834885  13.390000   -5.270000     0.0      0.0       0.0      0.0      0.0   \n",
       "23834886  33.860001   17.850000     0.0      0.0       0.0      0.0      0.0   \n",
       "23834887  25.379999   11.410000     0.0      0.0       0.0      0.0      0.0   \n",
       "\n",
       "          Flag_WBGT  Flag_UTCI  \n",
       "2490            0.0        0.0  \n",
       "2491            0.0        0.0  \n",
       "2492            0.0        0.0  \n",
       "2493            0.0        0.0  \n",
       "2494            0.0        0.0  \n",
       "...             ...        ...  \n",
       "23834883        0.0        0.0  \n",
       "23834884        0.0        0.0  \n",
       "23834885        0.0        0.0  \n",
       "23834886        0.0        0.0  \n",
       "23834887        0.0        0.0  \n",
       "\n",
       "[1947926 rows x 30 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# # Dataset needs to be scaled down\n",
    "\n",
    "# # We can filter based on FIPS Code- (Numeric ID for States and Counties in U.S.)\n",
    "# # To look at one state (TX), filter DataFrame for 'StCoFIPS' values between 48001 and 48507, inclusive\n",
    "\n",
    "\n",
    "tx_filtered_df = df_all_0[(df_all_0['StCoFIPS'] >= 48001) & (df_all_0['StCoFIPS'] <= 48507)]\n",
    "tx_filtered_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>StCoFIPS</th>\n",
       "      <th>Date</th>\n",
       "      <th>Tmin_C</th>\n",
       "      <th>Tmax_C</th>\n",
       "      <th>Tmean_C</th>\n",
       "      <th>TDmin_C</th>\n",
       "      <th>TDmax_C</th>\n",
       "      <th>TDmean_C</th>\n",
       "      <th>NETmin_C</th>\n",
       "      <th>NETmax_C</th>\n",
       "      <th>...</th>\n",
       "      <th>UTCImin_C</th>\n",
       "      <th>UTCImax_C</th>\n",
       "      <th>UTCImean_C</th>\n",
       "      <th>Flag_T</th>\n",
       "      <th>Flag_TD</th>\n",
       "      <th>Flag_NET</th>\n",
       "      <th>Flag_HI</th>\n",
       "      <th>Flag_HX</th>\n",
       "      <th>Flag_WBGT</th>\n",
       "      <th>Flag_UTCI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1198</th>\n",
       "      <td>26001</td>\n",
       "      <td>10958.0</td>\n",
       "      <td>-0.93</td>\n",
       "      <td>7.23</td>\n",
       "      <td>2.68</td>\n",
       "      <td>-1.86</td>\n",
       "      <td>6.58</td>\n",
       "      <td>2.28</td>\n",
       "      <td>-16.580000</td>\n",
       "      <td>-5.27</td>\n",
       "      <td>...</td>\n",
       "      <td>-14.810000</td>\n",
       "      <td>3.30</td>\n",
       "      <td>-4.10</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1199</th>\n",
       "      <td>26003</td>\n",
       "      <td>10958.0</td>\n",
       "      <td>-4.46</td>\n",
       "      <td>-0.48</td>\n",
       "      <td>-2.41</td>\n",
       "      <td>-6.88</td>\n",
       "      <td>-1.79</td>\n",
       "      <td>-4.12</td>\n",
       "      <td>-21.200001</td>\n",
       "      <td>-14.49</td>\n",
       "      <td>...</td>\n",
       "      <td>-24.010000</td>\n",
       "      <td>-10.63</td>\n",
       "      <td>-15.89</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1200</th>\n",
       "      <td>26005</td>\n",
       "      <td>10958.0</td>\n",
       "      <td>3.19</td>\n",
       "      <td>11.90</td>\n",
       "      <td>7.77</td>\n",
       "      <td>1.81</td>\n",
       "      <td>9.11</td>\n",
       "      <td>6.22</td>\n",
       "      <td>-8.970000</td>\n",
       "      <td>0.40</td>\n",
       "      <td>...</td>\n",
       "      <td>-6.180000</td>\n",
       "      <td>6.61</td>\n",
       "      <td>-1.32</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1201</th>\n",
       "      <td>26007</td>\n",
       "      <td>10958.0</td>\n",
       "      <td>-2.58</td>\n",
       "      <td>6.13</td>\n",
       "      <td>2.10</td>\n",
       "      <td>-3.91</td>\n",
       "      <td>5.60</td>\n",
       "      <td>1.55</td>\n",
       "      <td>-19.290001</td>\n",
       "      <td>-6.51</td>\n",
       "      <td>...</td>\n",
       "      <td>-19.139999</td>\n",
       "      <td>1.79</td>\n",
       "      <td>-6.32</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1202</th>\n",
       "      <td>26009</td>\n",
       "      <td>10958.0</td>\n",
       "      <td>-2.29</td>\n",
       "      <td>6.32</td>\n",
       "      <td>1.85</td>\n",
       "      <td>-3.55</td>\n",
       "      <td>4.84</td>\n",
       "      <td>0.54</td>\n",
       "      <td>-18.520000</td>\n",
       "      <td>-6.21</td>\n",
       "      <td>...</td>\n",
       "      <td>-18.150000</td>\n",
       "      <td>-0.39</td>\n",
       "      <td>-8.58</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23833420</th>\n",
       "      <td>26157</td>\n",
       "      <td>18626.0</td>\n",
       "      <td>-3.02</td>\n",
       "      <td>3.74</td>\n",
       "      <td>0.04</td>\n",
       "      <td>-8.15</td>\n",
       "      <td>2.65</td>\n",
       "      <td>-2.72</td>\n",
       "      <td>-17.959999</td>\n",
       "      <td>-10.81</td>\n",
       "      <td>...</td>\n",
       "      <td>-20.600000</td>\n",
       "      <td>-8.60</td>\n",
       "      <td>-15.29</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23833421</th>\n",
       "      <td>26159</td>\n",
       "      <td>18626.0</td>\n",
       "      <td>-1.54</td>\n",
       "      <td>3.65</td>\n",
       "      <td>0.49</td>\n",
       "      <td>-6.44</td>\n",
       "      <td>3.41</td>\n",
       "      <td>-1.53</td>\n",
       "      <td>-17.420000</td>\n",
       "      <td>-10.88</td>\n",
       "      <td>...</td>\n",
       "      <td>-17.920000</td>\n",
       "      <td>-7.76</td>\n",
       "      <td>-13.67</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23833422</th>\n",
       "      <td>26161</td>\n",
       "      <td>18626.0</td>\n",
       "      <td>-2.24</td>\n",
       "      <td>5.97</td>\n",
       "      <td>1.12</td>\n",
       "      <td>-8.31</td>\n",
       "      <td>5.24</td>\n",
       "      <td>-1.72</td>\n",
       "      <td>-15.520000</td>\n",
       "      <td>-8.20</td>\n",
       "      <td>...</td>\n",
       "      <td>-17.139999</td>\n",
       "      <td>-6.12</td>\n",
       "      <td>-12.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23833423</th>\n",
       "      <td>26163</td>\n",
       "      <td>18626.0</td>\n",
       "      <td>-1.41</td>\n",
       "      <td>6.36</td>\n",
       "      <td>1.75</td>\n",
       "      <td>-6.98</td>\n",
       "      <td>5.55</td>\n",
       "      <td>-1.21</td>\n",
       "      <td>-15.580000</td>\n",
       "      <td>-8.18</td>\n",
       "      <td>...</td>\n",
       "      <td>-18.570000</td>\n",
       "      <td>-7.83</td>\n",
       "      <td>-13.65</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23833424</th>\n",
       "      <td>26165</td>\n",
       "      <td>18626.0</td>\n",
       "      <td>-4.62</td>\n",
       "      <td>0.93</td>\n",
       "      <td>-2.31</td>\n",
       "      <td>-8.71</td>\n",
       "      <td>-0.24</td>\n",
       "      <td>-4.92</td>\n",
       "      <td>-19.549999</td>\n",
       "      <td>-11.92</td>\n",
       "      <td>...</td>\n",
       "      <td>-18.610001</td>\n",
       "      <td>-6.10</td>\n",
       "      <td>-14.17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>636527 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          StCoFIPS     Date  Tmin_C  Tmax_C  Tmean_C  TDmin_C  TDmax_C  \\\n",
       "1198         26001  10958.0   -0.93    7.23     2.68    -1.86     6.58   \n",
       "1199         26003  10958.0   -4.46   -0.48    -2.41    -6.88    -1.79   \n",
       "1200         26005  10958.0    3.19   11.90     7.77     1.81     9.11   \n",
       "1201         26007  10958.0   -2.58    6.13     2.10    -3.91     5.60   \n",
       "1202         26009  10958.0   -2.29    6.32     1.85    -3.55     4.84   \n",
       "...            ...      ...     ...     ...      ...      ...      ...   \n",
       "23833420     26157  18626.0   -3.02    3.74     0.04    -8.15     2.65   \n",
       "23833421     26159  18626.0   -1.54    3.65     0.49    -6.44     3.41   \n",
       "23833422     26161  18626.0   -2.24    5.97     1.12    -8.31     5.24   \n",
       "23833423     26163  18626.0   -1.41    6.36     1.75    -6.98     5.55   \n",
       "23833424     26165  18626.0   -4.62    0.93    -2.31    -8.71    -0.24   \n",
       "\n",
       "          TDmean_C   NETmin_C  NETmax_C  ...  UTCImin_C  UTCImax_C  \\\n",
       "1198          2.28 -16.580000     -5.27  ... -14.810000       3.30   \n",
       "1199         -4.12 -21.200001    -14.49  ... -24.010000     -10.63   \n",
       "1200          6.22  -8.970000      0.40  ...  -6.180000       6.61   \n",
       "1201          1.55 -19.290001     -6.51  ... -19.139999       1.79   \n",
       "1202          0.54 -18.520000     -6.21  ... -18.150000      -0.39   \n",
       "...            ...        ...       ...  ...        ...        ...   \n",
       "23833420     -2.72 -17.959999    -10.81  ... -20.600000      -8.60   \n",
       "23833421     -1.53 -17.420000    -10.88  ... -17.920000      -7.76   \n",
       "23833422     -1.72 -15.520000     -8.20  ... -17.139999      -6.12   \n",
       "23833423     -1.21 -15.580000     -8.18  ... -18.570000      -7.83   \n",
       "23833424     -4.92 -19.549999    -11.92  ... -18.610001      -6.10   \n",
       "\n",
       "          UTCImean_C  Flag_T  Flag_TD  Flag_NET  Flag_HI  Flag_HX  Flag_WBGT  \\\n",
       "1198           -4.10     0.0      0.0       0.0      0.0      0.0        0.0   \n",
       "1199          -15.89     0.0      0.0       0.0      0.0      0.0        0.0   \n",
       "1200           -1.32     0.0      0.0       0.0      0.0      0.0        0.0   \n",
       "1201           -6.32     0.0      0.0       0.0      0.0      0.0        0.0   \n",
       "1202           -8.58     0.0      0.0       0.0      0.0      0.0        0.0   \n",
       "...              ...     ...      ...       ...      ...      ...        ...   \n",
       "23833420      -15.29     0.0      0.0       0.0      0.0      0.0        0.0   \n",
       "23833421      -13.67     0.0      0.0       0.0      0.0      0.0        0.0   \n",
       "23833422      -12.02     0.0      0.0       0.0      0.0      0.0        0.0   \n",
       "23833423      -13.65     0.0      0.0       0.0      0.0      0.0        0.0   \n",
       "23833424      -14.17     0.0      0.0       0.0      0.0      0.0        0.0   \n",
       "\n",
       "          Flag_UTCI  \n",
       "1198            0.0  \n",
       "1199            0.0  \n",
       "1200            0.0  \n",
       "1201            0.0  \n",
       "1202            0.0  \n",
       "...             ...  \n",
       "23833420        0.0  \n",
       "23833421        0.0  \n",
       "23833422        0.0  \n",
       "23833423        0.0  \n",
       "23833424        0.0  \n",
       "\n",
       "[636527 rows x 30 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mi_filtered_df = df_all_0[(df_all_0['StCoFIPS'] >= 26001) & (df_all_0['StCoFIPS'] <= 26165)]\n",
    "mi_filtered_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# # Filter DataFrame for single county using Harris County, TX as example)\n",
    "\n",
    "# harris_df = tx_filtered_df[(tx_filtered_df['StCoFIPS'] == 48201)]\n",
    "# harris_df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# # export csv \n",
    "\n",
    "# harris_df.to_csv('harris.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# # Filter DataFrame to (Houston Statistical Metro Area)\n",
    "\n",
    "\n",
    "# filter_counties = [26163, 26125,26099,26093,26147,26087]\n",
    "\n",
    "# # Filtering the DataFrame based on 'StCoFIPS' values\n",
    "\n",
    "# detroit_metro_counties = df_name[df_name['StCoFIPS'].isin(filter_counties)]\n",
    "# detroit_metro_counties\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# #Export to csv\n",
    "\n",
    "# detroit_metro_counties.to_csv('detroit_metro_daily_temps_2000_2020.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Data Cleaning and Preprocessing Cells"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
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      "/var/folders/xd/jl_0pvqx5295gyzxfw09l8b00000gn/T/ipykernel_60204/315877089.py:8: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  tx_filtered_df['Date'] = tx_filtered_df['Date'].apply(posixct_date_to_yyyymmdd)\n"
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       "      StCoFIPS      Date     Tmin_C  Tmax_C    Tmean_C    TDmin_C    TDmax_C  \\\n",
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   "source": [
    "# Function to convert days in 'posixct_date' (assumed to be days since 1970-01-01) to 'YYYYMMDD'\n",
    "\n",
    "def posixct_date_to_yyyymmdd(posixct_date):\n",
    "    epoch_start = datetime.datetime(1970, 1, 1)\n",
    "    actual_date = epoch_start + datetime.timedelta(seconds=int(posixct_date * 86400))  # Convert days to seconds\n",
    "    return actual_date.strftime('%Y%m%d')\n",
