{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os\n",
    "\n",
    "from helpers import (\n",
    "    get_data_path_for_config,\n",
    "    get_combined_df,\n",
    "    save_final_df_as_jsonl,\n",
    "    handle_slug_column_mappings,\n",
    "    set_home_type,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "CONFIG_NAME = \"for_sale_listings\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "processing Metro_new_pending_uc_sfrcondo_sm_month.csv\n",
      "processing Metro_invt_fs_uc_sfrcondo_week.csv\n",
      "processing Metro_mlp_uc_sfrcondo_week.csv\n",
      "processing Metro_invt_fs_uc_sfr_month.csv\n",
      "processing Metro_mlp_uc_sfr_sm_month.csv\n",
      "processing Metro_new_pending_uc_sfrcondo_month.csv\n",
      "processing Metro_mlp_uc_sfrcondo_sm_week.csv\n",
      "processing Metro_invt_fs_uc_sfrcondo_month.csv\n",
      "processing Metro_mlp_uc_sfr_sm_week.csv\n",
      "processing Metro_mlp_uc_sfrcondo_month.csv\n",
      "processing Metro_new_pending_uc_sfrcondo_sm_week.csv\n",
      "processing Metro_invt_fs_uc_sfr_sm_week.csv\n",
      "processing Metro_invt_fs_uc_sfr_sm_month.csv\n",
      "processing Metro_mlp_uc_sfr_month.csv\n",
      "processing Metro_new_listings_uc_sfrcondo_week.csv\n",
      "processing Metro_mlp_uc_sfrcondo_sm_month.csv\n",
      "processing Metro_invt_fs_uc_sfrcondo_sm_week.csv\n",
      "processing Metro_new_listings_uc_sfrcondo_sm_week.csv\n",
      "processing Metro_new_listings_uc_sfrcondo_month.csv\n",
      "processing Metro_new_pending_uc_sfrcondo_week.csv\n",
      "processing Metro_invt_fs_uc_sfr_week.csv\n",
      "processing Metro_new_listings_uc_sfrcondo_sm_month.csv\n",
      "processing Metro_mlp_uc_sfr_week.csv\n",
      "processing Metro_invt_fs_uc_sfrcondo_sm_month.csv\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RegionID</th>\n",
       "      <th>SizeRank</th>\n",
       "      <th>RegionName</th>\n",
       "      <th>RegionType</th>\n",
       "      <th>StateName</th>\n",
       "      <th>Home Type</th>\n",
       "      <th>Date</th>\n",
       "      <th>Median Listing Price</th>\n",
       "      <th>Median Listing Price (Smoothed)</th>\n",
       "      <th>New Pending (Smoothed)</th>\n",
       "      <th>New Listings</th>\n",
       "      <th>New Listings (Smoothed)</th>\n",
       "      <th>New Pending</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>102001</td>\n",
       "      <td>0</td>\n",
       "      <td>United States</td>\n",
       "      <td>country</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SFR</td>\n",
       "      <td>2018-01-13</td>\n",
       "      <td>259000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>102001</td>\n",
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       "      <td>2018-01-20</td>\n",
       "      <td>259900.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>102001</td>\n",
       "      <td>0</td>\n",
       "      <td>United States</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>SFR</td>\n",
       "      <td>2018-01-27</td>\n",
       "      <td>259900.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>102001</td>\n",
       "      <td>0</td>\n",
       "      <td>United States</td>\n",
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       "      <td>SFR</td>\n",
       "      <td>2018-02-03</td>\n",
       "      <td>260000.0</td>\n",
       "      <td>259700.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>102001</td>\n",
       "      <td>0</td>\n",
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       "      <td>SFR</td>\n",
       "      <td>2018-02-10</td>\n",
       "      <td>264900.0</td>\n",
       "      <td>261175.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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",
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       "      <th>578648</th>\n",
       "      <td>845172</td>\n",
       "      <td>769</td>\n",
       "      <td>Winfield, KS</td>\n",
       "      <td>msa</td>\n",
       "      <td>KS</td>\n",
       "      <td>all homes</td>\n",
       "      <td>2023-12-09</td>\n",
       "      <td>134950.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>578649</th>\n",
       "      <td>845172</td>\n",
       "      <td>769</td>\n",
       "      <td>Winfield, KS</td>\n",
       "      <td>msa</td>\n",
       "      <td>KS</td>\n",
       "      <td>all homes</td>\n",
       "      <td>2023-12-16</td>\n",
       "      <td>120000.0</td>\n",
       "      <td>133938.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>845172</td>\n",
       "      <td>769</td>\n",
       "      <td>Winfield, KS</td>\n",
