{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "DATA_DIR = \"../data\"\n",
    "PROCESSED_DIR = \"../processed/\"\n",
    "FACET_DIR = \"sales/\"\n",
    "FULL_DATA_DIR_PATH = os.path.join(DATA_DIR, FACET_DIR)\n",
    "FULL_PROCESSED_DIR_PATH = os.path.join(PROCESSED_DIR, FACET_DIR)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "processing Metro_mean_sale_to_list_uc_sfrcondo_sm_month.csv\n",
      "processing Metro_median_sale_to_list_uc_sfrcondo_week.csv\n",
      "processing Metro_median_sale_price_uc_sfr_week.csv\n",
      "processing Metro_pct_sold_below_list_uc_sfrcondo_sm_month.csv\n",
      "processing Metro_median_sale_price_uc_sfr_sm_sa_week.csv\n",
      "processing Metro_pct_sold_below_list_uc_sfrcondo_month.csv\n",
      "processing Metro_median_sale_price_uc_sfrcondo_sm_week.csv\n",
      "processing Metro_pct_sold_below_list_uc_sfrcondo_sm_week.csv\n",
      "processing Metro_median_sale_price_uc_sfr_month.csv\n",
      "processing Metro_median_sale_to_list_uc_sfrcondo_sm_month.csv\n",
      "processing Metro_pct_sold_above_list_uc_sfrcondo_month.csv\n",
      "processing Metro_median_sale_to_list_uc_sfrcondo_sm_week.csv\n",
      "processing Metro_median_sale_price_uc_sfrcondo_sm_sa_month.csv\n",
      "processing Metro_sales_count_now_uc_sfrcondo_month.csv\n",
      "processing Metro_pct_sold_above_list_uc_sfrcondo_week.csv\n",
      "processing Metro_mean_sale_to_list_uc_sfrcondo_sm_week.csv\n",
      "processing Metro_median_sale_price_uc_sfrcondo_sm_month.csv\n",
      "processing Metro_mean_sale_to_list_uc_sfrcondo_week.csv\n",
      "processing Metro_median_sale_price_uc_sfr_sm_month.csv\n",
      "processing Metro_median_sale_to_list_uc_sfrcondo_month.csv\n",
      "processing Metro_median_sale_price_uc_sfrcondo_sm_sa_week.csv\n",
      "processing Metro_pct_sold_below_list_uc_sfrcondo_week.csv\n",
      "processing Metro_median_sale_price_uc_sfrcondo_week.csv\n",
      "processing Metro_mean_sale_to_list_uc_sfrcondo_month.csv\n",
      "processing Metro_pct_sold_above_list_uc_sfrcondo_sm_week.csv\n",
      "processing Metro_median_sale_price_uc_sfr_sm_week.csv\n",
      "processing Metro_median_sale_price_uc_sfrcondo_month.csv\n",
      "processing Metro_pct_sold_above_list_uc_sfrcondo_sm_month.csv\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",
       "        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>Mean Sale to List Ratio (Smoothed)</th>\n",
       "      <th>Median Sale to List Ratio</th>\n",
       "      <th>Median Sale Price</th>\n",
       "      <th>% Sold Below List (Smoothed)</th>\n",
       "      <th>Median Sale Price (Smoothed) (Seasonally Adjusted)</th>\n",
       "      <th>% Sold Below List</th>\n",
       "      <th>Median Sale Price (Smoothed)</th>\n",
       "      <th>Median Sale to List Ratio (Smoothed)</th>\n",
       "      <th>% Sold Above List</th>\n",
       "      <th>Nowcast</th>\n",
       "      <th>Mean Sale to List Ratio</th>\n",
       "      <th>% Sold Above List (Smoothed)</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>2008-02-02</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>172000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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",
       "      <td>0</td>\n",
       "      <td>United States</td>\n",
       "      <td>country</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SFR</td>\n",
       "      <td>2008-02-09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>165400.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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",
       "      <td>country</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SFR</td>\n",
       "      <td>2008-02-16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>168000.0</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <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",
       "      <td>country</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SFR</td>\n",
       "      <td>2008-02-23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>167600.0</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>4</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>2008-02-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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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       "      <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",
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       "      <td>296</td>\n",
       "      <td>Ottawa, IL</td>\n",
       "      <td>msa</td>\n",
       "      <td>IL</td>\n",
       "      <td>all homes</td>\n",
       "      <td>2023-07-31</td>\n",
       "      <td>0.976219</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.554969</td>\n",