    "\n",
    "tx_filtered_df['Date'] = tx_filtered_df['Date'].apply(posixct_date_to_yyyymmdd)\n",
    "\n",
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   "execution_count": 29,
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      "/var/folders/xd/jl_0pvqx5295gyzxfw09l8b00000gn/T/ipykernel_60204/625484653.py:8: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
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      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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       "      StCoFIPS      Date  Tmin_C  Tmax_C  Tmean_C  TDmin_C  TDmax_C  TDmean_C  \\\n",
       "1198     26001  20000102   -0.93    7.23     2.68    -1.86     6.58      2.28   \n",
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       "1202     26009  20000102   -2.29    6.32     1.85    -3.55     4.84      0.54   \n",
       "\n",
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       "[5 rows x 30 columns]"
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     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Function to convert days in 'posixct_date' (assumed to be days since 1970-01-01) to 'YYYYMMDD'\n",
    "\n",
    "def posixct_date_to_yyyymmdd(posixct_date):\n",
    "    epoch_start = datetime.datetime(1970, 1, 1)\n",
    "    actual_date = epoch_start + datetime.timedelta(seconds=int(posixct_date * 86400))  # Convert days to seconds\n",
    "    return actual_date.strftime('%Y%m%d')\n",
    "\n",
    "mi_filtered_df['Date'] = mi_filtered_df['Date'].apply(posixct_date_to_yyyymmdd)\n",
    "\n",
    "mi_filtered_df.head()"
   ]
  },
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   "execution_count": null,
   "metadata": {},
   "outputs": [],
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   "execution_count": 10,
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      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 23835252 entries, 1 to 23835252\n",
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      " #   Column      Dtype  \n",
      "---  ------      -----  \n",
      " 0   StCoFIPS    int32  \n",
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      " 5   TDmin_C     float32\n",
      " 6   TDmax_C     float32\n",
      " 7   TDmean_C    float32\n",
      " 8   NETmin_C    float32\n",
      " 9   NETmax_C    float32\n",
      " 10  NETmean_C   float32\n",
      " 11  HImin_C     float32\n",
      " 12  HImax_C     float32\n",
      " 13  HImean_C    float32\n",
      " 14  HXmin_C     float32\n",
      " 15  HXmax_C     float32\n",
      " 16  HXmean_C    float32\n",
      " 17  WBGTmin_C   float32\n",
      " 18  WBGTmax_C   float32\n",
      " 19  WBGTmean_C  float32\n",
      " 20  UTCImin_C   float32\n",
      " 21  UTCImax_C   float32\n",
      " 22  UTCImean_C  float32\n",
      " 23  Flag_T      float32\n",
      " 24  Flag_TD     float32\n",
      " 25  Flag_NET    float32\n",
      " 26  Flag_HI     float32\n",
      " 27  Flag_HX     float32\n",
      " 28  Flag_WBGT   float32\n",
      " 29  Flag_UTCI   float32\n",
      "dtypes: float32(28), int32(1), object(1)\n",
      "memory usage: 2.8+ GB\n"
     ]
    }
   ],
   "source": [
    "\n",
    "df_all_0.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert \"Date\" to datetime format\n",
    "df_all_0['Date'] = pd.to_datetime(df_all_0['Date'].astype(str), format='%Y%m%d')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/xd/jl_0pvqx5295gyzxfw09l8b00000gn/T/ipykernel_60204/3590510221.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  tx_filtered_df['Date'] = pd.to_datetime(tx_filtered_df['Date'].astype(str), format='%Y%m%d')\n"
     ]
    }
   ],
   "source": [
    "# Convert \"Date\" to datetime format\n",
    "tx_filtered_df['Date'] = pd.to_datetime(tx_filtered_df['Date'].astype(str), format='%Y%m%d')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 1947926 entries, 2490 to 23834887\n",
      "Data columns (total 30 columns):\n",
      " #   Column      Dtype         \n",
      "---  ------      -----         \n",
      " 0   StCoFIPS    int32         \n",
      " 1   Date        datetime64[ns]\n",
      " 2   Tmin_C      float32       \n",
      " 3   Tmax_C      float32       \n",
      " 4   Tmean_C     float32       \n",
      " 5   TDmin_C     float32       \n",
      " 6   TDmax_C     float32       \n",
      " 7   TDmean_C    float32       \n",
      " 8   NETmin_C    float32       \n",
      " 9   NETmax_C    float32       \n",
      " 10  NETmean_C   float32       \n",
      " 11  HImin_C     float32       \n",
      " 12  HImax_C     float32       \n",
      " 13  HImean_C    float32       \n",
      " 14  HXmin_C     float32       \n",
      " 15  HXmax_C     float32       \n",
      " 16  HXmean_C    float32       \n",
      " 17  WBGTmin_C   float32       \n",
      " 18  WBGTmax_C   float32       \n",
      " 19  WBGTmean_C  float32       \n",
      " 20  UTCImin_C   float32       \n",
      " 21  UTCImax_C   float32       \n",
      " 22  UTCImean_C  float32       \n",
      " 23  Flag_T      float32       \n",
      " 24  Flag_TD     float32       \n",
      " 25  Flag_NET    float32       \n",
      " 26  Flag_HI     float32       \n",
      " 27  Flag_HX     float32       \n",
      " 28  Flag_WBGT   float32       \n",
      " 29  Flag_UTCI   float32       \n",
      "dtypes: datetime64[ns](1), float32(28), int32(1)\n",
      "memory usage: 245.2 MB\n"
     ]
    }
   ],
   "source": [
    "tx_filtered_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/xd/jl_0pvqx5295gyzxfw09l8b00000gn/T/ipykernel_60204/2090068948.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  mi_filtered_df['Date'] = pd.to_datetime(mi_filtered_df['Date'].astype(str), format='%Y%m%d')\n"
     ]
    }
   ],
   "source": [
    "# Convert \"Date\" to datetime format\n",
    "mi_filtered_df['Date'] = pd.to_datetime(mi_filtered_df['Date'].astype(str), format='%Y%m%d')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 636527 entries, 1198 to 23833424\n",
      "Data columns (total 30 columns):\n",
      " #   Column      Non-Null Count   Dtype         \n",
      "---  ------      --------------   -----         \n",
      " 0   StCoFIPS    636527 non-null  int32         \n",
      " 1   Date        636527 non-null  datetime64[ns]\n",
      " 2   Tmin_C      636527 non-null  float32       \n",
      " 3   Tmax_C      636527 non-null  float32       \n",
      " 4   Tmean_C     636527 non-null  float32       \n",
      " 5   TDmin_C     636527 non-null  float32       \n",
      " 6   TDmax_C     636527 non-null  float32       \n",
      " 7   TDmean_C    636527 non-null  float32       \n",
      " 8   NETmin_C    636527 non-null  float32       \n",
      " 9   NETmax_C    636527 non-null  float32       \n",
      " 10  NETmean_C   636527 non-null  float32       \n",
      " 11  HImin_C     636527 non-null  float32       \n",
      " 12  HImax_C     636527 non-null  float32       \n",
      " 13  HImean_C    636527 non-null  float32       \n",
      " 14  HXmin_C     636527 non-null  float32       \n",
      " 15  HXmax_C     636527 non-null  float32       \n",
      " 16  HXmean_C    636527 non-null  float32       \n",
      " 17  WBGTmin_C   636527 non-null  float32       \n",
      " 18  WBGTmax_C   636527 non-null  float32       \n",
      " 19  WBGTmean_C  636527 non-null  float32       \n",
      " 20  UTCImin_C   636527 non-null  float32       \n",
      " 21  UTCImax_C   636527 non-null  float32       \n",
      " 22  UTCImean_C  636527 non-null  float32       \n",
      " 23  Flag_T      636527 non-null  float32       \n",
      " 24  Flag_TD     636527 non-null  float32       \n",
      " 25  Flag_NET    636527 non-null  float32       \n",
      " 26  Flag_HI     636527 non-null  float32       \n",
      " 27  Flag_HX     636527 non-null  float32       \n",
      " 28  Flag_WBGT   636527 non-null  float32       \n",
      " 29  Flag_UTCI   636527 non-null  float32       \n",
      "dtypes: datetime64[ns](1), float32(28), int32(1)\n",
      "memory usage: 80.1 MB\n"
     ]
    }
   ],
   "source": [
    "mi_filtered_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
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       "      <td>16.230000</td>\n",
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       "      <td>16.280001</td>\n",
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       "      <td>7.29</td>\n",
       "      <td>14.83</td>\n",
       "      <td>10.17</td>\n",
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       "      <td>11.59</td>\n",
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       "      <td>13.46</td>\n",
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       "         StCoFIPS  Tmin_C     Tmax_C    Tmean_C  TDmin_C    TDmax_C  TDmean_C  \\\n",
       "Date                                                                            \n",
       "10958.0      1001   14.62  21.629999  17.280001    14.45  16.520000     15.38   \n",
       "10958.0      1003   16.26  22.610001  18.799999    15.82  18.430000     17.18   \n",
       "10958.0      1005   13.88  20.090000  16.230000    13.80  16.280001     14.97   \n",
       "10958.0      1007   13.57  21.020000  16.620001    13.46  16.680000     15.04   \n",
       "10958.0      1009   13.49  18.490000  15.290000    13.35  15.800000     14.52   \n",
       "\n",
       "         NETmin_C  NETmax_C  NETmean_C  ...  UTCImin_C  UTCImax_C  UTCImean_C  \\\n",
       "Date                                    ...                                     \n",
       "10958.0      8.10     15.61      10.88  ...      11.98  24.879999       16.57   \n",
       "10958.0     10.10     15.88      12.35  ...      13.32  25.459999       17.92   \n",
       "10958.0      7.29     14.83      10.17  ...      11.59  23.100000       15.76   \n",
       "10958.0      6.52     15.05      10.09  ...       9.71  24.620001       15.55   \n",
       "10958.0      5.84     12.15       8.19  ...       9.77  21.110001       13.55   \n",
       "\n",
       "         Flag_T  Flag_TD  Flag_NET  Flag_HI  Flag_HX  Flag_WBGT  Flag_UTCI  \n",
       "Date                                                                        \n",
       "10958.0     0.0      0.0       0.0      0.0      0.0        0.0        0.0  \n",
       "10958.0     0.0      0.0       0.0      0.0      0.0        0.0        0.0  \n",
       "10958.0     0.0      0.0       0.0      0.0      0.0        0.0        0.0  \n",
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       "\n",
       "[5 rows x 29 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Drop columns\n",
    "\n",
    "df_all_0f = df_all_0.drop(['Flag_T','Flag_TD','Flag_NET','Flag_HI','Flag_HX','Flag_WBGT', 'Flag_UTCI'], axis=1)\n",
    "\n",
    "#set \"Date\" as index\n",
    "\n",
    "df_all_0.set_index(\"Date\", inplace=True)\n",
    "\n",
    "df_all_0.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>21.980000</td>\n",
       "      <td>18.799999</td>\n",
       "      <td>10.64</td>\n",
       "      <td>25.030001</td>\n",
       "      <td>16.680000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>48003</td>\n",
       "      <td>3.730000</td>\n",
       "      <td>17.75</td>\n",
       "      <td>11.380000</td>\n",
       "      <td>-7.530000</td>\n",
       "      <td>0.110000</td>\n",
       "      <td>-5.020000</td>\n",
       "      <td>-4.42</td>\n",
       "      <td>8.370000</td>\n",
       "      <td>2.41</td>\n",
       "      <td>...</td>\n",
       "      <td>9.600000</td>\n",
       "      <td>0.140000</td>\n",
       "      <td>14.610000</td>\n",
       "      <td>8.190000</td>\n",
       "      <td>0.13</td>\n",
       "      <td>12.890000</td>\n",
       "      <td>6.880000</td>\n",
       "      <td>-15.64</td>\n",
       "      <td>17.870001</td>\n",
       "      <td>2.060000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>48005</td>\n",
       "      <td>17.860001</td>\n",
       "      <td>23.35</td>\n",
       "      <td>19.870001</td>\n",
       "      <td>16.650000</td>\n",
       "      <td>18.750000</td>\n",
       "      <td>17.700001</td>\n",
       "      <td>10.24</td>\n",
       "      <td>17.209999</td>\n",
       "      <td>13.19</td>\n",
       "      <td>...</td>\n",
       "      <td>20.209999</td>\n",
       "      <td>22.820000</td>\n",
       "      <td>29.020000</td>\n",
       "      <td>25.549999</td>\n",
       "      <td>17.09</td>\n",
       "      <td>22.309999</td>\n",
       "      <td>19.090000</td>\n",
       "      <td>12.56</td>\n",
       "      <td>25.110001</td>\n",
       "      <td>17.629999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>48007</td>\n",
       "      <td>20.200001</td>\n",
       "      <td>24.07</td>\n",
       "      <td>21.410000</td>\n",
       "      <td>18.219999</td>\n",
       "      <td>18.990000</td>\n",
       "      <td>18.629999</td>\n",
       "      <td>11.46</td>\n",
       "      <td>16.230000</td>\n",
       "      <td>13.01</td>\n",
       "      <td>...</td>\n",
       "      <td>21.809999</td>\n",
       "      <td>26.340000</td>\n",