       "      <td>msa</td>\n",
       "      <td>KS</td>\n",
       "      <td>all homes</td>\n",
       "      <td>2023-12-23</td>\n",
       "      <td>111000.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <th>578651</th>\n",
       "      <td>845172</td>\n",
       "      <td>769</td>\n",
       "      <td>Winfield, KS</td>\n",
       "      <td>msa</td>\n",
       "      <td>KS</td>\n",
       "      <td>all homes</td>\n",
       "      <td>2023-12-30</td>\n",
       "      <td>126950.0</td>\n",
       "      <td>123225.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>578652</th>\n",
       "      <td>845172</td>\n",
       "      <td>769</td>\n",
       "      <td>Winfield, KS</td>\n",
       "      <td>msa</td>\n",
       "      <td>KS</td>\n",
       "      <td>all homes</td>\n",
       "      <td>2024-01-06</td>\n",
       "      <td>128000.0</td>\n",
       "      <td>121488.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>578653 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        RegionID  SizeRank     RegionName RegionType StateName  Home Type  \\\n",
       "0         102001         0  United States    country       NaN        SFR   \n",
       "1         102001         0  United States    country       NaN        SFR   \n",
       "2         102001         0  United States    country       NaN        SFR   \n",
       "3         102001         0  United States    country       NaN        SFR   \n",
       "4         102001         0  United States    country       NaN        SFR   \n",
       "...          ...       ...            ...        ...       ...        ...   \n",
       "578648    845172       769   Winfield, KS        msa        KS  all homes   \n",
       "578649    845172       769   Winfield, KS        msa        KS  all homes   \n",
       "578650    845172       769   Winfield, KS        msa        KS  all homes   \n",
       "578651    845172       769   Winfield, KS        msa        KS  all homes   \n",
       "578652    845172       769   Winfield, KS        msa        KS  all homes   \n",
       "\n",
       "              Date  Median Listing Price  Median Listing Price (Smoothed)  \\\n",
       "0       2018-01-13              259000.0                              NaN   \n",
       "1       2018-01-20              259900.0                              NaN   \n",
       "2       2018-01-27              259900.0                              NaN   \n",
       "3       2018-02-03              260000.0                         259700.0   \n",
       "4       2018-02-10              264900.0                         261175.0   \n",
       "...            ...                   ...                              ...   \n",
       "578648  2023-12-09              134950.0                         138913.0   \n",
       "578649  2023-12-16              120000.0                         133938.0   \n",
       "578650  2023-12-23              111000.0                         126463.0   \n",
       "578651  2023-12-30              126950.0                         123225.0   \n",
       "578652  2024-01-06              128000.0                         121488.0   \n",
       "\n",
       "        New Pending (Smoothed)  New Listings  New Listings (Smoothed)  \\\n",
       "0                          NaN           NaN                      NaN   \n",
       "1                          NaN           NaN                      NaN   \n",
       "2                          NaN           NaN                      NaN   \n",
       "3                          NaN           NaN                      NaN   \n",
       "4                          NaN           NaN                      NaN   \n",
       "...                        ...           ...                      ...   \n",
       "578648                     NaN           NaN                      NaN   \n",
       "578649                     NaN           NaN                      NaN   \n",
       "578650                     NaN           NaN                      NaN   \n",
       "578651                     NaN           NaN                      NaN   \n",
       "578652                     NaN           NaN                      NaN   \n",
       "\n",
       "        New Pending  \n",
       "0               NaN  \n",
       "1               NaN  \n",
       "2               NaN  \n",
       "3               NaN  \n",
       "4               NaN  \n",
       "...             ...  \n",
       "578648          NaN  \n",
       "578649          NaN  \n",
       "578650          NaN  \n",
       "578651          NaN  \n",
       "578652          NaN  \n",
       "\n",
       "[578653 rows x 13 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_frames = []\n",
