fix: update days on market data

processed/days_on_market/final.jsonl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:fc4cb57aeaef46572070e01871980ab0214c145047aa61e71cfa65e1d45a9367
-size 232501403
+oid sha256:1cf82e9ce68b4ebf991214a7de3fbc8f25de319da470741761d44d11d5cc89f3
+size 230154547

processors/days_on_market.ipynb

@@ -12,7 +12,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -25,7 +25,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -322,7 +322,7 @@
        "[586714 rows x 13 columns]"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -365,6 +365,34 @@
     "    return 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",
     "for filename in os.listdir(FULL_DATA_DIR_PATH):\n",
     "    if filename.endswith(\".csv\"):\n",
     "        # print(\"processing \" + filename)\n",
@@ -403,37 +431,8 @@
     "                break\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",
     "\n",
-    "# iterate over rows of combined df and coalesce column values across columns that start with \"Median Sale Price\"\n",
     "columns_to_coalesce = slug_column_mappings.values()\n",
     "print(columns_to_coalesce)\n",
     "\n",
@@ -452,7 +451,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -480,7 +479,7 @@
        "      <th>Size Rank</th>\n",
        "      <th>Region</th>\n",
        "      <th>Region Type</th>\n",
-       "      <th>StateName</th>\n",
+       "      <th>State</th>\n",
        "      <th>Home Type</th>\n",
        "      <th>Date</th>\n",
        "      <th>Mean Listings Price Cut Amount (Smoothed)</th>\n",
@@ -674,18 +673,18 @@
        "</div>"
       ],
       "text/plain": [
-       "        Region ID  Size Rank         Region Region Type StateName  \\\n",
-       "0          102001          0  United States     country       NaN   \n",
-       "1          102001          0  United States     country       NaN   \n",
-       "2          102001          0  United States     country       NaN   \n",
-       "3          102001          0  United States     country       NaN   \n",
-       "4          102001          0  United States     country       NaN   \n",
-       "...           ...        ...            ...         ...       ...   \n",
-       "586709     845172        769   Winfield, KS         msa        KS   \n",
-       "586710     845172        769   Winfield, KS         msa        KS   \n",
-       "586711     845172        769   Winfield, KS         msa        KS   \n",
-       "586712     845172        769   Winfield, KS         msa        KS   \n",
-       "586713     845172        769   Winfield, KS         msa        KS   \n",
+       "        Region ID  Size Rank         Region Region Type State  \\\n",
+       "0          102001          0  United States     country   NaN   \n",
+       "1          102001          0  United States     country   NaN   \n",
+       "2          102001          0  United States     country   NaN   \n",
+       "3          102001          0  United States     country   NaN   \n",
+       "4          102001          0  United States     country   NaN   \n",
+       "...           ...        ...            ...         ...   ...   \n",
+       "586709     845172        769   Winfield, KS         msa    KS   \n",
+       "586710     845172        769   Winfield, KS         msa    KS   \n",
+       "586711     845172        769   Winfield, KS         msa    KS   \n",
+       "586712     845172        769   Winfield, KS         msa    KS   \n",
+       "586713     845172        769   Winfield, KS         msa    KS   \n",
        "\n",
        "                      Home Type        Date  \\\n",
        "0                           SFR  2018-01-06   \n",
@@ -742,7 +741,7 @@
        "[586714 rows x 13 columns]"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -755,6 +754,7 @@
     "        \"SizeRank\": \"Size Rank\",\n",
     "        \"RegionName\": \"Region\",\n",
     "        \"RegionType\": \"Region Type\",\n",
+    "        \"StateName\": \"State\",\n",
     "    }\n",
     ")\n",
     "\n",
@@ -763,7 +763,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [

tester.ipynb

@@ -13,45 +13,40 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "home_value_forecasts\n",
-      "new_constructions\n",
-      "for_sale_listings\n",
-      "rentals\n",
-      "sales\n",
-      "home_values\n"
+      "days_on_market\n"
      ]
     },
     {
-     "ename": "ValueError",
-     "evalue": "BuilderConfig 'home_values' not found. Available: ['home_value_forecasts', 'new_constructions', 'for_sale_listings', 'rentals', 'sales']",
+     "ename": "UnboundLocalError",
+     "evalue": "cannot access local variable 'features' where it is not associated with a value",
      "output_type": "error",
      "traceback": [
       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[11], line 12\u001b[0m\n\u001b[1;32m     10\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m config \u001b[38;5;129;01min\u001b[39;00m configs:\n\u001b[1;32m     11\u001b[0m     \u001b[38;5;28mprint\u001b[39m(config)\n\u001b[0;32m---> 12\u001b[0m     dataset \u001b[38;5;241m=\u001b[39m \u001b[43mload_dataset\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmisikoff/zillow\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrust_remote_code\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n",