       "      <td>30.330000</td>\n",
       "      <td>27.750000</td>\n",
       "      <td>19.17</td>\n",
       "      <td>23.400000</td>\n",
       "      <td>20.590000</td>\n",
       "      <td>10.18</td>\n",
       "      <td>24.280001</td>\n",
       "      <td>15.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>48009</td>\n",
       "      <td>10.840000</td>\n",
       "      <td>20.84</td>\n",
       "      <td>15.860000</td>\n",
       "      <td>-4.590000</td>\n",
       "      <td>10.990000</td>\n",
       "      <td>3.660000</td>\n",
       "      <td>3.67</td>\n",
       "      <td>13.370000</td>\n",
       "      <td>8.46</td>\n",
       "      <td>...</td>\n",
       "      <td>14.780000</td>\n",
       "      <td>10.370000</td>\n",
       "      <td>19.860001</td>\n",
       "      <td>14.980000</td>\n",
       "      <td>8.49</td>\n",
       "      <td>16.740000</td>\n",
       "      <td>12.500000</td>\n",
       "      <td>4.01</td>\n",
       "      <td>25.650000</td>\n",
       "      <td>12.210000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            StCoFIPS     Tmin_C  Tmax_C    Tmean_C    TDmin_C    TDmax_C  \\\n",
       "Date                                                                       \n",
       "2000-01-02     48001  17.969999   22.02  19.469999  16.639999  18.709999   \n",
       "2000-01-02     48003   3.730000   17.75  11.380000  -7.530000   0.110000   \n",
       "2000-01-02     48005  17.860001   23.35  19.870001  16.650000  18.750000   \n",
       "2000-01-02     48007  20.200001   24.07  21.410000  18.219999  18.990000   \n",
       "2000-01-02     48009  10.840000   20.84  15.860000  -4.590000  10.990000   \n",
       "\n",
       "             TDmean_C  NETmin_C   NETmax_C  NETmean_C  ...   HImean_C  \\\n",
       "Date                                                   ...              \n",
       "2000-01-02  17.549999      9.58  15.810000      12.50  ...  19.790001   \n",
       "2000-01-02  -5.020000     -4.42   8.370000       2.41  ...   9.600000   \n",
       "2000-01-02  17.700001     10.24  17.209999      13.19  ...  20.209999   \n",
       "2000-01-02  18.629999     11.46  16.230000      13.01  ...  21.809999   \n",
       "2000-01-02   3.660000      3.67  13.370000       8.46  ...  14.780000   \n",
       "\n",
       "              HXmin_C    HXmax_C   HXmean_C  WBGTmin_C  WBGTmax_C  WBGTmean_C  \\\n",
       "Date                                                                            \n",
       "2000-01-02  22.940001  27.920000  25.049999      17.18  21.980000   18.799999   \n",
       "2000-01-02   0.140000  14.610000   8.190000       0.13  12.890000    6.880000   \n",
       "2000-01-02  22.820000  29.020000  25.549999      17.09  22.309999   19.090000   \n",
       "2000-01-02  26.340000  30.330000  27.750000      19.17  23.400000   20.590000   \n",
       "2000-01-02  10.370000  19.860001  14.980000       8.49  16.740000   12.500000   \n",
       "\n",
       "            UTCImin_C  UTCImax_C  UTCImean_C  \n",
       "Date                                          \n",
       "2000-01-02      10.64  25.030001   16.680000  \n",
       "2000-01-02     -15.64  17.870001    2.060000  \n",
       "2000-01-02      12.56  25.110001   17.629999  \n",
       "2000-01-02      10.18  24.280001   15.300000  \n",
       "2000-01-02       4.01  25.650000   12.210000  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Drop columns (TX)\n",
    "\n",
    "tx_filtered_df = tx_filtered_df.drop(['Flag_T','Flag_TD','Flag_NET','Flag_HI','Flag_HX','Flag_WBGT', 'Flag_UTCI'], axis=1)\n",
    "\n",
    "#set \"Date\" as index\n",
    "\n",
    "tx_filtered_df.set_index(\"Date\", inplace=True)\n",
    "\n",
    "tx_filtered_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>StCoFIPS</th>\n",
       "      <th>Tmin_C</th>\n",
       "      <th>Tmax_C</th>\n",
       "      <th>Tmean_C</th>\n",
       "      <th>TDmin_C</th>\n",
       "      <th>TDmax_C</th>\n",
       "      <th>TDmean_C</th>\n",
       "      <th>NETmin_C</th>\n",
       "      <th>NETmax_C</th>\n",
       "      <th>NETmean_C</th>\n",
       "      <th>...</th>\n",
       "      <th>HImean_C</th>\n",
       "      <th>HXmin_C</th>\n",
       "      <th>HXmax_C</th>\n",
       "      <th>HXmean_C</th>\n",
       "      <th>WBGTmin_C</th>\n",
       "      <th>WBGTmax_C</th>\n",
       "      <th>WBGTmean_C</th>\n",
       "      <th>UTCImin_C</th>\n",
       "      <th>UTCImax_C</th>\n",
       "      <th>UTCImean_C</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>26001</td>\n",
       "      <td>-0.93</td>\n",
       "      <td>7.23</td>\n",
       "      <td>2.68</td>\n",
       "      <td>-1.86</td>\n",
       "      <td>6.58</td>\n",
       "      <td>2.28</td>\n",
       "      <td>-16.580000</td>\n",
       "      <td>-5.27</td>\n",
       "      <td>-8.79</td>\n",
       "      <td>...</td>\n",
       "      <td>2.46</td>\n",
       "      <td>-3.51</td>\n",
       "      <td>7.08</td>\n",
       "      <td>1.18</td>\n",
       "      <td>-1.66</td>\n",
       "      <td>6.68</td>\n",
       "      <td>2.24</td>\n",
       "      <td>-14.810000</td>\n",
       "      <td>3.30</td>\n",
       "      <td>-4.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>26003</td>\n",
       "      <td>-4.46</td>\n",
       "      <td>-0.48</td>\n",
       "      <td>-2.41</td>\n",
       "      <td>-6.88</td>\n",
       "      <td>-1.79</td>\n",
       "      <td>-4.12</td>\n",
       "      <td>-21.200001</td>\n",
       "      <td>-14.49</td>\n",
       "      <td>-17.32</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.41</td>\n",
       "      <td>-7.95</td>\n",
       "      <td>-3.05</td>\n",
       "      <td>-5.44</td>\n",
       "      <td>-5.59</td>\n",
       "      <td>-0.74</td>\n",
       "      <td>-3.25</td>\n",
       "      <td>-24.010000</td>\n",
       "      <td>-10.63</td>\n",
       "      <td>-15.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>26005</td>\n",
       "      <td>3.19</td>\n",
       "      <td>11.90</td>\n",
       "      <td>7.77</td>\n",
       "      <td>1.81</td>\n",
       "      <td>9.11</td>\n",
       "      <td>6.22</td>\n",
       "      <td>-8.970000</td>\n",
       "      <td>0.40</td>\n",
       "      <td>-4.05</td>\n",
       "      <td>...</td>\n",
       "      <td>7.13</td>\n",
       "      <td>1.51</td>\n",
       "      <td>12.72</td>\n",
       "      <td>7.54</td>\n",
       "      <td>2.31</td>\n",
       "      <td>11.98</td>\n",
       "      <td>7.24</td>\n",
       "      <td>-6.180000</td>\n",
       "      <td>6.61</td>\n",
       "      <td>-1.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>26007</td>\n",
       "      <td>-2.58</td>\n",
       "      <td>6.13</td>\n",
       "      <td>2.10</td>\n",
       "      <td>-3.91</td>\n",
       "      <td>5.60</td>\n",
       "      <td>1.55</td>\n",
       "      <td>-19.290001</td>\n",
       "      <td>-6.51</td>\n",
       "      <td>-10.37</td>\n",
       "      <td>...</td>\n",
       "      <td>1.96</td>\n",
       "      <td>-5.59</td>\n",
       "      <td>5.62</td>\n",
       "      <td>0.39</td>\n",
       "      <td>-3.36</td>\n",
       "      <td>5.60</td>\n",
       "      <td>1.67</td>\n",
       "      <td>-19.139999</td>\n",
       "      <td>1.79</td>\n",
       "      <td>-6.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>26009</td>\n",
       "      <td>-2.29</td>\n",
       "      <td>6.32</td>\n",
       "      <td>1.85</td>\n",
       "      <td>-3.55</td>\n",
       "      <td>4.84</td>\n",
       "      <td>0.54</td>\n",
       "      <td>-18.520000</td>\n",
       "      <td>-6.21</td>\n",
       "      <td>-11.47</td>\n",
       "      <td>...</td>\n",
       "      <td>1.68</td>\n",
       "      <td>-5.23</td>\n",
       "      <td>5.55</td>\n",
       "      <td>-0.13</td>\n",
       "      <td>-3.06</td>\n",
       "      <td>5.69</td>\n",
       "      <td>1.15</td>\n",
       "      <td>-18.150000</td>\n",
       "      <td>-0.39</td>\n",
       "      <td>-8.58</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            StCoFIPS  Tmin_C  Tmax_C  Tmean_C  TDmin_C  TDmax_C  TDmean_C  \\\n",
       "Date                                                                        \n",
       "2000-01-02     26001   -0.93    7.23     2.68    -1.86     6.58      2.28   \n",
       "2000-01-02     26003   -4.46   -0.48    -2.41    -6.88    -1.79     -4.12   \n",
       "2000-01-02     26005    3.19   11.90     7.77     1.81     9.11      6.22   \n",
       "2000-01-02     26007   -2.58    6.13     2.10    -3.91     5.60      1.55   \n",
       "2000-01-02     26009   -2.29    6.32     1.85    -3.55     4.84      0.54   \n",
       "\n",
       "             NETmin_C  NETmax_C  NETmean_C  ...  HImean_C  HXmin_C  HXmax_C  \\\n",
       "Date                                        ...                               \n",
       "2000-01-02 -16.580000     -5.27      -8.79  ...      2.46    -3.51     7.08   \n",
       "2000-01-02 -21.200001    -14.49     -17.32  ...     -2.41    -7.95    -3.05   \n",
       "2000-01-02  -8.970000      0.40      -4.05  ...      7.13     1.51    12.72   \n",
       "2000-01-02 -19.290001     -6.51     -10.37  ...      1.96    -5.59     5.62   \n",
       "2000-01-02 -18.520000     -6.21     -11.47  ...      1.68    -5.23     5.55   \n",
       "\n",
       "            HXmean_C  WBGTmin_C  WBGTmax_C  WBGTmean_C  UTCImin_C  UTCImax_C  \\\n",
       "Date                                                                           \n",
       "2000-01-02      1.18      -1.66       6.68        2.24 -14.810000       3.30   \n",
       "2000-01-02     -5.44      -5.59      -0.74       -3.25 -24.010000     -10.63   \n",
       "2000-01-02      7.54       2.31      11.98        7.24  -6.180000       6.61   \n",
       "2000-01-02      0.39      -3.36       5.60        1.67 -19.139999       1.79   \n",
       "2000-01-02     -0.13      -3.06       5.69        1.15 -18.150000      -0.39   \n",
       "\n",
       "            UTCImean_C  \n",
       "Date                    \n",
       "2000-01-02       -4.10  \n",
       "2000-01-02      -15.89  \n",
       "2000-01-02       -1.32  \n",
       "2000-01-02       -6.32  \n",
       "2000-01-02       -8.58  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Drop columns (MI)\n",
    "\n",
    "mi_filtered_df = mi_filtered_df.drop(['Flag_T','Flag_TD','Flag_NET','Flag_HI','Flag_HX','Flag_WBGT', 'Flag_UTCI'], axis=1)\n",
    "\n",
    "#set \"Date\" as index\n",
    "\n",
    "mi_filtered_df.set_index(\"Date\", inplace=True)\n",
    "\n",
    "mi_filtered_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FIPS Code-County</th>\n",
       "      <th>Min Ambient Temp</th>\n",
       "      <th>Max Ambient Temp</th>\n",
       "      <th>Mean Ambient Temp</th>\n",
       "      <th>Min Dew Point</th>\n",
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       "      <th>Mean Dew Point</th>\n",
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       "      <th>Mean Net Effective Temp</th>\n",
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       "      <th>Flag_UTCI</th>\n",
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       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>1001</td>\n",
       "      <td>14.620000</td>\n",
       "      <td>21.629999</td>\n",
       "      <td>17.280001</td>\n",
       "      <td>14.450000</td>\n",
       "      <td>16.520000</td>\n",
       "      <td>15.380000</td>\n",
       "      <td>8.100000</td>\n",
       "      <td>15.610000</td>\n",
       "      <td>10.880000</td>\n",
       "      <td>...</td>\n",
       "      <td>11.980000</td>\n",
       "      <td>24.879999</td>\n",
       "      <td>16.570000</td>\n",
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       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>1003</td>\n",
       "      <td>16.260000</td>\n",
       "      <td>22.610001</td>\n",
       "      <td>18.799999</td>\n",
       "      <td>15.820000</td>\n",
       "      <td>18.430000</td>\n",
       "      <td>17.180000</td>\n",
       "      <td>10.100000</td>\n",
       "      <td>15.880000</td>\n",
       "      <td>12.350000</td>\n",
       "      <td>...</td>\n",
       "      <td>13.320000</td>\n",
       "      <td>25.459999</td>\n",
       "      <td>17.920000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>1005</td>\n",
       "      <td>13.880000</td>\n",
       "      <td>20.090000</td>\n",
       "      <td>16.230000</td>\n",
       "      <td>13.800000</td>\n",
       "      <td>16.280001</td>\n",
       "      <td>14.970000</td>\n",
       "      <td>7.290000</td>\n",
       "      <td>14.830000</td>\n",
       "      <td>10.170000</td>\n",
       "      <td>...</td>\n",
       "      <td>11.590000</td>\n",
       "      <td>23.100000</td>\n",
       "      <td>15.760000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>1007</td>\n",
       "      <td>13.570000</td>\n",
       "      <td>21.020000</td>\n",
       "      <td>16.620001</td>\n",
       "      <td>13.460000</td>\n",