    "\n",
    "exclude_columns = [\n",
    "    \"RegionID\",\n",
    "    \"SizeRank\",\n",
    "    \"RegionName\",\n",
    "    \"RegionType\",\n",
    "    \"StateName\",\n",
    "    \"Home Type\",\n",
    "]\n",
    "\n",
    "slug_column_mappings = {\n",
    "    \"_mlp_\": \"Median Listing Price\",\n",
    "    \"_new_listings_\": \"New Listings\",\n",
    "    \"new_pending\": \"New Pending\",\n",
    "}\n",
    "\n",
    "data_dir_path = get_data_path_for_config(CONFIG_NAME)\n",
    "\n",
    "for filename in os.listdir(data_dir_path):\n",
    "    if filename.endswith(\".csv\"):\n",
    "        print(\"processing \" + filename)\n",
    "        cur_df = pd.read_csv(os.path.join(data_dir_path, filename))\n",
    "\n",
    "        # ignore monthly data for now since it is redundant\n",
    "        if \"month\" in filename:\n",
    "            continue\n",
    "\n",
    "        cur_df = set_home_type(cur_df, filename)\n",
    "\n",
    "        data_frames = handle_slug_column_mappings(\n",
    "            data_frames, slug_column_mappings, exclude_columns, filename, cur_df\n",
    "        )\n",
    "\n",
    "combined_df = get_combined_df(\n",
    "    data_frames,\n",
    "    [\n",
    "        \"RegionID\",\n",
    "        \"SizeRank\",\n",
    "        \"RegionName\",\n",
    "        \"RegionType\",\n",
    "        \"StateName\",\n",
    "        \"Home Type\",\n",
    "        \"Date\",\n",
    "    ],\n",
    ")\n",
    "\n",
    "combined_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>Region ID</th>\n",
       "      <th>Size Rank</th>\n",
       "      <th>Region</th>\n",
       "      <th>Region Type</th>\n",
       "      <th>State</th>\n",
       "      <th>Home Type</th>\n",
       "      <th>Date</th>\n",
       "      <th>Median Listing Price</th>\n",
       "      <th>Median Listing Price (Smoothed)</th>\n",
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       "      <th>0</th>\n",
       "      <td>102001</td>\n",
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       "      <td>259000.0</td>\n",
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       "      <td>NaN</td>\n",
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       "      <th>1</th>\n",
       "      <td>102001</td>\n",
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       "      <th>2</th>\n",
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       "      <td>2018-01-27</td>\n",
       "      <td>259900.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>3</th>\n",
       "      <td>102001</td>\n",
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       "      <td>2018-02-03</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
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       "      <td>0</td>\n",
       "      <td>United States</td>\n",
       "      <td>country</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SFR</td>\n",
       "      <td>2018-02-10</td>\n",
       "      <td>264900.0</td>\n",
       "      <td>261175.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <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",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>578648</th>\n",
       "      <td>845172</td>\n",
       "      <td>769</td>\n",
       "      <td>Winfield, KS</td>\n",
       "      <td>msa</td>\n",
       "      <td>KS</td>\n",
       "      <td>all homes</td>\n",
       "      <td>2023-12-09</td>\n",
       "      <td>134950.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>845172</td>\n",
       "      <td>769</td>\n",
       "      <td>Winfield, KS</td>\n",
       "      <td>msa</td>\n",
       "      <td>KS</td>\n",
       "      <td>all homes</td>\n",
       "      <td>2023-12-16</td>\n",
       "      <td>120000.0</td>\n",
       "      <td>133938.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>578650</th>\n",
       "      <td>845172</td>\n",
       "      <td>769</td>\n",
       "      <td>Winfield, KS</td>\n",
       "      <td>msa</td>\n",
       "      <td>KS</td>\n",
       "      <td>all homes</td>\n",
       "      <td>2023-12-23</td>\n",
       "      <td>111000.0</td>\n",
       "      <td>126463.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>578651</th>\n",
       "      <td>845172</td>\n",
       "      <td>769</td>\n",
       "      <td>Winfield, KS</td>\n",
       "      <td>msa</td>\n",
       "      <td>KS</td>\n",
       "      <td>all homes</td>\n",
       "      <td>2023-12-30</td>\n",
       "      <td>126950.0</td>\n",
       "      <td>123225.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>578652</th>\n",