+      "\u001b[0;31mUnboundLocalError\u001b[0m                         Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[14], line 12\u001b[0m\n\u001b[1;32m     10\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m config \u001b[38;5;129;01min\u001b[39;00m configs:\n\u001b[1;32m     11\u001b[0m     \u001b[38;5;28mprint\u001b[39m(config)\n\u001b[0;32m---> 12\u001b[0m     dataset \u001b[38;5;241m=\u001b[39m \u001b[43mload_dataset\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmisikoff/zillow\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrust_remote_code\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n",
       "File \u001b[0;32m~/opt/anaconda3/envs/sta663/lib/python3.12/site-packages/datasets/load.py:2548\u001b[0m, in \u001b[0;36mload_dataset\u001b[0;34m(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, verification_mode, ignore_verifications, keep_in_memory, save_infos, revision, token, use_auth_token, task, streaming, num_proc, storage_options, trust_remote_code, **config_kwargs)\u001b[0m\n\u001b[1;32m   2543\u001b[0m verification_mode \u001b[38;5;241m=\u001b[39m VerificationMode(\n\u001b[1;32m   2544\u001b[0m     (verification_mode \u001b[38;5;129;01mor\u001b[39;00m VerificationMode\u001b[38;5;241m.\u001b[39mBASIC_CHECKS) \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m save_infos \u001b[38;5;28;01melse\u001b[39;00m VerificationMode\u001b[38;5;241m.\u001b[39mALL_CHECKS\n\u001b[1;32m   2545\u001b[0m )\n\u001b[1;32m   2547\u001b[0m \u001b[38;5;66;03m# Create a dataset builder\u001b[39;00m\n\u001b[0;32m-> 2548\u001b[0m builder_instance \u001b[38;5;241m=\u001b[39m \u001b[43mload_dataset_builder\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   2549\u001b[0m \u001b[43m    \u001b[49m\u001b[43mpath\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2550\u001b[0m \u001b[43m    \u001b[49m\u001b[43mname\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2551\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdata_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata_dir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2552\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdata_files\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata_files\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2553\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcache_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcache_dir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2554\u001b[0m \u001b[43m    \u001b[49m\u001b[43mfeatures\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfeatures\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2555\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdownload_config\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdownload_config\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2556\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdownload_mode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdownload_mode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2557\u001b[0m \u001b[43m    \u001b[49m\u001b[43mrevision\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrevision\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2558\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtoken\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtoken\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2559\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstorage_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstorage_options\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2560\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtrust_remote_code\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtrust_remote_code\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2561\u001b[0m \u001b[43m    \u001b[49m\u001b[43m_require_default_config_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mname\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mis\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m   2562\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mconfig_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2563\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   2565\u001b[0m \u001b[38;5;66;03m# Return iterable dataset in case of streaming\u001b[39;00m\n\u001b[1;32m   2566\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m streaming:\n",
       "File \u001b[0;32m~/opt/anaconda3/envs/sta663/lib/python3.12/site-packages/datasets/load.py:2257\u001b[0m, in \u001b[0;36mload_dataset_builder\u001b[0;34m(path, name, data_dir, data_files, cache_dir, features, download_config, download_mode, revision, token, use_auth_token, storage_options, trust_remote_code, _require_default_config_name, **config_kwargs)\u001b[0m\n\u001b[1;32m   2255\u001b[0m builder_cls \u001b[38;5;241m=\u001b[39m get_dataset_builder_class(dataset_module, dataset_name\u001b[38;5;241m=\u001b[39mdataset_name)\n\u001b[1;32m   2256\u001b[0m \u001b[38;5;66;03m# Instantiate the dataset builder\u001b[39;00m\n\u001b[0;32m-> 2257\u001b[0m builder_instance: DatasetBuilder \u001b[38;5;241m=\u001b[39m \u001b[43mbuilder_cls\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   