       "      <td>16.680000</td>\n",
       "      <td>15.040000</td>\n",
       "      <td>6.520000</td>\n",
       "      <td>15.050000</td>\n",
       "      <td>10.090000</td>\n",
       "      <td>...</td>\n",
       "      <td>9.710000</td>\n",
       "      <td>24.620001</td>\n",
       "      <td>15.550000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>1009</td>\n",
       "      <td>13.490000</td>\n",
       "      <td>18.490000</td>\n",
       "      <td>15.290000</td>\n",
       "      <td>13.350000</td>\n",
       "      <td>15.800000</td>\n",
       "      <td>14.520000</td>\n",
       "      <td>5.840000</td>\n",
       "      <td>12.150000</td>\n",
       "      <td>8.190000</td>\n",
       "      <td>...</td>\n",
       "      <td>9.770000</td>\n",
       "      <td>21.110001</td>\n",
       "      <td>13.550000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-30</th>\n",
       "      <td>56037</td>\n",
       "      <td>-18.959999</td>\n",
       "      <td>-6.530000</td>\n",
       "      <td>-12.460000</td>\n",
       "      <td>-22.549999</td>\n",
       "      <td>-11.140000</td>\n",
       "      <td>-16.629999</td>\n",
       "      <td>-34.660000</td>\n",
       "      <td>-19.940001</td>\n",
       "      <td>-26.650000</td>\n",
       "      <td>...</td>\n",
       "      <td>-34.779999</td>\n",
       "      <td>-5.290000</td>\n",
       "      <td>-22.959999</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-30</th>\n",
       "      <td>56039</td>\n",
       "      <td>-20.900000</td>\n",
       "      <td>-11.780000</td>\n",
       "      <td>-15.730000</td>\n",
       "      <td>-23.230000</td>\n",
       "      <td>-14.330000</td>\n",
       "      <td>-18.450001</td>\n",
       "      <td>-28.820000</td>\n",
       "      <td>-17.070000</td>\n",
       "      <td>-23.100000</td>\n",
       "      <td>...</td>\n",
       "      <td>-26.260000</td>\n",
       "      <td>-3.410000</td>\n",
       "      <td>-16.930000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-30</th>\n",
       "      <td>56041</td>\n",
       "      <td>-17.400000</td>\n",
       "      <td>-4.620000</td>\n",
       "      <td>-11.120000</td>\n",
       "      <td>-21.910000</td>\n",
       "      <td>-10.230000</td>\n",
       "      <td>-15.980000</td>\n",
       "      <td>-31.110001</td>\n",
       "      <td>-15.470000</td>\n",
       "      <td>-23.129999</td>\n",
       "      <td>...</td>\n",
       "      <td>-31.590000</td>\n",
       "      <td>-0.860000</td>\n",
       "      <td>-18.830000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-30</th>\n",
       "      <td>56043</td>\n",
       "      <td>-14.400000</td>\n",
       "      <td>-1.320000</td>\n",
       "      <td>-8.460000</td>\n",
       "      <td>-18.790001</td>\n",
       "      <td>-11.980000</td>\n",
       "      <td>-15.820000</td>\n",
       "      <td>-23.910000</td>\n",
       "      <td>-4.220000</td>\n",
       "      <td>-14.330000</td>\n",
       "      <td>...</td>\n",
       "      <td>-23.879999</td>\n",
       "      <td>12.100000</td>\n",
       "      <td>-10.110000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-30</th>\n",
       "      <td>56045</td>\n",
       "      <td>-10.170000</td>\n",
       "      <td>1.020000</td>\n",
       "      <td>-5.550000</td>\n",
       "      <td>-16.530001</td>\n",
       "      <td>-10.280000</td>\n",
       "      <td>-13.640000</td>\n",
       "      <td>-23.049999</td>\n",
       "      <td>-6.860000</td>\n",
       "      <td>-15.110000</td>\n",
       "      <td>...</td>\n",
       "      <td>-25.030001</td>\n",
       "      <td>3.480000</td>\n",
       "      <td>-14.240000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>23835252 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            FIPS Code-County  Min Ambient Temp  Max Ambient Temp  \\\n",
       "Date                                                               \n",
       "2000-01-02              1001         14.620000         21.629999   \n",
       "2000-01-02              1003         16.260000         22.610001   \n",
       "2000-01-02              1005         13.880000         20.090000   \n",
       "2000-01-02              1007         13.570000         21.020000   \n",
       "2000-01-02              1009         13.490000         18.490000   \n",
       "...                      ...               ...               ...   \n",
       "2020-12-30             56037        -18.959999         -6.530000   \n",
       "2020-12-30             56039        -20.900000        -11.780000   \n",
       "2020-12-30             56041        -17.400000         -4.620000   \n",
       "2020-12-30             56043        -14.400000         -1.320000   \n",
       "2020-12-30             56045        -10.170000          1.020000   \n",
       "\n",
       "            Mean Ambient Temp  Min Dew Point  Max Dew point  Mean Dew Point  \\\n",
       "Date                                                                          \n",
       "2000-01-02          17.280001      14.450000      16.520000       15.380000   \n",
       "2000-01-02          18.799999      15.820000      18.430000       17.180000   \n",
       "2000-01-02          16.230000      13.800000      16.280001       14.970000   \n",
       "2000-01-02          16.620001      13.460000      16.680000       15.040000   \n",
       "2000-01-02          15.290000      13.350000      15.800000       14.520000   \n",
       "...                       ...            ...            ...             ...   \n",
       "2020-12-30         -12.460000     -22.549999     -11.140000      -16.629999   \n",
       "2020-12-30         -15.730000     -23.230000     -14.330000      -18.450001   \n",
       "2020-12-30         -11.120000     -21.910000     -10.230000      -15.980000   \n",
       "2020-12-30          -8.460000     -18.790001     -11.980000      -15.820000   \n",
       "2020-12-30          -5.550000     -16.530001     -10.280000      -13.640000   \n",
       "\n",
       "            Min Net Effective Temp  Max Net Effective Temp  \\\n",
       "Date                                                         \n",
       "2000-01-02                8.100000               15.610000   \n",
       "2000-01-02               10.100000               15.880000   \n",
       "2000-01-02                7.290000               14.830000   \n",
       "2000-01-02                6.520000               15.050000   \n",
       "2000-01-02                5.840000               12.150000   \n",
       "...                            ...                     ...   \n",
       "2020-12-30              -34.660000              -19.940001   \n",
       "2020-12-30              -28.820000              -17.070000   \n",
       "2020-12-30              -31.110001              -15.470000   \n",
       "2020-12-30              -23.910000               -4.220000   \n",
       "2020-12-30              -23.049999               -6.860000   \n",
       "\n",
       "            Mean Net Effective Temp  ...   Min UTCI   Max UTCI  Mean UTCI  \\\n",
       "Date                                 ...                                    \n",
       "2000-01-02                10.880000  ...  11.980000  24.879999  16.570000   \n",
       "2000-01-02                12.350000  ...  13.320000  25.459999  17.920000   \n",
       "2000-01-02                10.170000  ...  11.590000  23.100000  15.760000   \n",
       "2000-01-02                10.090000  ...   9.710000  24.620001  15.550000   \n",
       "2000-01-02                 8.190000  ...   9.770000  21.110001  13.550000   \n",
       "...                             ...  ...        ...        ...        ...   \n",
       "2020-12-30               -26.650000  ... -34.779999  -5.290000 -22.959999   \n",
       "2020-12-30               -23.100000  ... -26.260000  -3.410000 -16.930000   \n",
       "2020-12-30               -23.129999  ... -31.590000  -0.860000 -18.830000   \n",
       "2020-12-30               -14.330000  ... -23.879999  12.100000 -10.110000   \n",
       "2020-12-30               -15.110000  ... -25.030001   3.480000 -14.240000   \n",
       "\n",
       "            Flag_T  Flag_TD  Flag_NET  Flag_HI  Flag_HX  Flag_WBGT  Flag_UTCI  \n",
       "Date                                                                           \n",
       "2000-01-02     0.0      0.0       0.0      0.0      0.0        0.0        0.0  \n",
       "2000-01-02     0.0      0.0       0.0      0.0      0.0        0.0        0.0  \n",
       "2000-01-02     0.0      0.0       0.0      0.0      0.0        0.0        0.0  \n",
       "2000-01-02     0.0      0.0       0.0      0.0      0.0        0.0        0.0  \n",
       "2000-01-02     0.0      0.0       0.0      0.0      0.0        0.0        0.0  \n",
       "...            ...      ...       ...      ...      ...        ...        ...  \n",
       "2020-12-30     0.0      0.0       0.0      0.0      0.0        0.0        0.0  \n",
       "2020-12-30     0.0      0.0       0.0      0.0      0.0        0.0        0.0  \n",
       "2020-12-30     0.0      0.0       0.0      0.0      0.0        0.0        0.0  \n",
       "2020-12-30     0.0      0.0       0.0      0.0      0.0        0.0        0.0  \n",
       "2020-12-30     0.0      0.0       0.0      0.0      0.0        0.0        0.0  \n",
       "\n",
       "[23835252 rows x 29 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " # Rename columns (ALL)\n",
    "\n",
    "df_all_1 = df_all_0.rename(columns={\n",
    "                                                'StCoFIPS':'FIPS Code-County',\n",
    "                                                'Tmin_C':'Min Ambient Temp',\n",
    "                                                'Tmax_C':'Max Ambient Temp',\n",
    "                                                'Tmean_C':'Mean Ambient Temp',\n",
    "                                                'TDmin_C':'Min Dew Point',\n",
    "                                                'TDmax_C':'Max Dew point',\n",
    "                                                'TDmean_C':'Mean Dew Point',\n",
    "                                                'NETmin_C':'Min Net Effective Temp',\n",
    "                                                'NETmax_C':'Max Net Effective Temp',\n",
    "                                                'NETmean_C':'Mean Net Effective Temp',\n",
    "                                                'HImin_C':'Min Heat Index',             \n",
    "                                                'HImax_C':'Max Heat Index',             \n",
    "                                                'HImean_C':'Mean Heat Index',           \n",
    "                                                'HXmin_C':'Min Humidex',             \n",
    "                                                'HXmax_C':'Max Humidex',             \n",
    "                                                'HXmean_C':'Mean Humidex',           \n",
    "                                                'WBGTmin_C':'Min WBGT',           \n",
    "                                                'WBGTmax_C':'Max WBGT',          \n",
    "                                                'WBGTmean_C':'Mean WBGT',           \n",
    "                                                'UTCImin_C':'Min UTCI',       \n",
    "                                                'UTCImax_C':'Max UTCI',          \n",
    "                                                'UTCImean_C':'Mean UTCI',})\n",
    "df_all_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FIPS Code-County</th>\n",
       "      <th>Min Ambient Temp</th>\n",
       "      <th>Max Ambient Temp</th>\n",
       "      <th>Mean Ambient Temp</th>\n",
       "      <th>Min Dew Point</th>\n",
       "      <th>Max Dew point</th>\n",
       "      <th>Mean Dew Point</th>\n",
       "      <th>Min Net Effective Temp</th>\n",
       "      <th>Max Net Effective Temp</th>\n",
       "      <th>Mean Net Effective Temp</th>\n",
       "      <th>...</th>\n",
       "      <th>Mean Heat Index</th>\n",
       "      <th>Min Humidex</th>\n",
       "      <th>Max Humidex</th>\n",
       "      <th>Mean Humidex</th>\n",
       "      <th>Min WBGT</th>\n",
       "      <th>Max WBGT</th>\n",
       "      <th>Mean WBGT</th>\n",
       "      <th>Min UTCI</th>\n",
       "      <th>Max UTCI</th>\n",
       "      <th>Mean UTCI</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>48001</td>\n",
       "      <td>17.969999</td>\n",
       "      <td>22.020000</td>\n",
       "      <td>19.469999</td>\n",
       "      <td>16.639999</td>\n",
       "      <td>18.709999</td>\n",
       "      <td>17.549999</td>\n",
       "      <td>9.58</td>\n",
       "      <td>15.810000</td>\n",
       "      <td>12.50</td>\n",
       "      <td>...</td>\n",
       "      <td>19.790001</td>\n",
       "      <td>22.940001</td>\n",
       "      <td>27.920000</td>\n",
       "      <td>25.049999</td>\n",
       "      <td>17.18</td>\n",
       "      <td>21.980000</td>\n",
       "      <td>18.799999</td>\n",
