fix: regiontype to region type and use categories instead of strings where possible

checker.ipynb

@@ -0,0 +1,412 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# import json as pandas\n",
+ "import pandas as pd"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 27,
+ "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>Home Type</th>\n",
+ " <th>State</th>\n",
+ " <th>Metro</th>\n",
+ " <th>State Code FIPS</th>\n",
+ " <th>Municipal Code FIPS</th>\n",
+ " <th>Date</th>\n",
+ " <th>Rent (Smoothed)</th>\n",
+ " <th>Rent (Smoothed) (Seasonally Adjusted)</th>\n",
+ " <th>City</th>\n",
+ " <th>County</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>66</td>\n",
+ " <td>146</td>\n",
+ " <td>Ada County</td>\n",
+ " <td>county</td>\n",
+ " <td>all homes plus multifamily</td>\n",
+ " <td>Ada County</td>\n",
+ " <td>Boise City, ID</td>\n",
+ " <td>16.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>2015-01-31</td>\n",
+ " <td>927.493763</td>\n",
+ " <td>927.493763</td>\n",
+ " <td>None</td>\n",
+ " <td>Ada County</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>66</td>\n",
+ " <td>146</td>\n",
+ " <td>Ada County</td>\n",
+ " <td>county</td>\n",
+ " <td>all homes plus multifamily</td>\n",
+ " <td>Ada County</td>\n",
+ " <td>Boise City, ID</td>\n",
+ " <td>16.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>2015-02-28</td>\n",
+ " <td>931.690623</td>\n",
+ " <td>931.690623</td>\n",
+ " <td>None</td>\n",
+ " <td>Ada County</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>66</td>\n",
+ " <td>146</td>\n",
+ " <td>Ada County</td>\n",
+ " <td>county</td>\n",
+ " <td>all homes plus multifamily</td>\n",
+ " <td>Ada County</td>\n",
+ " <td>Boise City, ID</td>\n",
+ " <td>16.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>2015-03-31</td>\n",
+ " <td>932.568601</td>\n",
+ " <td>932.568601</td>\n",
+ " <td>None</td>\n",
+ " <td>Ada County</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>66</td>\n",
+ " <td>146</td>\n",
+ " <td>Ada County</td>\n",
+ " <td>county</td>\n",
+ " <td>all homes plus multifamily</td>\n",
+ " <td>Ada County</td>\n",
+ " <td>Boise City, ID</td>\n",
+ " <td>16.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>2015-04-30</td>\n",
+ " <td>933.148134</td>\n",
+ " <td>933.148134</td>\n",
+ " <td>None</td>\n",
+ " <td>Ada County</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>66</td>\n",
+ " <td>146</td>\n",
+ " <td>Ada County</td>\n",
+ " <td>county</td>\n",
+ " <td>all homes plus multifamily</td>\n",
+ " <td>Ada County</td>\n",
+ " <td>Boise City, ID</td>\n",
+ " <td>16.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>2015-05-31</td>\n",
+ " <td>941.045724</td>\n",
+ " <td>941.045724</td>\n",
+ " <td>None</td>\n",
+ " <td>Ada County</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",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1258735</th>\n",
+ " <td>857850</td>\n",
+ " <td>713</td>\n",
+ " <td>Cherry Hill</td>\n",
+ " <td>city</td>\n",
+ " <td>all homes plus multifamily</td>\n",
+ " <td>Camden County</td>\n",
+ " <td>Philadelphia-Camden-Wilmington, PA-NJ-DE-MD</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>2023-08-31</td>\n",
+ " <td>2291.604800</td>\n",
+ " <td>2244.961006</td>\n",
+ " <td>Cherry Hill</td>\n",
+ " <td>None</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1258736</th>\n",
+ " <td>857850</td>\n",
+ " <td>713</td>\n",
+ " <td>Cherry Hill</td>\n",
+ " <td>city</td>\n",
+ " <td>all homes plus multifamily</td>\n",
+ " <td>Camden County</td>\n",
+ " <td>Philadelphia-Camden-Wilmington, PA-NJ-DE-MD</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>2023-09-30</td>\n",