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       "      <td>0.491379</td>\n",
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       "      <td>0.985172</td>\n",
       "      <td>0.312332</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.979227</td>\n",
       "      <td>0.312332</td>\n",
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       "    <tr>\n",
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       "      <td>845167</td>\n",
       "      <td>296</td>\n",
       "      <td>Ottawa, IL</td>\n",
       "      <td>msa</td>\n",
       "      <td>IL</td>\n",
       "      <td>all homes</td>\n",
       "      <td>2023-08-31</td>\n",
       "      <td>0.971893</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.541090</td>\n",
       "      <td>125089.0</td>\n",
       "      <td>0.602041</td>\n",
       "      <td>131833.0</td>\n",
       "      <td>0.987383</td>\n",
       "      <td>0.294778</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.959261</td>\n",
       "      <td>0.294778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504605</th>\n",
       "      <td>845167</td>\n",
       "      <td>296</td>\n",
       "      <td>Ottawa, IL</td>\n",
       "      <td>msa</td>\n",
       "      <td>IL</td>\n",
       "      <td>all homes</td>\n",
       "      <td>2023-09-30</td>\n",
       "      <td>0.968028</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.531140</td>\n",
       "      <td>127199.0</td>\n",
       "      <td>0.500000</td>\n",
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       "      <td>0.991072</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>0.965595</td>\n",
       "      <td>0.285128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504606</th>\n",
       "      <td>845167</td>\n",
       "      <td>296</td>\n",
       "      <td>Ottawa, IL</td>\n",
       "      <td>msa</td>\n",
       "      <td>IL</td>\n",
       "      <td>all homes</td>\n",
       "      <td>2023-10-31</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>0.272350</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.962599</td>\n",
       "      <td>0.272350</td>\n",
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       "    <tr>\n",
       "      <th>504607</th>\n",
       "      <td>845167</td>\n",
       "      <td>296</td>\n",
       "      <td>Ottawa, IL</td>\n",
       "      <td>msa</td>\n",
       "      <td>IL</td>\n",
       "      <td>all homes</td>\n",
       "      <td>2023-11-30</td>\n",
       "      <td>0.967126</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.539226</td>\n",
       "      <td>129291.0</td>\n",
       "      <td>0.543210</td>\n",
       "      <td>131000.0</td>\n",
       "      <td>0.990886</td>\n",
       "      <td>0.280538</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.973184</td>\n",
       "      <td>0.280538</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>504608 rows × 19 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",
       "504603    845167       296     Ottawa, IL        msa        IL  all homes   \n",
       "504604    845167       296     Ottawa, IL        msa        IL  all homes   \n",
       "504605    845167       296     Ottawa, IL        msa        IL  all homes   \n",
       "504606    845167       296     Ottawa, IL        msa        IL  all homes   \n",
       "504607    845167       296     Ottawa, IL        msa        IL  all homes   \n",
       "\n",
       "              Date  Mean Sale to List Ratio (Smoothed)  \\\n",
       "0       2008-02-02                                 NaN   \n",
       "1       2008-02-09                                 NaN   \n",
       "2       2008-02-16                                 NaN   \n",
       "3       2008-02-23                                 NaN   \n",
       "4       2008-02-29                                 NaN   \n",
       "...            ...                                 ...   \n",
       "504603  2023-07-31                            0.976219   \n",
       "504604  2023-08-31                            0.971893   \n",
       "504605  2023-09-30                            0.968028   \n",
       "504606  2023-10-31                            0.962485   \n",
       "504607  2023-11-30                            0.967126   \n",
       "\n",
       "        Median Sale to List Ratio  Median Sale Price  \\\n",
       "0                             NaN           172000.0   \n",
       "1                             NaN           165400.0   \n",
       "2                             NaN           168000.0   \n",
       "3                             NaN           165000.0   \n",
       "4                             NaN                NaN   \n",
       "...                           ...                ...   \n",