2258\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcache_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcache_dir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2259\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdataset_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdataset_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2260\u001b[0m \u001b[43m    \u001b[49m\u001b[43mconfig_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconfig_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2261\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdata_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata_dir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2262\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdata_files\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata_files\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2263\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;28;43mhash\u001b[39;49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdataset_module\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mhash\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2264\u001b[0m \u001b[43m    \u001b[49m\u001b[43minfo\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minfo\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2265\u001b[0m \u001b[43m    \u001b[49m\u001b[43mfeatures\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfeatures\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2266\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtoken\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtoken\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2267\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstorage_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstorage_options\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2268\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mbuilder_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2269\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mconfig_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2270\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   2271\u001b[0m builder_instance\u001b[38;5;241m.\u001b[39m_use_legacy_cache_dir_if_possible(dataset_module)\n\u001b[1;32m   2273\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m builder_instance\n",
-      "File \u001b[0;32m~/opt/anaconda3/envs/sta663/lib/python3.12/site-packages/datasets/builder.py:371\u001b[0m, in \u001b[0;36mDatasetBuilder.__init__\u001b[0;34m(self, cache_dir, dataset_name, config_name, hash, base_path, info, features, token, use_auth_token, repo_id, data_files, data_dir, storage_options, writer_batch_size, name, **config_kwargs)\u001b[0m\n\u001b[1;32m    369\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m data_dir \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    370\u001b[0m     config_kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdata_dir\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m data_dir\n\u001b[0;32m--> 371\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconfig, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconfig_id \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_create_builder_config\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    372\u001b[0m \u001b[43m    \u001b[49m\u001b[43mconfig_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconfig_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    373\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcustom_features\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfeatures\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    374\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mconfig_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    375\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    377\u001b[0m \u001b[38;5;66;03m# prepare info: DatasetInfo are a standardized dataclass across all datasets\u001b[39;00m\n\u001b[1;32m    378\u001b[0m \u001b[38;5;66;03m# Prefill datasetinfo\u001b[39;00m\n\u001b[1;32m    379\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m info \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    380\u001b[0m     \u001b[38;5;66;03m# TODO FOR PACKAGED MODULES IT IMPORTS DATA FROM src/packaged_modules which doesn't make sense\u001b[39;00m\n",
-      "File \u001b[0;32m~/opt/anaconda3/envs/sta663/lib/python3.12/site-packages/datasets/builder.py:592\u001b[0m, in \u001b[0;36mDatasetBuilder._create_builder_config\u001b[0;34m(self, config_name, custom_features, **config_kwargs)\u001b[0m\n\u001b[1;32m    590\u001b[0m     builder_config \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbuilder_configs\u001b[38;5;241m.\u001b[39mget(config_name)\n\u001b[1;32m    591\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m builder_config \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mBUILDER_CONFIGS:\n\u001b[0;32m--> 592\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m    593\u001b[0m             \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mBuilderConfig \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mconfig_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m not found. Available: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mlist\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbuilder_configs\u001b[38;5;241m.\u001b[39mkeys())\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    594\u001b[0m         )\n\u001b[1;32m    596\u001b[0m \u001b[38;5;66;03m# if not using an existing config, then create a new config on the fly\u001b[39;00m\n\u001b[1;32m    597\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m builder_config:\n",