       "      <td>10.64</td>\n",
       "      <td>25.030001</td>\n",
       "      <td>16.680000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>48003</td>\n",
       "      <td>3.730000</td>\n",
       "      <td>17.750000</td>\n",
       "      <td>11.380000</td>\n",
       "      <td>-7.530000</td>\n",
       "      <td>0.110000</td>\n",
       "      <td>-5.020000</td>\n",
       "      <td>-4.42</td>\n",
       "      <td>8.370000</td>\n",
       "      <td>2.41</td>\n",
       "      <td>...</td>\n",
       "      <td>9.600000</td>\n",
       "      <td>0.140000</td>\n",
       "      <td>14.610000</td>\n",
       "      <td>8.190000</td>\n",
       "      <td>0.13</td>\n",
       "      <td>12.890000</td>\n",
       "      <td>6.880000</td>\n",
       "      <td>-15.64</td>\n",
       "      <td>17.870001</td>\n",
       "      <td>2.060000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>48005</td>\n",
       "      <td>17.860001</td>\n",
       "      <td>23.350000</td>\n",
       "      <td>19.870001</td>\n",
       "      <td>16.650000</td>\n",
       "      <td>18.750000</td>\n",
       "      <td>17.700001</td>\n",
       "      <td>10.24</td>\n",
       "      <td>17.209999</td>\n",
       "      <td>13.19</td>\n",
       "      <td>...</td>\n",
       "      <td>20.209999</td>\n",
       "      <td>22.820000</td>\n",
       "      <td>29.020000</td>\n",
       "      <td>25.549999</td>\n",
       "      <td>17.09</td>\n",
       "      <td>22.309999</td>\n",
       "      <td>19.090000</td>\n",
       "      <td>12.56</td>\n",
       "      <td>25.110001</td>\n",
       "      <td>17.629999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>48007</td>\n",
       "      <td>20.200001</td>\n",
       "      <td>24.070000</td>\n",
       "      <td>21.410000</td>\n",
       "      <td>18.219999</td>\n",
       "      <td>18.990000</td>\n",
       "      <td>18.629999</td>\n",
       "      <td>11.46</td>\n",
       "      <td>16.230000</td>\n",
       "      <td>13.01</td>\n",
       "      <td>...</td>\n",
       "      <td>21.809999</td>\n",
       "      <td>26.340000</td>\n",
       "      <td>30.330000</td>\n",
       "      <td>27.750000</td>\n",
       "      <td>19.17</td>\n",
       "      <td>23.400000</td>\n",
       "      <td>20.590000</td>\n",
       "      <td>10.18</td>\n",
       "      <td>24.280001</td>\n",
       "      <td>15.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>48009</td>\n",
       "      <td>10.840000</td>\n",
       "      <td>20.840000</td>\n",
       "      <td>15.860000</td>\n",
       "      <td>-4.590000</td>\n",
       "      <td>10.990000</td>\n",
       "      <td>3.660000</td>\n",
       "      <td>3.67</td>\n",
       "      <td>13.370000</td>\n",
       "      <td>8.46</td>\n",
       "      <td>...</td>\n",
       "      <td>14.780000</td>\n",
       "      <td>10.370000</td>\n",
       "      <td>19.860001</td>\n",
       "      <td>14.980000</td>\n",
       "      <td>8.49</td>\n",
       "      <td>16.740000</td>\n",
       "      <td>12.500000</td>\n",
       "      <td>4.01</td>\n",
       "      <td>25.650000</td>\n",
       "      <td>12.210000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-30</th>\n",
       "      <td>48499</td>\n",
       "      <td>5.990000</td>\n",
       "      <td>16.790001</td>\n",
       "      <td>12.100000</td>\n",
       "      <td>5.670000</td>\n",
       "      <td>16.740000</td>\n",
       "      <td>11.390000</td>\n",
       "      <td>-5.94</td>\n",
       "      <td>12.220000</td>\n",
       "      <td>2.69</td>\n",
       "      <td>...</td>\n",
       "      <td>11.860000</td>\n",
       "      <td>5.530000</td>\n",
       "      <td>21.799999</td>\n",
       "      <td>14.270000</td>\n",
       "      <td>5.50</td>\n",
       "      <td>17.400000</td>\n",
       "      <td>11.640000</td>\n",
       "      <td>-2.94</td>\n",
       "      <td>19.270000</td>\n",
       "      <td>6.780000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-30</th>\n",
       "      <td>48501</td>\n",
       "      <td>0.150000</td>\n",
       "      <td>8.590000</td>\n",
       "      <td>3.610000</td>\n",
       "      <td>-13.660000</td>\n",
       "      <td>1.370000</td>\n",
       "      <td>-7.510000</td>\n",
       "      <td>-14.77</td>\n",
       "      <td>0.190000</td>\n",
       "      <td>-7.73</td>\n",
       "      <td>...</td>\n",
       "      <td>2.730000</td>\n",
       "      <td>-3.760000</td>\n",
       "      <td>6.100000</td>\n",
       "      <td>0.160000</td>\n",
       "      <td>-3.15</td>\n",
       "      <td>4.790000</td>\n",
       "      <td>0.960000</td>\n",
       "      <td>-19.98</td>\n",
       "      <td>-0.520000</td>\n",
       "      <td>-10.680000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-30</th>\n",
       "      <td>48503</td>\n",
       "      <td>4.150000</td>\n",
       "      <td>17.070000</td>\n",
       "      <td>7.140000</td>\n",
       "      <td>-5.090000</td>\n",
       "      <td>14.960000</td>\n",
       "      <td>3.750000</td>\n",
       "      <td>-10.44</td>\n",
       "      <td>9.020000</td>\n",
       "      <td>-5.13</td>\n",
       "      <td>...</td>\n",
       "      <td>6.400000</td>\n",
       "      <td>1.160000</td>\n",
       "      <td>20.930000</td>\n",
       "      <td>6.420000</td>\n",
       "      <td>1.33</td>\n",
       "      <td>15.890000</td>\n",
       "      <td>5.900000</td>\n",
       "      <td>-11.22</td>\n",
       "      <td>13.390000</td>\n",
       "      <td>-5.270000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-30</th>\n",
       "      <td>48505</td>\n",
       "      <td>17.290001</td>\n",
       "      <td>27.870001</td>\n",
       "      <td>22.090000</td>\n",
       "      <td>11.340000</td>\n",
       "      <td>16.190001</td>\n",
       "      <td>14.020000</td>\n",
       "      <td>8.13</td>\n",
       "      <td>21.730000</td>\n",
       "      <td>14.33</td>\n",
       "      <td>...</td>\n",
       "      <td>21.969999</td>\n",
       "      <td>20.129999</td>\n",
       "      <td>30.020000</td>\n",
       "      <td>25.459999</td>\n",
       "      <td>15.21</td>\n",
       "      <td>24.760000</td>\n",
       "      <td>19.440001</td>\n",
       "      <td>6.77</td>\n",
       "      <td>33.860001</td>\n",
       "      <td>17.850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-30</th>\n",
       "      <td>48507</td>\n",
       "      <td>9.880000</td>\n",
       "      <td>23.240000</td>\n",
       "      <td>17.330000</td>\n",
       "      <td>4.830000</td>\n",
       "      <td>15.710000</td>\n",
       "      <td>12.140000</td>\n",
       "      <td>-1.51</td>\n",
       "      <td>17.309999</td>\n",
       "      <td>9.01</td>\n",
       "      <td>...</td>\n",
       "      <td>17.020000</td>\n",
       "      <td>9.770000</td>\n",
       "      <td>25.879999</td>\n",
       "      <td>19.850000</td>\n",
       "      <td>8.36</td>\n",
       "      <td>20.420000</td>\n",
       "      <td>15.380000</td>\n",
       "      <td>-1.89</td>\n",
       "      <td>25.379999</td>\n",
       "      <td>11.410000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1947926 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            FIPS Code-County  Min Ambient Temp  Max Ambient Temp  \\\n",
       "Date                                                               \n",
       "2000-01-02             48001         17.969999         22.020000   \n",
       "2000-01-02             48003          3.730000         17.750000   \n",
       "2000-01-02             48005         17.860001         23.350000   \n",
       "2000-01-02             48007         20.200001         24.070000   \n",
       "2000-01-02             48009         10.840000         20.840000   \n",
       "...                      ...               ...               ...   \n",
       "2020-12-30             48499          5.990000         16.790001   \n",
       "2020-12-30             48501          0.150000          8.590000   \n",
       "2020-12-30             48503          4.150000         17.070000   \n",
       "2020-12-30             48505         17.290001         27.870001   \n",
       "2020-12-30             48507          9.880000         23.240000   \n",
       "\n",
       "            Mean Ambient Temp  Min Dew Point  Max Dew point  Mean Dew Point  \\\n",
       "Date                                                                          \n",
       "2000-01-02          19.469999      16.639999      18.709999       17.549999   \n",
       "2000-01-02          11.380000      -7.530000       0.110000       -5.020000   \n",
       "2000-01-02          19.870001      16.650000      18.750000       17.700001   \n",
       "2000-01-02          21.410000      18.219999      18.990000       18.629999   \n",
       "2000-01-02          15.860000      -4.590000      10.990000        3.660000   \n",
       "...                       ...            ...            ...             ...   \n",
       "2020-12-30          12.100000       5.670000      16.740000       11.390000   \n",
       "2020-12-30           3.610000     -13.660000       1.370000       -7.510000   \n",
       "2020-12-30           7.140000      -5.090000      14.960000        3.750000   \n",
       "2020-12-30          22.090000      11.340000      16.190001       14.020000   \n",
       "2020-12-30          17.330000       4.830000      15.710000       12.140000   \n",
       "\n",
       "            Min Net Effective Temp  Max Net Effective Temp  \\\n",
       "Date                                                         \n",
       "2000-01-02                    9.58               15.810000   \n",
       "2000-01-02                   -4.42                8.370000   \n",
       "2000-01-02                   10.24               17.209999   \n",
       "2000-01-02                   11.46               16.230000   \n",
       "2000-01-02                    3.67               13.370000   \n",
       "...                            ...                     ...   \n",
       "2020-12-30                   -5.94               12.220000   \n",
       "2020-12-30                  -14.77                0.190000   \n",
       "2020-12-30                  -10.44                9.020000   \n",
       "2020-12-30                    8.13               21.730000   \n",
       "2020-12-30                   -1.51               17.309999   \n",
       "\n",
       "            Mean Net Effective Temp  ...  Mean Heat Index  Min Humidex  \\\n",
       "Date                                 ...                                 \n",
       "2000-01-02                    12.50  ...        19.790001    22.940001   \n",
       "2000-01-02                     2.41  ...         9.600000     0.140000   \n",
       "2000-01-02                    13.19  ...        20.209999    22.820000   \n",
       "2000-01-02                    13.01  ...        21.809999    26.340000   \n",
       "2000-01-02                     8.46  ...        14.780000    10.370000   \n",
       "...                             ...  ...              ...          ...   \n",
       "2020-12-30                     2.69  ...        11.860000     5.530000   \n",
       "2020-12-30                    -7.73  ...         2.730000    -3.760000   \n",
       "2020-12-30                    -5.13  ...         6.400000     1.160000   \n",
       "2020-12-30                    14.33  ...        21.969999    20.129999   \n",
       "2020-12-30                     9.01  ...        17.020000     9.770000   \n",
       "\n",
       "            Max Humidex  Mean Humidex  Min WBGT   Max WBGT  Mean WBGT  \\\n",
       "Date                                                                    \n",
       "2000-01-02    27.920000     25.049999     17.18  21.980000  18.799999   \n",
       "2000-01-02    14.610000      8.190000      0.13  12.890000   6.880000   \n",
       "2000-01-02    29.020000     25.549999     17.09  22.309999  19.090000   \n",
       "2000-01-02    30.330000     27.750000     19.17  23.400000  20.590000   \n",
       "2000-01-02    19.860001     14.980000      8.49  16.740000  12.500000   \n",
       "...                 ...           ...       ...        ...        ...   \n",
       "2020-12-30    21.799999     14.270000      5.50  17.400000  11.640000   \n",
       "2020-12-30     6.100000      0.160000     -3.15   4.790000   0.960000   \n",
       "2020-12-30    20.930000      6.420000      1.33  15.890000   5.900000   \n",
       "2020-12-30    30.020000     25.459999     15.21  24.760000  19.440001   \n",
       "2020-12-30    25.879999     19.850000      8.36  20.420000  15.380000   \n",
       "\n",
       "            Min UTCI   Max UTCI  Mean UTCI  \n",
       "Date                                        \n",
       "2000-01-02     10.64  25.030001  16.680000  \n",
       "2000-01-02    -15.64  17.870001   2.060000  \n",
       "2000-01-02     12.56  25.110001  17.629999  \n",
       "2000-01-02     10.18  24.280001  15.300000  \n",
       "2000-01-02      4.01  25.650000  12.210000  \n",
       "...              ...        ...        ...  \n",