       "504603                        NaN                NaN   \n",
       "504604                        NaN                NaN   \n",
       "504605                        NaN                NaN   \n",
       "504606                        NaN                NaN   \n",
       "504607                        NaN                NaN   \n",
       "\n",
       "        % Sold Below List (Smoothed)  \\\n",
       "0                                NaN   \n",
       "1                                NaN   \n",
       "2                                NaN   \n",
       "3                                NaN   \n",
       "4                                NaN   \n",
       "...                              ...   \n",
       "504603                      0.554969   \n",
       "504604                      0.541090   \n",
       "504605                      0.531140   \n",
       "504606                      0.558836   \n",
       "504607                      0.539226   \n",
       "\n",
       "        Median Sale Price (Smoothed) (Seasonally Adjusted)  % Sold Below List  \\\n",
       "0                                                     NaN                 NaN   \n",
       "1                                                     NaN                 NaN   \n",
       "2                                                     NaN                 NaN   \n",
       "3                                                     NaN                 NaN   \n",
       "4                                                     NaN                 NaN   \n",
       "...                                                   ...                 ...   \n",
       "504603                                           127574.0            0.491379   \n",
       "504604                                           125089.0            0.602041   \n",
       "504605                                           127199.0            0.500000   \n",
       "504606                                           131159.0            0.574468   \n",
       "504607                                           129291.0            0.543210   \n",
       "\n",
       "        Median Sale Price (Smoothed)  Median Sale to List Ratio (Smoothed)  \\\n",
       "0                                NaN                                   NaN   \n",
       "1                                NaN                                   NaN   \n",
       "2                                NaN                                   NaN   \n",
       "3                           167600.0                                   NaN   \n",
       "4                                NaN                                   NaN   \n",
       "...                              ...                                   ...   \n",
       "504603                      133500.0                              0.985172   \n",
       "504604                      131833.0                              0.987383   \n",
       "504605                      132333.0                              0.991072   \n",
       "504606                      134667.0                              0.985657   \n",
       "504607                      131000.0                              0.990886   \n",
       "\n",
       "        % Sold Above List  Nowcast  Mean Sale to List Ratio  \\\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",
       "504603           0.312332      NaN                 0.979227   \n",
       "504604           0.294778      NaN                 0.959261   \n",
       "504605           0.285128      NaN                 0.965595   \n",
       "504606           0.272350      NaN                 0.962599   \n",
       "504607           0.280538      NaN                 0.973184   \n",
       "\n",
       "        % Sold Above List (Smoothed)  \n",
       "0                                NaN  \n",
       "1                                NaN  \n",
       "2                                NaN  \n",
       "3                                NaN  \n",
       "4                                NaN  \n",
       "...                              ...  \n",
       "504603                      0.312332  \n",
       "504604                      0.294778  \n",
       "504605                      0.285128  \n",
       "504606                      0.272350  \n",
       "504607                      0.280538  \n",
       "\n",
       "[504608 rows x 19 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# base cols RegionID,SizeRank,RegionName,RegionType,StateName\n",
    "\n",
    "exclude_columns = [\n",
    "    \"RegionID\",\n",
    "    \"SizeRank\",\n",
    "    \"RegionName\",\n",
    "    \"RegionType\",\n",
    "    \"StateName\",\n",
    "    \"Home Type\",\n",
    "]\n",
    "\n",
    "data_frames = []\n",
    "\n",
    "for filename in os.listdir(FULL_DATA_DIR_PATH):\n",