+ " <td>2296.188906</td>\n",
+ " <td>2254.213172</td>\n",
+ " <td>Cherry Hill</td>\n",
+ " <td>None</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1258737</th>\n",
+ " <td>857850</td>\n",
+ " <td>713</td>\n",
+ " <td>Cherry Hill</td>\n",
+ " <td>city</td>\n",
+ " <td>all homes plus multifamily</td>\n",
+ " <td>Camden County</td>\n",
+ " <td>Philadelphia-Camden-Wilmington, PA-NJ-DE-MD</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>2023-10-31</td>\n",
+ " <td>2292.270938</td>\n",
+ " <td>2261.540446</td>\n",
+ " <td>Cherry Hill</td>\n",
+ " <td>None</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1258738</th>\n",
+ " <td>857850</td>\n",
+ " <td>713</td>\n",
+ " <td>Cherry Hill</td>\n",
+ " <td>city</td>\n",
+ " <td>all homes plus multifamily</td>\n",
+ " <td>Camden County</td>\n",
+ " <td>Philadelphia-Camden-Wilmington, PA-NJ-DE-MD</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>2023-11-30</td>\n",
+ " <td>2253.417140</td>\n",
+ " <td>2257.956024</td>\n",
+ " <td>Cherry Hill</td>\n",
+ " <td>None</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1258739</th>\n",
+ " <td>857850</td>\n",
+ " <td>713</td>\n",
+ " <td>Cherry Hill</td>\n",
+ " <td>city</td>\n",
+ " <td>all homes plus multifamily</td>\n",
+ " <td>Camden County</td>\n",
+ " <td>Philadelphia-Camden-Wilmington, PA-NJ-DE-MD</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>2023-12-31</td>\n",
+ " <td>2280.830303</td>\n",
+ " <td>2280.830303</td>\n",
+ " <td>Cherry Hill</td>\n",
+ " <td>None</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "<p>1258740 rows × 14 columns</p>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " Region ID Size Rank Region Region Type \\\n",
+ "0 66 146 Ada County county \n",
+ "1 66 146 Ada County county \n",
+ "2 66 146 Ada County county \n",
+ "3 66 146 Ada County county \n",
+ "4 66 146 Ada County county \n",
+ "... ... ... ... ... \n",
+ "1258735 857850 713 Cherry Hill city \n",
+ "1258736 857850 713 Cherry Hill city \n",
+ "1258737 857850 713 Cherry Hill city \n",
+ "1258738 857850 713 Cherry Hill city \n",
+ "1258739 857850 713 Cherry Hill city \n",
+ "\n",
+ " Home Type State \\\n",
+ "0 all homes plus multifamily Ada County \n",
+ "1 all homes plus multifamily Ada County \n",
+ "2 all homes plus multifamily Ada County \n",
+ "3 all homes plus multifamily Ada County \n",
+ "4 all homes plus multifamily Ada County \n",
+ "... ... ... \n",
+ "1258735 all homes plus multifamily Camden County \n",
+ "1258736 all homes plus multifamily Camden County \n",
+ "1258737 all homes plus multifamily Camden County \n",
+ "1258738 all homes plus multifamily Camden County \n",
+ "1258739 all homes plus multifamily Camden County \n",
+ "\n",
+ " Metro State Code FIPS \\\n",
+ "0 Boise City, ID 16.0 \n",
+ "1 Boise City, ID 16.0 \n",
+ "2 Boise City, ID 16.0 \n",
+ "3 Boise City, ID 16.0 \n",
+ "4 Boise City, ID 16.0 \n",
+ "... ... ... \n",
+ "1258735 Philadelphia-Camden-Wilmington, PA-NJ-DE-MD NaN \n",
+ "1258736 Philadelphia-Camden-Wilmington, PA-NJ-DE-MD NaN \n",
+ "1258737 Philadelphia-Camden-Wilmington, PA-NJ-DE-MD NaN \n",
+ "1258738 Philadelphia-Camden-Wilmington, PA-NJ-DE-MD NaN \n",
+ "1258739 Philadelphia-Camden-Wilmington, PA-NJ-DE-MD NaN \n",
+ "\n",
+ " Municipal Code FIPS Date Rent (Smoothed) \\\n",
+ "0 1.0 2015-01-31 927.493763 \n",
+ "1 1.0 2015-02-28 931.690623 \n",
+ "2 1.0 2015-03-31 932.568601 \n",
+ "3 1.0 2015-04-30 933.148134 \n",
+ "4 1.0 2015-05-31 941.045724 \n",
+ "... ... ... ... \n",
+ "1258735 NaN 2023-08-31 2291.604800 \n",
+ "1258736 NaN 2023-09-30 2296.188906 \n",
+ "1258737 NaN 2023-10-31 2292.270938 \n",