       "2020-12-30     -2.94  19.270000   6.780000  \n",
       "2020-12-30    -19.98  -0.520000 -10.680000  \n",
       "2020-12-30    -11.22  13.390000  -5.270000  \n",
       "2020-12-30      6.77  33.860001  17.850000  \n",
       "2020-12-30     -1.89  25.379999  11.410000  \n",
       "\n",
       "[1947926 rows x 22 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Rename columns (TX)\n",
    "\n",
    "tx_filtered_df = tx_filtered_df.rename(columns={\n",
    "                                                'StCoFIPS':'FIPS Code-County',\n",
    "                                                'Tmin_C':'Min Ambient Temp',\n",
    "                                                'Tmax_C':'Max Ambient Temp',\n",
    "                                                'Tmean_C':'Mean Ambient Temp',\n",
    "                                                'TDmin_C':'Min Dew Point',\n",
    "                                                'TDmax_C':'Max Dew point',\n",
    "                                                'TDmean_C':'Mean Dew Point',\n",
    "                                                'NETmin_C':'Min Net Effective Temp',\n",
    "                                                'NETmax_C':'Max Net Effective Temp',\n",
    "                                                'NETmean_C':'Mean Net Effective Temp',\n",
    "                                                'HImin_C':'Min Heat Index',             \n",
    "                                                'HImax_C':'Max Heat Index',             \n",
    "                                                'HImean_C':'Mean Heat Index',           \n",
    "                                                'HXmin_C':'Min Humidex',             \n",
    "                                                'HXmax_C':'Max Humidex',             \n",
    "                                                'HXmean_C':'Mean Humidex',           \n",
    "                                                'WBGTmin_C':'Min WBGT',           \n",
    "                                                'WBGTmax_C':'Max WBGT',          \n",
    "                                                'WBGTmean_C':'Mean WBGT',           \n",
    "                                                'UTCImin_C':'Min UTCI',       \n",
    "                                                'UTCImax_C':'Max UTCI',          \n",
    "                                                'UTCImean_C':'Mean UTCI',})\n",
    "tx_filtered_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FIPS Code-County</th>\n",
       "      <th>Min Ambient Temp</th>\n",
       "      <th>Max Ambient Temp</th>\n",
       "      <th>Mean Ambient Temp</th>\n",
       "      <th>Min Dew Point</th>\n",
       "      <th>Max Dew point</th>\n",
       "      <th>Mean Dew Point</th>\n",
       "      <th>Min Net Effective Temp</th>\n",
       "      <th>Max Net Effective Temp</th>\n",
       "      <th>Mean Net Effective Temp</th>\n",
       "      <th>...</th>\n",
       "      <th>Mean Heat Index</th>\n",
       "      <th>Min Humidex</th>\n",
       "      <th>Max Humidex</th>\n",
       "      <th>Mean Humidex</th>\n",
       "      <th>Min WBGT</th>\n",
       "      <th>Max WBGT</th>\n",
       "      <th>Mean WBGT</th>\n",
       "      <th>Min UTCI</th>\n",
       "      <th>Max UTCI</th>\n",
       "      <th>Mean UTCI</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>26001</td>\n",
       "      <td>-0.93</td>\n",
       "      <td>7.23</td>\n",
       "      <td>2.68</td>\n",
       "      <td>-1.86</td>\n",
       "      <td>6.58</td>\n",
       "      <td>2.28</td>\n",
       "      <td>-16.580000</td>\n",
       "      <td>-5.27</td>\n",
       "      <td>-8.79</td>\n",
       "      <td>...</td>\n",
       "      <td>2.46</td>\n",
       "      <td>-3.51</td>\n",
       "      <td>7.08</td>\n",
       "      <td>1.18</td>\n",
       "      <td>-1.66</td>\n",
       "      <td>6.68</td>\n",
       "      <td>2.24</td>\n",
       "      <td>-14.810000</td>\n",
       "      <td>3.30</td>\n",
       "      <td>-4.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>26003</td>\n",
       "      <td>-4.46</td>\n",
       "      <td>-0.48</td>\n",
       "      <td>-2.41</td>\n",
       "      <td>-6.88</td>\n",
       "      <td>-1.79</td>\n",
       "      <td>-4.12</td>\n",
       "      <td>-21.200001</td>\n",
       "      <td>-14.49</td>\n",
       "      <td>-17.32</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.41</td>\n",
       "      <td>-7.95</td>\n",
       "      <td>-3.05</td>\n",
       "      <td>-5.44</td>\n",
       "      <td>-5.59</td>\n",
       "      <td>-0.74</td>\n",
       "      <td>-3.25</td>\n",
       "      <td>-24.010000</td>\n",
       "      <td>-10.63</td>\n",
       "      <td>-15.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>26005</td>\n",
       "      <td>3.19</td>\n",
       "      <td>11.90</td>\n",
       "      <td>7.77</td>\n",
       "      <td>1.81</td>\n",
       "      <td>9.11</td>\n",
       "      <td>6.22</td>\n",
       "      <td>-8.970000</td>\n",
       "      <td>0.40</td>\n",
       "      <td>-4.05</td>\n",
       "      <td>...</td>\n",
       "      <td>7.13</td>\n",
       "      <td>1.51</td>\n",
       "      <td>12.72</td>\n",
       "      <td>7.54</td>\n",
       "      <td>2.31</td>\n",
       "      <td>11.98</td>\n",
       "      <td>7.24</td>\n",
       "      <td>-6.180000</td>\n",
       "      <td>6.61</td>\n",
       "      <td>-1.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>26007</td>\n",
       "      <td>-2.58</td>\n",
       "      <td>6.13</td>\n",
       "      <td>2.10</td>\n",
       "      <td>-3.91</td>\n",
       "      <td>5.60</td>\n",
       "      <td>1.55</td>\n",
       "      <td>-19.290001</td>\n",
       "      <td>-6.51</td>\n",
       "      <td>-10.37</td>\n",
       "      <td>...</td>\n",
       "      <td>1.96</td>\n",
       "      <td>-5.59</td>\n",
       "      <td>5.62</td>\n",
       "      <td>0.39</td>\n",
       "      <td>-3.36</td>\n",
       "      <td>5.60</td>\n",
       "      <td>1.67</td>\n",
       "      <td>-19.139999</td>\n",
       "      <td>1.79</td>\n",
       "      <td>-6.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>26009</td>\n",
       "      <td>-2.29</td>\n",
       "      <td>6.32</td>\n",
       "      <td>1.85</td>\n",
       "      <td>-3.55</td>\n",
       "      <td>4.84</td>\n",
       "      <td>0.54</td>\n",
       "      <td>-18.520000</td>\n",
       "      <td>-6.21</td>\n",
       "      <td>-11.47</td>\n",
       "      <td>...</td>\n",
       "      <td>1.68</td>\n",
       "      <td>-5.23</td>\n",
       "      <td>5.55</td>\n",
       "      <td>-0.13</td>\n",
       "      <td>-3.06</td>\n",
       "      <td>5.69</td>\n",
       "      <td>1.15</td>\n",
       "      <td>-18.150000</td>\n",
       "      <td>-0.39</td>\n",
       "      <td>-8.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-30</th>\n",
       "      <td>26157</td>\n",
       "      <td>-3.02</td>\n",
       "      <td>3.74</td>\n",
       "      <td>0.04</td>\n",
       "      <td>-8.15</td>\n",
       "      <td>2.65</td>\n",
       "      <td>-2.72</td>\n",
       "      <td>-17.959999</td>\n",
       "      <td>-10.81</td>\n",
       "      <td>-14.76</td>\n",
       "      <td>...</td>\n",
       "      <td>0.04</td>\n",
       "      <td>-6.72</td>\n",
       "      <td>2.28</td>\n",
       "      <td>-2.66</td>\n",
       "      <td>-4.70</td>\n",
       "      <td>3.42</td>\n",
       "      <td>-1.00</td>\n",
       "      <td>-20.600000</td>\n",
       "      <td>-8.60</td>\n",
       "      <td>-15.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-30</th>\n",
       "      <td>26159</td>\n",
       "      <td>-1.54</td>\n",
       "      <td>3.65</td>\n",
       "      <td>0.49</td>\n",
       "      <td>-6.44</td>\n",
       "      <td>3.41</td>\n",
       "      <td>-1.53</td>\n",
       "      <td>-17.420000</td>\n",
       "      <td>-10.88</td>\n",
       "      <td>-14.38</td>\n",
       "      <td>...</td>\n",
       "      <td>0.49</td>\n",
       "      <td>-4.85</td>\n",
       "      <td>2.42</td>\n",
       "      <td>-1.96</td>\n",
       "      <td>-3.06</td>\n",
       "      <td>3.48</td>\n",
       "      <td>-0.30</td>\n",
       "      <td>-17.920000</td>\n",
       "      <td>-7.76</td>\n",
       "      <td>-13.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-30</th>\n",
       "      <td>26161</td>\n",
       "      <td>-2.24</td>\n",
       "      <td>5.97</td>\n",
       "      <td>1.12</td>\n",
       "      <td>-8.31</td>\n",
       "      <td>5.24</td>\n",
       "      <td>-1.72</td>\n",
       "      <td>-15.520000</td>\n",
       "      <td>-8.20</td>\n",
       "      <td>-12.58</td>\n",
       "      <td>...</td>\n",
       "      <td>0.96</td>\n",
       "      <td>-5.72</td>\n",
       "      <td>5.34</td>\n",
       "      <td>-1.30</td>\n",
       "      <td>-3.82</td>\n",
       "      <td>5.64</td>\n",
       "      <td>0.03</td>\n",
       "      <td>-17.139999</td>\n",
       "      <td>-6.12</td>\n",
       "      <td>-12.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-30</th>\n",
       "      <td>26163</td>\n",
       "      <td>-1.41</td>\n",
       "      <td>6.36</td>\n",
       "      <td>1.75</td>\n",
       "      <td>-6.98</td>\n",
       "      <td>5.55</td>\n",
       "      <td>-1.21</td>\n",
       "      <td>-15.580000</td>\n",
       "      <td>-8.18</td>\n",
       "      <td>-12.62</td>\n",
       "      <td>...</td>\n",
       "      <td>1.56</td>\n",
       "      <td>-4.79</td>\n",
       "      <td>5.83</td>\n",
       "      <td>-0.57</td>\n",
       "      <td>-3.03</td>\n",
       "      <td>5.99</td>\n",
       "      <td>0.62</td>\n",
       "      <td>-18.570000</td>\n",
       "      <td>-7.83</td>\n",
       "      <td>-13.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-30</th>\n",
       "      <td>26165</td>\n",
       "      <td>-4.62</td>\n",
       "      <td>0.93</td>\n",
       "      <td>-2.31</td>\n",
       "      <td>-8.71</td>\n",
       "      <td>-0.24</td>\n",
       "      <td>-4.92</td>\n",
       "      <td>-19.549999</td>\n",
       "      <td>-11.92</td>\n",
       "      <td>-16.23</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.31</td>\n",
       "      <td>-8.39</td>\n",
       "      <td>-1.40</td>\n",
       "      <td>-5.47</td>\n",
       "      <td>-6.08</td>\n",
       "      <td>0.74</td>\n",
       "      <td>-3.23</td>\n",
       "      <td>-18.610001</td>\n",
       "      <td>-6.10</td>\n",
       "      <td>-14.17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>636527 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            FIPS Code-County  Min Ambient Temp  Max Ambient Temp  \\\n",
       "Date                                                               \n",
       "2000-01-02             26001             -0.93              7.23   \n",
       "2000-01-02             26003             -4.46             -0.48   \n",
       "2000-01-02             26005              3.19             11.90   \n",
       "2000-01-02             26007             -2.58              6.13   \n",
       "2000-01-02             26009             -2.29              6.32   \n",
       "...                      ...               ...               ...   \n",
       "2020-12-30             26157             -3.02              3.74   \n",
       "2020-12-30             26159             -1.54              3.65   \n",
       "2020-12-30             26161             -2.24              5.97   \n",
       "2020-12-30             26163             -1.41              6.36   \n",
       "2020-12-30             26165             -4.62              0.93   \n",
       "\n",
       "            Mean Ambient Temp  Min Dew Point  Max Dew point  Mean Dew Point  \\\n",
       "Date                                                                          \n",
       "2000-01-02               2.68          -1.86           6.58            2.28   \n",
       "2000-01-02              -2.41          -6.88          -1.79           -4.12   \n",
       "2000-01-02               7.77           1.81           9.11            6.22   \n",
       "2000-01-02               2.10          -3.91           5.60            1.55   \n",
       "2000-01-02               1.85          -3.55           4.84            0.54   \n",
       "...                       ...            ...            ...             ...   \n",
       "2020-12-30               0.04          -8.15           2.65           -2.72   \n",
       "2020-12-30               0.49          -6.44           3.41           -1.53   \n",
       "2020-12-30               1.12          -8.31           5.24           -1.72   \n",
       "2020-12-30               1.75          -6.98           5.55           -1.21   \n",
       "2020-12-30              -2.31          -8.71          -0.24           -4.92   \n",
       "\n",
       "            Min Net Effective Temp  Max Net Effective Temp  \\\n",