    "    if filename.endswith(\".csv\"):\n",
    "        print(\"processing \" + filename)\n",
    "        cur_df = pd.read_csv(os.path.join(FULL_DATA_DIR_PATH, filename))\n",
    "\n",
    "        # ignore monthly data for now since it is redundant\n",
    "        if \"monthly\" in filename:\n",
    "            continue\n",
    "\n",
    "        if \"_sfrcondo_\" in filename:\n",
    "            cur_df[\"Home Type\"] = \"all homes\"\n",
    "        elif \"_sfr_\" in filename:\n",
    "            cur_df[\"Home Type\"] = \"SFR\"\n",
    "\n",
    "        # Identify columns to pivot\n",
    "        columns_to_pivot = [col for col in cur_df.columns if col not in exclude_columns]\n",
    "\n",
    "        smoothed = \"_sm_\" in filename\n",
    "        seasonally_adjusted = \"_sa_\" in filename\n",
    "\n",
    "        if \"_median_sale_to_list_\" in filename:\n",
    "            col_name = \"Median Sale to List Ratio\"\n",
    "            if smoothed:\n",
    "                col_name += \" (Smoothed)\"\n",
    "            if seasonally_adjusted:\n",
    "                col_name += \" (Seasonally Adjusted)\"\n",
    "\n",
    "            cur_df = pd.melt(\n",
    "                cur_df,\n",
    "                id_vars=exclude_columns,\n",
    "                value_vars=columns_to_pivot,\n",
    "                var_name=\"Date\",\n",
    "                value_name=col_name,\n",
    "            )\n",
    "\n",
    "        elif \"_mean_sale_to_list_\" in filename:\n",
    "            col_name = \"Mean Sale to List Ratio\"\n",
    "            if smoothed:\n",
    "                col_name += \" (Smoothed)\"\n",
    "            if seasonally_adjusted:\n",
    "                col_name += \" (Seasonally Adjusted)\"\n",
    "\n",
    "            cur_df = pd.melt(\n",
    "                cur_df,\n",
    "                id_vars=exclude_columns,\n",
    "                value_vars=columns_to_pivot,\n",
    "                var_name=\"Date\",\n",
    "                value_name=col_name,\n",
    "            )\n",
    "\n",
    "        elif \"_median_sale_price_\" in filename:\n",
    "            col_name = \"Median Sale Price\"\n",
    "            if smoothed:\n",
    "                col_name += \" (Smoothed)\"\n",
    "            if seasonally_adjusted:\n",
    "                col_name += \" (Seasonally Adjusted)\"\n",
    "\n",
    "            cur_df = pd.melt(\n",
    "                cur_df,\n",
    "                id_vars=exclude_columns,\n",
    "                value_vars=columns_to_pivot,\n",
    "                var_name=\"Date\",\n",
    "                value_name=col_name,\n",
    "            )\n",
    "\n",
    "        elif \"_pct_sold_above_list_\" in filename:\n",
    "            col_name = \"% Sold Above List\"\n",
    "            if smoothed:\n",
    "                col_name += \" (Smoothed)\"\n",
    "            if seasonally_adjusted:\n",
    "                col_name += \" (Seasonally Adjusted)\"\n",
    "\n",
    "            cur_df = pd.melt(\n",
    "                cur_df,\n",
    "                id_vars=exclude_columns,\n",
    "                value_vars=columns_to_pivot,\n",
    "                var_name=\"Date\",\n",
    "                value_name=col_name,\n",
    "            )\n",
    "\n",
    "        elif \"_pct_sold_below_list_\" in filename:\n",
    "            col_name = \"% Sold Below List\"\n",
    "            if smoothed:\n",
    "                col_name += \" (Smoothed)\"\n",
    "            if seasonally_adjusted:\n",
    "                col_name += \" (Seasonally Adjusted)\"\n",
    "\n",
    "            cur_df = pd.melt(\n",
    "                cur_df,\n",
    "                id_vars=exclude_columns,\n",
    "                value_vars=columns_to_pivot,\n",
    "                var_name=\"Date\",\n",
    "                value_name=col_name,\n",
    "            )\n",
    "\n",
    "        elif \"_sales_count_now_\" in filename:\n",
    "            col_name = \"Nowcast\"\n",
    "            if smoothed:\n",
    "                col_name += \" (Smoothed)\"\n",
    "            if seasonally_adjusted:\n",
    "                col_name += \" (Seasonally Adjusted)\"\n",
    "\n",
    "            cur_df = pd.melt(\n",
    "                cur_df,\n",
    "                id_vars=exclude_columns,\n",
    "                value_vars=columns_to_pivot,\n",
    "                var_name=\"Date\",\n",
    "                value_name=col_name,\n",
    "            )\n",
    "\n",
    "        data_frames.append(cur_df)\n",
    "\n",
    "\n",
    "def get_combined_df(data_frames):\n",
    "    combined_df = None\n",
    "    if len(data_frames) > 1:\n",
    "        # iterate over dataframes and merge or concat\n",