+ "1258738 NaN 2023-11-30 2253.417140 \n",
+ "1258739 NaN 2023-12-31 2280.830303 \n",
+ "\n",
+ " Rent (Smoothed) (Seasonally Adjusted) City County \n",
+ "0 927.493763 None Ada County \n",
+ "1 931.690623 None Ada County \n",
+ "2 932.568601 None Ada County \n",
+ "3 933.148134 None Ada County \n",
+ "4 941.045724 None Ada County \n",
+ "... ... ... ... \n",
+ "1258735 2244.961006 Cherry Hill None \n",
+ "1258736 2254.213172 Cherry Hill None \n",
+ "1258737 2261.540446 Cherry Hill None \n",
+ "1258738 2257.956024 Cherry Hill None \n",
+ "1258739 2280.830303 Cherry Hill None \n",
+ "\n",
+ "[1258740 rows x 14 columns]"
+ ]
+ },
+ "execution_count": 27,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# read the data\n",
+ "x = pd.read_json(\"processed/rentals/final5.jsonl\", lines=True)\n",
+ "x"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 28,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "array(['county', 'city', 'zip', 'country', 'msa'], dtype=object)"
+ ]
+ },
+ "execution_count": 28,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# get unique values for column\n",
+ "x[\"Region Type\"].unique()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 29,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "array(['all homes plus multifamily', 'SFR', 'multifamily'], dtype=object)"
+ ]
+ },
+ "execution_count": 29,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "x[\"Home Type\"].unique()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "array(['1-Bedroom', '2-Bedrooms', '3-Bedrooms', '4-Bedrooms',\n",
+ " '5+-Bedrooms', 'All Bedrooms'], dtype=object)"
+ ]
+ },
+ "execution_count": 15,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "x[\"Bedroom Count\"].unique()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "sta663",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.12.2"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

processed/home_values_forecasts/final5.jsonl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:421196e30d457c961a82ab3bfebd47093b01e86e426868435daf6827b86d8529
-size 14018271
+oid sha256:a8627505370927a63475f06adf6470710cf92be0a1a2184497b56e8d00cabd56
+size 14050125

processors/{home_value_forecasts.ipynb → home_values_forecasts.ipynb}

@@ -419,336 +419,19 @@
  },
  {
  "cell_type": "code",
- "execution_count": 4,
+ "execution_count": 1,
  "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>RegionType</th>\n",
- " <th>State</th>\n",
- " <th>City</th>\n",
- " <th>Metro</th>\n",
- " <th>County</th>\n",
- " <th>Date</th>\n",
- " <th>Month Over Month % (Smoothed) (Seasonally Adjusted)</th>\n",
- " <th>Quarter Over Quarter % (Smoothed) (Seasonally Adjusted)</th>\n",
- " <th>Year Over Year % (Smoothed) (Seasonally Adjusted)</th>\n",
- " <th>Month Over Month %</th>\n",
- " <th>Quarter Over Quarter %</th>\n",
- " <th>Year Over Year %</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>0</th>\n",
- " <td>58001</td>\n",
- " <td>30490</td>\n",
- " <td>501</td>\n",
- " <td>zip</td>\n",
- " <td>NY</td>\n",
- " <td>Holtsville</td>\n",
- " <td>New York-Newark-Jersey City, NY-NJ-PA</td>\n",
- " <td>Suffolk County</td>\n",
- " <td>2023-12-31</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>-0.7</td>\n",
- " <td>-0.9</td>\n",
- " <td>0.6</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1</th>\n",
- " <td>58002</td>\n",
- " <td>30490</td>\n",
- " <td>544</td>\n",
- " <td>zip</td>\n",
- " <td>NY</td>\n",
- " <td>Holtsville</td>\n",
- " <td>New York-Newark-Jersey City, NY-NJ-PA</td>\n",
- " <td>Suffolk County</td>\n",
- " <td>2023-12-31</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>-0.7</td>\n",