       "      <td>845172</td>\n",
       "      <td>769</td>\n",
       "      <td>Winfield, KS</td>\n",
       "      <td>msa</td>\n",
       "      <td>KS</td>\n",
       "      <td>all homes</td>\n",
       "      <td>2024-01-06</td>\n",
       "      <td>128000.0</td>\n",
       "      <td>121488.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>578653 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Region ID  Size Rank         Region Region Type State  Home Type  \\\n",
       "0          102001          0  United States     country   NaN        SFR   \n",
       "1          102001          0  United States     country   NaN        SFR   \n",
       "2          102001          0  United States     country   NaN        SFR   \n",
       "3          102001          0  United States     country   NaN        SFR   \n",
       "4          102001          0  United States     country   NaN        SFR   \n",
       "...           ...        ...            ...         ...   ...        ...   \n",
       "578648     845172        769   Winfield, KS         msa    KS  all homes   \n",
       "578649     845172        769   Winfield, KS         msa    KS  all homes   \n",
       "578650     845172        769   Winfield, KS         msa    KS  all homes   \n",
       "578651     845172        769   Winfield, KS         msa    KS  all homes   \n",
       "578652     845172        769   Winfield, KS         msa    KS  all homes   \n",
       "\n",
       "             Date  Median Listing Price  Median Listing Price (Smoothed)  \\\n",
       "0      2018-01-13              259000.0                              NaN   \n",
       "1      2018-01-20              259900.0                              NaN   \n",
       "2      2018-01-27              259900.0                              NaN   \n",
       "3      2018-02-03              260000.0                         259700.0   \n",
       "4      2018-02-10              264900.0                         261175.0   \n",
       "...           ...                   ...                              ...   \n",
       "578648 2023-12-09              134950.0                         138913.0   \n",
       "578649 2023-12-16              120000.0                         133938.0   \n",
       "578650 2023-12-23              111000.0                         126463.0   \n",
       "578651 2023-12-30              126950.0                         123225.0   \n",
       "578652 2024-01-06              128000.0                         121488.0   \n",
       "\n",
       "        New Pending (Smoothed)  New Listings  New Listings (Smoothed)  \\\n",
       "0                          NaN           NaN                      NaN   \n",
       "1                          NaN           NaN                      NaN   \n",
       "2                          NaN           NaN                      NaN   \n",
       "3                          NaN           NaN                      NaN   \n",
       "4                          NaN           NaN                      NaN   \n",
       "...                        ...           ...                      ...   \n",
       "578648                     NaN           NaN                      NaN   \n",
       "578649                     NaN           NaN                      NaN   \n",
       "578650                     NaN           NaN                      NaN   \n",
       "578651                     NaN           NaN                      NaN   \n",
       "578652                     NaN           NaN                      NaN   \n",
       "\n",
       "        New Pending  \n",
       "0               NaN  \n",
       "1               NaN  \n",
       "2               NaN  \n",
       "3               NaN  \n",
       "4               NaN  \n",
       "...             ...  \n",
       "578648          NaN  \n",
       "578649          NaN  \n",
       "578650          NaN  \n",
       "578651          NaN  \n",
       "578652          NaN  \n",
       "\n",
       "[578653 rows x 13 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Adjust column names\n",
    "final_df = combined_df.rename(\n",
    "    columns={\n",
    "        \"RegionID\": \"Region ID\",\n",
    "        \"SizeRank\": \"Size Rank\",\n",
    "        \"RegionName\": \"Region\",\n",
    "        \"RegionType\": \"Region Type\",\n",
    "        \"StateName\": \"State\",\n",
    "    }\n",
    ")\n",
    "\n",
    "final_df[\"Date\"] = pd.to_datetime(final_df[\"Date\"], format=\"%Y-%m-%d\")\n",
    "\n",
    "final_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "save_final_df_as_jsonl(CONFIG_NAME, final_df)"
   ]
  }
 ],
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