    "        combined_df = data_frames[0]\n",
    "        for i in range(1, len(data_frames)):\n",
    "            cur_df = data_frames[i]\n",
    "            combined_df = pd.merge(\n",
    "                combined_df,\n",
    "                cur_df,\n",
    "                on=[\n",
    "                    \"RegionID\",\n",
    "                    \"SizeRank\",\n",
    "                    \"RegionName\",\n",
    "                    \"RegionType\",\n",
    "                    \"StateName\",\n",
    "                    \"Home Type\",\n",
    "                    \"Date\",\n",
    "                ],\n",
    "                how=\"outer\",\n",
    "                suffixes=(\"\", \"_\" + str(i)),\n",
    "            )\n",
    "    elif len(data_frames) == 1:\n",
    "        combined_df = data_frames[0]\n",
    "\n",
    "    return combined_df\n",
    "\n",
    "\n",
    "combined_df = get_combined_df(data_frames)\n",
    "# iterate over rows of combined df and coalesce column values across columns that start with \"Median Sale Price\"\n",
    "columns_to_coalesce = [\n",
    "    \"Mean Sale to List Ratio (Smoothed)\"\n",
    "    \"Median Sale to List Ratio\"\n",
    "    \"Median Sale Price\"\n",
    "    \"% Sold Below List (Smoothed)\",\n",
    "    \"Median Sale Price (Smoothed) (Seasonally Adjusted)\",\n",
    "    \"% Sold Below List\",\n",
    "    \"Median Sale Price (Smoothed)\",\n",
    "    \"Median Sale to List Ratio (Smoothed)\",\n",
    "    \"% Sold Above List\",\n",
    "    \"Nowcast\",\n",
    "    \"Mean Sale to List Ratio\",\n",
    "    \"% Sold Above List (Smoothed)\",\n",
    "]\n",
    "\n",
    "for index, row in combined_df.iterrows():\n",
    "    for col in combined_df.columns:\n",
    "        for column_to_coalesce in columns_to_coalesce:\n",
    "            if column_to_coalesce in col and \"_\" in col:\n",
    "                if not pd.isna(row[col]):\n",
    "                    combined_df.at[index, column_to_coalesce] = row[col]\n",
    "\n",
    "# remove columns with underscores\n",
    "combined_df = combined_df[[col for col in combined_df.columns if \"_\" not in col]]\n",
    "\n",
    "combined_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>Mean Sale to List Ratio (Smoothed)</th>\n",
       "      <th>Median Sale to List Ratio</th>\n",
       "      <th>Median Sale Price</th>\n",
       "      <th>% Sold Below List (Smoothed)</th>\n",
       "      <th>Median Sale Price (Smoothed) (Seasonally Adjusted)</th>\n",
       "      <th>% Sold Below List</th>\n",
       "      <th>Median Sale Price (Smoothed)</th>\n",
       "      <th>Median Sale to List Ratio (Smoothed)</th>\n",
       "      <th>% Sold Above List</th>\n",
       "      <th>Nowcast</th>\n",
       "      <th>Mean Sale to List Ratio</th>\n",
       "      <th>% Sold Above List (Smoothed)</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>2008-02-02</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>172000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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",
       "      <td>0</td>\n",
       "      <td>United States</td>\n",
       "      <td>country</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SFR</td>\n",
       "      <td>2008-02-09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>165400.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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",
       "      <td>country</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SFR</td>\n",
       "      <td>2008-02-16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>168000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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",
       "      <td>country</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SFR</td>\n",
       "      <td>2008-02-23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>165000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>167600.0</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>4</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>2008-02-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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>...</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504603</th>\n",
       "      <td>845167</td>\n",
       "      <td>296</td>\n",
       "      <td>Ottawa, IL</td>\n",
       "      <td>msa</td>\n",
       "      <td>IL</td>\n",
       "      <td>all homes</td>\n",
       "      <td>2023-07-31</td>\n",
       "      <td>0.976219</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.554969</td>\n",
       "      <td>127574.0</td>\n",
       "      <td>0.491379</td>\n",
       "      <td>133500.0</td>\n",
       "      <td>0.985172</td>\n",