-      "\u001b[0;31mValueError\u001b[0m: BuilderConfig 'home_values' not found. Available: ['home_value_forecasts', 'new_constructions', 'for_sale_listings', 'rentals', 'sales']"
+      "File \u001b[0;32m~/opt/anaconda3/envs/sta663/lib/python3.12/site-packages/datasets/builder.py:382\u001b[0m, in \u001b[0;36mDatasetBuilder.__init__\u001b[0;34m(self, cache_dir, dataset_name, config_name, hash, base_path, info, features, token, use_auth_token, repo_id, data_files, data_dir, storage_options, writer_batch_size, name, **config_kwargs)\u001b[0m\n\u001b[1;32m    379\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m info \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    380\u001b[0m     \u001b[38;5;66;03m# TODO FOR PACKAGED MODULES IT IMPORTS DATA FROM src/packaged_modules which doesn't make sense\u001b[39;00m\n\u001b[1;32m    381\u001b[0m     info \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mget_exported_dataset_info()\n\u001b[0;32m--> 382\u001b[0m     info\u001b[38;5;241m.\u001b[39mupdate(\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_info\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m)\n\u001b[1;32m    383\u001b[0m info\u001b[38;5;241m.\u001b[39mbuilder_name \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mname\n\u001b[1;32m    384\u001b[0m info\u001b[38;5;241m.\u001b[39mdataset_name \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdataset_name\n",
+      "File \u001b[0;32m~/.cache/huggingface/modules/datasets_modules/datasets/misikoff--zillow/d642880e153f01354c57f69b68ea9e02d46260977e73b26b4c4853d95d4fccac/zillow.py:266\u001b[0m, in \u001b[0;36mNewDataset._info\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    234\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconfig\u001b[38;5;241m.\u001b[39mname \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhome_values\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m    235\u001b[0m     features \u001b[38;5;241m=\u001b[39m datasets\u001b[38;5;241m.\u001b[39mFeatures(\n\u001b[1;32m    236\u001b[0m         {\n\u001b[1;32m    237\u001b[0m             \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mRegion ID\u001b[39m\u001b[38;5;124m\"\u001b[39m: datasets\u001b[38;5;241m.\u001b[39mValue(dtype\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstring\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28mid\u001b[39m\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mRegion ID\u001b[39m\u001b[38;5;124m\"\u001b[39m),\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    260\u001b[0m         }\n\u001b[1;32m    261\u001b[0m     )\n\u001b[1;32m    262\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m datasets\u001b[38;5;241m.\u001b[39mDatasetInfo(\n\u001b[1;32m    263\u001b[0m     \u001b[38;5;66;03m# This is the description that will appear on the datasets page.\u001b[39;00m\n\u001b[1;32m    264\u001b[0m     description\u001b[38;5;241m=\u001b[39m_DESCRIPTION,\n\u001b[1;32m    265\u001b[0m     \u001b[38;5;66;03m# This defines the different columns of the dataset and their types\u001b[39;00m\n\u001b[0;32m--> 266\u001b[0m     features\u001b[38;5;241m=\u001b[39m\u001b[43mfeatures\u001b[49m,  \u001b[38;5;66;03m# Here we define them above because they are different between the two configurations\u001b[39;00m\n\u001b[1;32m    267\u001b[0m     \u001b[38;5;66;03m# If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and\u001b[39;00m\n\u001b[1;32m    268\u001b[0m     \u001b[38;5;66;03m# specify them. They'll be used if as_supervised=True in builder.as_dataset.\u001b[39;00m\n\u001b[1;32m    269\u001b[0m     \u001b[38;5;66;03m# supervised_keys=(\"sentence\", \"label\"),\u001b[39;00m\n\u001b[1;32m    270\u001b[0m     \u001b[38;5;66;03m# Homepage of the dataset for documentation\u001b[39;00m\n\u001b[1;32m    271\u001b[0m     homepage\u001b[38;5;241m=\u001b[39m_HOMEPAGE,\n\u001b[1;32m    272\u001b[0m     \u001b[38;5;66;03m# License for the dataset if available\u001b[39;00m\n\u001b[1;32m    273\u001b[0m     license\u001b[38;5;241m=\u001b[39m_LICENSE,\n\u001b[1;32m    274\u001b[0m     \u001b[38;5;66;03m# Citation for the dataset\u001b[39;00m\n\u001b[1;32m    275\u001b[0m     citation\u001b[38;5;241m=\u001b[39m_CITATION,\n\u001b[1;32m    276\u001b[0m )\n",
+      "\u001b[0;31mUnboundLocalError\u001b[0m: cannot access local variable 'features' where it is not associated with a value"
      ]
     }
    ],
    "source": [
     "configs = [\n",
-    "    \"home_value_forecasts\",\n",
-    "    \"new_constructions\",\n",
-    "    \"for_sale_listings\",\n",
-    "    \"rentals\",\n",
-    "    \"sales\",\n",
-    "    \"home_values\",\n",
+    "    # \"home_value_forecasts\",\n",
+    "    # \"new_constructions\",\n",
+    "    # \"for_sale_listings\",\n",
+    "    # \"rentals\",\n",
+    "    # \"sales\",\n",
+    "    # \"home_values\",\n",
     "    \"days_on_market\",\n",
     "]\n",
     "for config in configs:\n",