       "Date                                                         \n",
       "2000-01-02              -16.580000                   -5.27   \n",
       "2000-01-02              -21.200001                  -14.49   \n",
       "2000-01-02               -8.970000                    0.40   \n",
       "2000-01-02              -19.290001                   -6.51   \n",
       "2000-01-02              -18.520000                   -6.21   \n",
       "...                            ...                     ...   \n",
       "2020-12-30              -17.959999                  -10.81   \n",
       "2020-12-30              -17.420000                  -10.88   \n",
       "2020-12-30              -15.520000                   -8.20   \n",
       "2020-12-30              -15.580000                   -8.18   \n",
       "2020-12-30              -19.549999                  -11.92   \n",
       "\n",
       "            Mean Net Effective Temp  ...  Mean Heat Index  Min Humidex  \\\n",
       "Date                                 ...                                 \n",
       "2000-01-02                    -8.79  ...             2.46        -3.51   \n",
       "2000-01-02                   -17.32  ...            -2.41        -7.95   \n",
       "2000-01-02                    -4.05  ...             7.13         1.51   \n",
       "2000-01-02                   -10.37  ...             1.96        -5.59   \n",
       "2000-01-02                   -11.47  ...             1.68        -5.23   \n",
       "...                             ...  ...              ...          ...   \n",
       "2020-12-30                   -14.76  ...             0.04        -6.72   \n",
       "2020-12-30                   -14.38  ...             0.49        -4.85   \n",
       "2020-12-30                   -12.58  ...             0.96        -5.72   \n",
       "2020-12-30                   -12.62  ...             1.56        -4.79   \n",
       "2020-12-30                   -16.23  ...            -2.31        -8.39   \n",
       "\n",
       "            Max Humidex  Mean Humidex  Min WBGT  Max WBGT  Mean WBGT  \\\n",
       "Date                                                                   \n",
       "2000-01-02         7.08          1.18     -1.66      6.68       2.24   \n",
       "2000-01-02        -3.05         -5.44     -5.59     -0.74      -3.25   \n",
       "2000-01-02        12.72          7.54      2.31     11.98       7.24   \n",
       "2000-01-02         5.62          0.39     -3.36      5.60       1.67   \n",
       "2000-01-02         5.55         -0.13     -3.06      5.69       1.15   \n",
       "...                 ...           ...       ...       ...        ...   \n",
       "2020-12-30         2.28         -2.66     -4.70      3.42      -1.00   \n",
       "2020-12-30         2.42         -1.96     -3.06      3.48      -0.30   \n",
       "2020-12-30         5.34         -1.30     -3.82      5.64       0.03   \n",
       "2020-12-30         5.83         -0.57     -3.03      5.99       0.62   \n",
       "2020-12-30        -1.40         -5.47     -6.08      0.74      -3.23   \n",
       "\n",
       "             Min UTCI  Max UTCI  Mean UTCI  \n",
       "Date                                        \n",
       "2000-01-02 -14.810000      3.30      -4.10  \n",
       "2000-01-02 -24.010000    -10.63     -15.89  \n",
       "2000-01-02  -6.180000      6.61      -1.32  \n",
       "2000-01-02 -19.139999      1.79      -6.32  \n",
       "2000-01-02 -18.150000     -0.39      -8.58  \n",
       "...               ...       ...        ...  \n",
       "2020-12-30 -20.600000     -8.60     -15.29  \n",
       "2020-12-30 -17.920000     -7.76     -13.67  \n",
       "2020-12-30 -17.139999     -6.12     -12.02  \n",
       "2020-12-30 -18.570000     -7.83     -13.65  \n",
       "2020-12-30 -18.610001     -6.10     -14.17  \n",
       "\n",
       "[636527 rows x 22 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Rename columns (MI)\n",
    "\n",
    "mi_filtered_df = mi_filtered_df.rename(columns={\n",
    "                                                'StCoFIPS':'FIPS Code-County',\n",
    "                                                'Tmin_C':'Min Ambient Temp',\n",
    "                                                'Tmax_C':'Max Ambient Temp',\n",
    "                                                'Tmean_C':'Mean Ambient Temp',\n",
    "                                                'TDmin_C':'Min Dew Point',\n",
    "                                                'TDmax_C':'Max Dew point',\n",
    "                                                'TDmean_C':'Mean Dew Point',\n",
    "                                                'NETmin_C':'Min Net Effective Temp',\n",
    "                                                'NETmax_C':'Max Net Effective Temp',\n",
    "                                                'NETmean_C':'Mean Net Effective Temp',\n",
    "                                                'HImin_C':'Min Heat Index',             \n",
    "                                                'HImax_C':'Max Heat Index',             \n",
    "                                                'HImean_C':'Mean Heat Index',           \n",
    "                                                'HXmin_C':'Min Humidex',             \n",
    "                                                'HXmax_C':'Max Humidex',             \n",
    "                                                'HXmean_C':'Mean Humidex',           \n",
    "                                                'WBGTmin_C':'Min WBGT',           \n",
    "                                                'WBGTmax_C':'Max WBGT',          \n",
    "                                                'WBGTmean_C':'Mean WBGT',           \n",
    "                                                'UTCImin_C':'Min UTCI',       \n",
    "                                                'UTCImax_C':'Max UTCI',          \n",
    "                                                'UTCImean_C':'Mean UTCI',})\n",
    "mi_filtered_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Convert Celsius to Fahrenheit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Convert Data from Celsius to Fahrenheit\n",
    "\n",
    "# # # Define conversion functions\n",
    "# def celsius_to_fahrenheit(celsius):\n",
    "#     return celsius * 9/5 + 32\n",
    "\n",
    "# # # Apply conversion\n",
    "# df_all_1= df_all_1.map(celsius_to_fahrenheit)\n",
    "# df_all_1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/xd/jl_0pvqx5295gyzxfw09l8b00000gn/T/ipykernel_60204/3496857274.py:10: FutureWarning: DataFrame.applymap has been deprecated. Use DataFrame.map instead.\n",
      "  tx_filtered_df[columns_to_convert] = tx_filtered_df[columns_to_convert].applymap(celsius_to_fahrenheit)\n"
     ]
    },
    {
     "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",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FIPS Code-County</th>\n",
       "      <th>Min Ambient Temp</th>\n",
       "      <th>Max Ambient Temp</th>\n",
       "      <th>Mean Ambient Temp</th>\n",
       "      <th>Min Dew Point</th>\n",
       "      <th>Max Dew point</th>\n",
       "      <th>Mean Dew Point</th>\n",
       "      <th>Min Net Effective Temp</th>\n",
       "      <th>Max Net Effective Temp</th>\n",
       "      <th>Mean Net Effective Temp</th>\n",
       "      <th>...</th>\n",
       "      <th>Mean Heat Index</th>\n",
       "      <th>Min Humidex</th>\n",
       "      <th>Max Humidex</th>\n",
       "      <th>Mean Humidex</th>\n",
       "      <th>Min WBGT</th>\n",
       "      <th>Max WBGT</th>\n",
       "      <th>Mean WBGT</th>\n",
       "      <th>Min UTCI</th>\n",
       "      <th>Max UTCI</th>\n",
       "      <th>Mean UTCI</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>48001</td>\n",
       "      <td>64.345999</td>\n",
       "      <td>71.636001</td>\n",
       "      <td>67.045999</td>\n",
       "      <td>61.951999</td>\n",
       "      <td>65.677998</td>\n",
       "      <td>63.589999</td>\n",
       "      <td>49.244</td>\n",
       "      <td>60.458001</td>\n",
       "      <td>54.500000</td>\n",
       "      <td>...</td>\n",
       "      <td>67.622002</td>\n",
       "      <td>73.292001</td>\n",
       "      <td>82.256000</td>\n",
       "      <td>77.089999</td>\n",
       "      <td>62.924001</td>\n",
       "      <td>71.563999</td>\n",
       "      <td>65.839999</td>\n",
       "      <td>51.152001</td>\n",
       "      <td>77.054001</td>\n",
       "      <td>62.024001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>48003</td>\n",
       "      <td>38.714000</td>\n",
       "      <td>63.950000</td>\n",
       "      <td>52.484000</td>\n",
       "      <td>18.446000</td>\n",
       "      <td>32.198000</td>\n",
       "      <td>22.964000</td>\n",
       "      <td>24.044</td>\n",
       "      <td>47.066000</td>\n",
       "      <td>36.338000</td>\n",
       "      <td>...</td>\n",
       "      <td>49.280001</td>\n",
       "      <td>32.252000</td>\n",
       "      <td>58.297999</td>\n",
       "      <td>46.741999</td>\n",
       "      <td>32.234000</td>\n",
       "      <td>55.202001</td>\n",
       "      <td>44.384000</td>\n",
       "      <td>3.847999</td>\n",
       "      <td>64.166002</td>\n",
       "      <td>35.708000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>48005</td>\n",
       "      <td>64.148001</td>\n",
       "      <td>74.030001</td>\n",
       "      <td>67.766002</td>\n",
       "      <td>61.969999</td>\n",
       "      <td>65.750000</td>\n",
       "      <td>63.860001</td>\n",
       "      <td>50.432</td>\n",
       "      <td>62.977998</td>\n",
       "      <td>55.741999</td>\n",
       "      <td>...</td>\n",
       "      <td>68.377998</td>\n",
       "      <td>73.075999</td>\n",
       "      <td>84.236001</td>\n",
       "      <td>77.989999</td>\n",
       "      <td>62.762000</td>\n",
       "      <td>72.157999</td>\n",
       "      <td>66.362000</td>\n",
       "      <td>54.608001</td>\n",
       "      <td>77.198001</td>\n",
       "      <td>63.733998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>48007</td>\n",
       "      <td>68.360001</td>\n",
       "      <td>75.325999</td>\n",
       "      <td>70.538000</td>\n",
       "      <td>64.795999</td>\n",
       "      <td>66.182000</td>\n",
       "      <td>65.533998</td>\n",
       "      <td>52.628</td>\n",
       "      <td>61.213999</td>\n",
       "      <td>55.418000</td>\n",
       "      <td>...</td>\n",
       "      <td>71.257999</td>\n",
       "      <td>79.412000</td>\n",
       "      <td>86.594000</td>\n",
       "      <td>81.950000</td>\n",
       "      <td>66.506000</td>\n",
       "      <td>74.119999</td>\n",
       "      <td>69.062000</td>\n",
       "      <td>50.324001</td>\n",
       "      <td>75.704001</td>\n",
       "      <td>59.540000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>48009</td>\n",
       "      <td>51.512000</td>\n",
       "      <td>69.512000</td>\n",
       "      <td>60.547999</td>\n",
       "      <td>23.738000</td>\n",
       "      <td>51.782000</td>\n",
       "      <td>38.588000</td>\n",
       "      <td>38.606</td>\n",
       "      <td>56.066000</td>\n",
       "      <td>47.228000</td>\n",
       "      <td>...</td>\n",
       "      <td>58.604000</td>\n",
       "      <td>50.666000</td>\n",
       "      <td>67.748001</td>\n",
       "      <td>58.963999</td>\n",
       "      <td>47.282000</td>\n",
       "      <td>62.132000</td>\n",
       "      <td>54.500000</td>\n",
       "      <td>39.218000</td>\n",
       "      <td>78.169999</td>\n",
       "      <td>53.978000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            FIPS Code-County  Min Ambient Temp  Max Ambient Temp  \\\n",
       "Date                                                               \n",
       "2000-01-02             48001         64.345999         71.636001   \n",
       "2000-01-02             48003         38.714000         63.950000   \n",
       "2000-01-02             48005         64.148001         74.030001   \n",
       "2000-01-02             48007         68.360001         75.325999   \n",
       "2000-01-02             48009         51.512000         69.512000   \n",
       "\n",
       "            Mean Ambient Temp  Min Dew Point  Max Dew point  Mean Dew Point  \\\n",
       "Date                                                                          \n",
       "2000-01-02          67.045999      61.951999      65.677998       63.589999   \n",
       "2000-01-02          52.484000      18.446000      32.198000       22.964000   \n",
       "2000-01-02          67.766002      61.969999      65.750000       63.860001   \n",
       "2000-01-02          70.538000      64.795999      66.182000       65.533998   \n",
       "2000-01-02          60.547999      23.738000      51.782000       38.588000   \n",
       "\n",
       "            Min Net Effective Temp  Max Net Effective Temp  \\\n",
       "Date                                                         \n",