       "      <td>0.312332</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.979227</td>\n",
       "      <td>0.312332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504604</th>\n",
       "      <td>845167</td>\n",
       "      <td>296</td>\n",
       "      <td>Ottawa, IL</td>\n",
       "      <td>msa</td>\n",
       "      <td>IL</td>\n",
       "      <td>all homes</td>\n",
       "      <td>2023-08-31</td>\n",
       "      <td>0.971893</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.541090</td>\n",
       "      <td>125089.0</td>\n",
       "      <td>0.602041</td>\n",
       "      <td>131833.0</td>\n",
       "      <td>0.987383</td>\n",
       "      <td>0.294778</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.959261</td>\n",
       "      <td>0.294778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504605</th>\n",
       "      <td>845167</td>\n",
       "      <td>296</td>\n",
       "      <td>Ottawa, IL</td>\n",
       "      <td>msa</td>\n",
       "      <td>IL</td>\n",
       "      <td>all homes</td>\n",
       "      <td>2023-09-30</td>\n",
       "      <td>0.968028</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.531140</td>\n",
       "      <td>127199.0</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>132333.0</td>\n",
       "      <td>0.991072</td>\n",
       "      <td>0.285128</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.965595</td>\n",
       "      <td>0.285128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504606</th>\n",
       "      <td>845167</td>\n",
       "      <td>296</td>\n",
       "      <td>Ottawa, IL</td>\n",
       "      <td>msa</td>\n",
       "      <td>IL</td>\n",
       "      <td>all homes</td>\n",
       "      <td>2023-10-31</td>\n",
       "      <td>0.962485</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.558836</td>\n",
       "      <td>131159.0</td>\n",
       "      <td>0.574468</td>\n",
       "      <td>134667.0</td>\n",
       "      <td>0.985657</td>\n",
       "      <td>0.272350</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.962599</td>\n",
       "      <td>0.272350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504607</th>\n",
       "      <td>845167</td>\n",
       "      <td>296</td>\n",
       "      <td>Ottawa, IL</td>\n",
       "      <td>msa</td>\n",
       "      <td>IL</td>\n",
       "      <td>all homes</td>\n",
       "      <td>2023-11-30</td>\n",
       "      <td>0.967126</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.539226</td>\n",
       "      <td>129291.0</td>\n",
       "      <td>0.543210</td>\n",
       "      <td>131000.0</td>\n",
       "      <td>0.990886</td>\n",
       "      <td>0.280538</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.973184</td>\n",
       "      <td>0.280538</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>504608 rows × 19 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",
       "504603     845167        296     Ottawa, IL         msa    IL  all homes   \n",
       "504604     845167        296     Ottawa, IL         msa    IL  all homes   \n",
       "504605     845167        296     Ottawa, IL         msa    IL  all homes   \n",
       "504606     845167        296     Ottawa, IL         msa    IL  all homes   \n",
       "504607     845167        296     Ottawa, IL         msa    IL  all homes   \n",
       "\n",
       "              Date  Mean Sale to List Ratio (Smoothed)  \\\n",
       "0       2008-02-02                                 NaN   \n",
       "1       2008-02-09                                 NaN   \n",
       "2       2008-02-16                                 NaN   \n",
       "3       2008-02-23                                 NaN   \n",
       "4       2008-02-29                                 NaN   \n",
       "...            ...                                 ...   \n",
       "504603  2023-07-31                            0.976219   \n",
       "504604  2023-08-31                            0.971893   \n",
       "504605  2023-09-30                            0.968028   \n",
       "504606  2023-10-31                            0.962485   \n",
       "504607  2023-11-30                            0.967126   \n",
       "\n",
       "        Median Sale to List Ratio  Median Sale Price  \\\n",
       "0                             NaN           172000.0   \n",
       "1                             NaN           165400.0   \n",
       "2                             NaN           168000.0   \n",
       "3                             NaN           165000.0   \n",
       "4                             NaN                NaN   \n",
       "...                           ...                ...   \n",
       "504603                        NaN                NaN   \n",
       "504604                        NaN                NaN   \n",