       "2000-01-02                  49.244               60.458001   \n",
       "2000-01-02                  24.044               47.066000   \n",
       "2000-01-02                  50.432               62.977998   \n",
       "2000-01-02                  52.628               61.213999   \n",
       "2000-01-02                  38.606               56.066000   \n",
       "\n",
       "            Mean Net Effective Temp  ...  Mean Heat Index  Min Humidex  \\\n",
       "Date                                 ...                                 \n",
       "2000-01-02                54.500000  ...        67.622002    73.292001   \n",
       "2000-01-02                36.338000  ...        49.280001    32.252000   \n",
       "2000-01-02                55.741999  ...        68.377998    73.075999   \n",
       "2000-01-02                55.418000  ...        71.257999    79.412000   \n",
       "2000-01-02                47.228000  ...        58.604000    50.666000   \n",
       "\n",
       "            Max Humidex  Mean Humidex   Min WBGT   Max WBGT  Mean WBGT  \\\n",
       "Date                                                                     \n",
       "2000-01-02    82.256000     77.089999  62.924001  71.563999  65.839999   \n",
       "2000-01-02    58.297999     46.741999  32.234000  55.202001  44.384000   \n",
       "2000-01-02    84.236001     77.989999  62.762000  72.157999  66.362000   \n",
       "2000-01-02    86.594000     81.950000  66.506000  74.119999  69.062000   \n",
       "2000-01-02    67.748001     58.963999  47.282000  62.132000  54.500000   \n",
       "\n",
       "             Min UTCI   Max UTCI  Mean UTCI  \n",
       "Date                                         \n",
       "2000-01-02  51.152001  77.054001  62.024001  \n",
       "2000-01-02   3.847999  64.166002  35.708000  \n",
       "2000-01-02  54.608001  77.198001  63.733998  \n",
       "2000-01-02  50.324001  75.704001  59.540000  \n",
       "2000-01-02  39.218000  78.169999  53.978000  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Convert Data from Celsius to Fahrenheit (TX)\n",
    "\n",
    "# Define conversion function\n",
    "def celsius_to_fahrenheit(celsius):\n",
    "    return celsius * 9/5 + 32\n",
    "\n",
    "# Apply conversion to all columns except \"FIPS Code-County\"\n",
    "columns_to_convert = tx_filtered_df.columns.difference(['FIPS Code-County'])  # Exclude the specific column\n",
    "\n",
    "tx_filtered_df[columns_to_convert] = tx_filtered_df[columns_to_convert].applymap(celsius_to_fahrenheit)\n",
    "\n",
    "# Display the head of the updated DataFrame\n",
    "tx_filtered_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/xd/jl_0pvqx5295gyzxfw09l8b00000gn/T/ipykernel_60204/2794079106.py:10: FutureWarning: DataFrame.applymap has been deprecated. Use DataFrame.map instead.\n",
      "  mi_filtered_df[columns_to_convert] = mi_filtered_df[columns_to_convert].applymap(celsius_to_fahrenheit)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FIPS Code-County</th>\n",
       "      <th>Min Ambient Temp</th>\n",
       "      <th>Max Ambient Temp</th>\n",
       "      <th>Mean Ambient Temp</th>\n",
       "      <th>Min Dew Point</th>\n",
       "      <th>Max Dew point</th>\n",
       "      <th>Mean Dew Point</th>\n",
       "      <th>Min Net Effective Temp</th>\n",
       "      <th>Max Net Effective Temp</th>\n",
       "      <th>Mean Net Effective Temp</th>\n",
       "      <th>...</th>\n",
       "      <th>Mean Heat Index</th>\n",
       "      <th>Min Humidex</th>\n",
       "      <th>Max Humidex</th>\n",
       "      <th>Mean Humidex</th>\n",
       "      <th>Min WBGT</th>\n",
       "      <th>Max WBGT</th>\n",
       "      <th>Mean WBGT</th>\n",
       "      <th>Min UTCI</th>\n",
       "      <th>Max UTCI</th>\n",
       "      <th>Mean UTCI</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>26001</td>\n",
       "      <td>30.326</td>\n",
       "      <td>45.014000</td>\n",
       "      <td>36.824</td>\n",
       "      <td>28.652</td>\n",
       "      <td>43.844000</td>\n",
       "      <td>36.104</td>\n",
       "      <td>2.156000</td>\n",
       "      <td>22.514</td>\n",
       "      <td>16.178000</td>\n",
       "      <td>...</td>\n",
       "      <td>36.428</td>\n",
       "      <td>25.682</td>\n",
       "      <td>44.744</td>\n",
       "      <td>34.124</td>\n",
       "      <td>29.012</td>\n",
       "      <td>44.024000</td>\n",
       "      <td>36.032</td>\n",
       "      <td>5.341999</td>\n",
       "      <td>37.940</td>\n",
       "      <td>24.620000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>26003</td>\n",
       "      <td>23.972</td>\n",
       "      <td>31.136000</td>\n",
       "      <td>27.662</td>\n",
       "      <td>19.616</td>\n",
       "      <td>28.778000</td>\n",
       "      <td>24.584</td>\n",
       "      <td>-6.160001</td>\n",
       "      <td>5.918</td>\n",
       "      <td>0.824001</td>\n",
       "      <td>...</td>\n",
       "      <td>27.662</td>\n",
       "      <td>17.690</td>\n",
       "      <td>26.510</td>\n",
       "      <td>22.208</td>\n",
       "      <td>21.938</td>\n",
       "      <td>30.668000</td>\n",
       "      <td>26.150</td>\n",
       "      <td>-11.218000</td>\n",
       "      <td>12.866</td>\n",
       "      <td>3.397999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>26005</td>\n",
       "      <td>37.742</td>\n",
       "      <td>53.419999</td>\n",
       "      <td>45.986</td>\n",
       "      <td>35.258</td>\n",
       "      <td>48.397999</td>\n",
       "      <td>43.196</td>\n",
       "      <td>15.854000</td>\n",
       "      <td>32.720</td>\n",
       "      <td>24.710000</td>\n",
       "      <td>...</td>\n",
       "      <td>44.834</td>\n",
       "      <td>34.718</td>\n",
       "      <td>54.896</td>\n",
       "      <td>45.572</td>\n",
       "      <td>36.158</td>\n",
       "      <td>53.563999</td>\n",
       "      <td>45.032</td>\n",
       "      <td>20.876000</td>\n",
       "      <td>43.898</td>\n",
       "      <td>29.624000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>26007</td>\n",
       "      <td>27.356</td>\n",
       "      <td>43.034000</td>\n",
       "      <td>35.780</td>\n",
       "      <td>24.962</td>\n",
       "      <td>42.080000</td>\n",
       "      <td>34.790</td>\n",
       "      <td>-2.722002</td>\n",
       "      <td>20.282</td>\n",
       "      <td>13.334000</td>\n",
       "      <td>...</td>\n",
       "      <td>35.528</td>\n",
       "      <td>21.938</td>\n",
       "      <td>42.116</td>\n",
       "      <td>32.702</td>\n",
       "      <td>25.952</td>\n",
       "      <td>42.080000</td>\n",
       "      <td>35.006</td>\n",
       "      <td>-2.451999</td>\n",
       "      <td>35.222</td>\n",
       "      <td>20.624000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>26009</td>\n",
       "      <td>27.878</td>\n",
       "      <td>43.376000</td>\n",
       "      <td>35.330</td>\n",
       "      <td>25.610</td>\n",
       "      <td>40.712000</td>\n",
       "      <td>32.972</td>\n",
       "      <td>-1.336001</td>\n",
       "      <td>20.822</td>\n",
       "      <td>11.354000</td>\n",
       "      <td>...</td>\n",
       "      <td>35.024</td>\n",
       "      <td>22.586</td>\n",
       "      <td>41.990</td>\n",
       "      <td>31.766</td>\n",
       "      <td>26.492</td>\n",
       "      <td>42.242000</td>\n",
       "      <td>34.070</td>\n",
       "      <td>-0.669999</td>\n",
       "      <td>31.298</td>\n",
       "      <td>16.556000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            FIPS Code-County  Min Ambient Temp  Max Ambient Temp  \\\n",
       "Date                                                               \n",
       "2000-01-02             26001            30.326         45.014000   \n",
       "2000-01-02             26003            23.972         31.136000   \n",
       "2000-01-02             26005            37.742         53.419999   \n",
       "2000-01-02             26007            27.356         43.034000   \n",
       "2000-01-02             26009            27.878         43.376000   \n",
       "\n",
       "            Mean Ambient Temp  Min Dew Point  Max Dew point  Mean Dew Point  \\\n",
       "Date                                                                          \n",
       "2000-01-02             36.824         28.652      43.844000          36.104   \n",
       "2000-01-02             27.662         19.616      28.778000          24.584   \n",
       "2000-01-02             45.986         35.258      48.397999          43.196   \n",
       "2000-01-02             35.780         24.962      42.080000          34.790   \n",
       "2000-01-02             35.330         25.610      40.712000          32.972   \n",
       "\n",
       "            Min Net Effective Temp  Max Net Effective Temp  \\\n",
       "Date                                                         \n",
       "2000-01-02                2.156000                  22.514   \n",
       "2000-01-02               -6.160001                   5.918   \n",
       "2000-01-02               15.854000                  32.720   \n",
       "2000-01-02               -2.722002                  20.282   \n",
       "2000-01-02               -1.336001                  20.822   \n",
       "\n",
       "            Mean Net Effective Temp  ...  Mean Heat Index  Min Humidex  \\\n",
       "Date                                 ...                                 \n",
       "2000-01-02                16.178000  ...           36.428       25.682   \n",
       "2000-01-02                 0.824001  ...           27.662       17.690   \n",
       "2000-01-02                24.710000  ...           44.834       34.718   \n",
       "2000-01-02                13.334000  ...           35.528       21.938   \n",
       "2000-01-02                11.354000  ...           35.024       22.586   \n",
       "\n",
       "            Max Humidex  Mean Humidex  Min WBGT   Max WBGT  Mean WBGT  \\\n",
       "Date                                                                    \n",
       "2000-01-02       44.744        34.124    29.012  44.024000     36.032   \n",
       "2000-01-02       26.510        22.208    21.938  30.668000     26.150   \n",
       "2000-01-02       54.896        45.572    36.158  53.563999     45.032   \n",
       "2000-01-02       42.116        32.702    25.952  42.080000     35.006   \n",
       "2000-01-02       41.990        31.766    26.492  42.242000     34.070   \n",
       "\n",
       "             Min UTCI  Max UTCI  Mean UTCI  \n",
       "Date                                        \n",
       "2000-01-02   5.341999    37.940  24.620000  \n",
       "2000-01-02 -11.218000    12.866   3.397999  \n",
       "2000-01-02  20.876000    43.898  29.624000  \n",
       "2000-01-02  -2.451999    35.222  20.624000  \n",
       "2000-01-02  -0.669999    31.298  16.556000  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Convert Data from Celsius to Fahrenheit (MI)\n",
    "\n",
    "# Define conversion function\n",
    "def celsius_to_fahrenheit(celsius):\n",
    "    return celsius * 9/5 + 32\n",
    "\n",
    "# Apply conversion to all columns except \"FIPS Code-County\"\n",
    "columns_to_convert = tx_filtered_df.columns.difference(['FIPS Code-County'])  # Exclude the specific column\n",
    "\n",
    "mi_filtered_df[columns_to_convert] = mi_filtered_df[columns_to_convert].applymap(celsius_to_fahrenheit)\n",
    "\n",
    "# Display the head of the updated DataFrame\n",
    "mi_filtered_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Export to csv "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# #Export to csv  (ALL)\n",
    "\n",
    "df_all_1.to_csv('all-cleaned.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "# #Export to csv (TX)\n",
    "\n",
    "tx_filtered_df.to_csv('tx-cleaned.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# #Export to csv (MI)\n",
    "\n",
    "mi_filtered_df.to_csv('mi-cleaned.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Embedding layer for NN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import tensorflow as tf\n",
    "# from tensorflow.keras.models import Sequential\n",
    "# from tensorflow.keras.layers import Embedding, Dense, LSTM\n",
    "\n",
    "# # Assuming you have a dataset with FIPS codes (as integers) and other features\n",
    "# num_counties = df['StCoFIPS'].nunique()  # Number of unique counties (FIPS codes)\n",
    "# embedding_size = 16  # You can choose the embedding dimension size based on your data\n",
    "\n",
    "# model = Sequential([\n",
    "#     Embedding(input_dim=num_counties, output_dim=embedding_size, input_length=1),\n",
    "#     LSTM(64, return_sequences=False),\n",
    "#     Dense(32, activation='relu'),\n",
    "#     Dense(1)  # For regression, predicting temperature or DTR\n",
    "# ])\n",
    "\n",
    "# model.compile(optimizer='adam', loss='mse')\n",
    "# model.summary()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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