       "504605                        NaN                NaN   \n",
       "504606                        NaN                NaN   \n",
       "504607                        NaN                NaN   \n",
       "\n",
       "        % Sold Below List (Smoothed)  \\\n",
       "0                                NaN   \n",
       "1                                NaN   \n",
       "2                                NaN   \n",
       "3                                NaN   \n",
       "4                                NaN   \n",
       "...                              ...   \n",
       "504603                      0.554969   \n",
       "504604                      0.541090   \n",
       "504605                      0.531140   \n",
       "504606                      0.558836   \n",
       "504607                      0.539226   \n",
       "\n",
       "        Median Sale Price (Smoothed) (Seasonally Adjusted)  % Sold Below List  \\\n",
       "0                                                     NaN                 NaN   \n",
       "1                                                     NaN                 NaN   \n",
       "2                                                     NaN                 NaN   \n",
       "3                                                     NaN                 NaN   \n",
       "4                                                     NaN                 NaN   \n",
       "...                                                   ...                 ...   \n",
       "504603                                           127574.0            0.491379   \n",
       "504604                                           125089.0            0.602041   \n",
       "504605                                           127199.0            0.500000   \n",
       "504606                                           131159.0            0.574468   \n",
       "504607                                           129291.0            0.543210   \n",
       "\n",
       "        Median Sale Price (Smoothed)  Median Sale to List Ratio (Smoothed)  \\\n",
       "0                                NaN                                   NaN   \n",
       "1                                NaN                                   NaN   \n",
       "2                                NaN                                   NaN   \n",
       "3                           167600.0                                   NaN   \n",
       "4                                NaN                                   NaN   \n",
       "...                              ...                                   ...   \n",
       "504603                      133500.0                              0.985172   \n",
       "504604                      131833.0                              0.987383   \n",
       "504605                      132333.0                              0.991072   \n",
       "504606                      134667.0                              0.985657   \n",
       "504607                      131000.0                              0.990886   \n",
       "\n",
       "        % Sold Above List  Nowcast  Mean Sale to List Ratio  \\\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",
       "504603           0.312332      NaN                 0.979227   \n",
       "504604           0.294778      NaN                 0.959261   \n",
       "504605           0.285128      NaN                 0.965595   \n",
       "504606           0.272350      NaN                 0.962599   \n",
       "504607           0.280538      NaN                 0.973184   \n",
       "\n",
       "        % Sold Above List (Smoothed)  \n",
       "0                                NaN  \n",
       "1                                NaN  \n",
       "2                                NaN  \n",
       "3                                NaN  \n",
       "4                                NaN  \n",
       "...                              ...  \n",
       "504603                      0.312332  \n",
       "504604                      0.294778  \n",
       "504605                      0.285128  \n",
       "504606                      0.272350  \n",
       "504607                      0.280538  \n",
       "\n",
       "[504608 rows x 19 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_df = combined_df\n",
    "final_df = final_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.sort_values(by=[\"Region ID\", \"Home Type\", \"Date\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "if not os.path.exists(FULL_PROCESSED_DIR_PATH):\n",
    "    os.makedirs(FULL_PROCESSED_DIR_PATH)\n",
    "\n",
    "final_df.to_json(FULL_PROCESSED_DIR_PATH + \"final.jsonl\", orient=\"records\", lines=True)"
   ]
  }
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