- " <td>-0.9</td>\n",
- " <td>0.6</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2</th>\n",
- " <td>58196</td>\n",
- " <td>7440</td>\n",
- " <td>1001</td>\n",
- " <td>zip</td>\n",
- " <td>MA</td>\n",
- " <td>Agawam</td>\n",
- " <td>Springfield, MA</td>\n",
- " <td>Hampden County</td>\n",
- " <td>2023-12-31</td>\n",
- " <td>0.4</td>\n",
- " <td>0.9</td>\n",
- " <td>3.2</td>\n",
- " <td>-0.6</td>\n",
- " <td>0.0</td>\n",
- " <td>3.0</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>3</th>\n",
- " <td>58197</td>\n",
- " <td>3911</td>\n",
- " <td>1002</td>\n",
- " <td>zip</td>\n",
- " <td>MA</td>\n",
- " <td>Amherst</td>\n",
- " <td>Springfield, MA</td>\n",
- " <td>Hampshire County</td>\n",
- " <td>2023-12-31</td>\n",
- " <td>0.2</td>\n",
- " <td>0.7</td>\n",
- " <td>2.7</td>\n",
- " <td>-0.6</td>\n",
- " <td>0.0</td>\n",
- " <td>2.9</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>4</th>\n",
- " <td>58198</td>\n",
- " <td>8838</td>\n",
- " <td>1003</td>\n",
- " <td>zip</td>\n",
- " <td>MA</td>\n",
- " <td>Amherst</td>\n",
- " <td>Springfield, MA</td>\n",
- " <td>Hampshire County</td>\n",
- " <td>2023-12-31</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>-0.7</td>\n",
- " <td>0.0</td>\n",
- " <td>3.4</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",
- " </tr>\n",
- " <tr>\n",
- " <th>31849</th>\n",
- " <td>827279</td>\n",
- " <td>7779</td>\n",
- " <td>72405</td>\n",
- " <td>zip</td>\n",
- " <td>AR</td>\n",
- " <td>Jonesboro</td>\n",
- " <td>Jonesboro, AR</td>\n",
- " <td>Craighead County</td>\n",
- " <td>2023-12-31</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>-0.7</td>\n",
- " <td>0.0</td>\n",
- " <td>2.5</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>31850</th>\n",
- " <td>834213</td>\n",
- " <td>30490</td>\n",
- " <td>11437</td>\n",
- " <td>zip</td>\n",
- " <td>NY</td>\n",
- " <td>New York</td>\n",
- " <td>New York-Newark-Jersey City, NY-NJ-PA</td>\n",
- " <td>Queens County</td>\n",
- " <td>2023-12-31</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>-0.7</td>\n",
- " <td>-0.9</td>\n",
- " <td>0.6</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>31851</th>\n",
- " <td>845914</td>\n",
- " <td>6361</td>\n",
- " <td>85288</td>\n",
- " <td>zip</td>\n",
- " <td>AZ</td>\n",
- " <td>Tempe</td>\n",
- " <td>Phoenix-Mesa-Chandler, AZ</td>\n",
- " <td>Maricopa County</td>\n",
- " <td>2023-12-31</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>-1.0</td>\n",
- " <td>0.0</td>\n",
- " <td>4.5</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>31852</th>\n",
- " <td>847854</td>\n",
- " <td>39992</td>\n",
- " <td>20598</td>\n",
- " <td>zip</td>\n",
- " <td>VA</td>\n",
- " <td>Arlington</td>\n",
- " <td>Washington-Arlington-Alexandria, DC-VA-MD-WV</td>\n",
- " <td>Arlington County</td>\n",
- " <td>2023-12-31</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>-0.4</td>\n",
- " <td>0.9</td>\n",
- " <td>1.2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>31853</th>\n",
- " <td>847855</td>\n",
- " <td>30490</td>\n",
- " <td>34249</td>\n",
- " <td>zip</td>\n",
- " <td>FL</td>\n",
- " <td>Sarasota</td>\n",
- " <td>North Port-Sarasota-Bradenton, FL</td>\n",
- " <td>Sarasota County</td>\n",
- " <td>2023-12-31</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>-0.9</td>\n",
- " <td>-0.1</td>\n",
- " <td>5.4</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "<p>31854 rows × 15 columns</p>\n",
- "</div>"
- ],
- "text/plain": [
- " Region ID Size Rank Region RegionType State City \\\n",
- "0 58001 30490 501 zip NY Holtsville \n",
- "1 58002 30490 544 zip NY Holtsville \n",
- "2 58196 7440 1001 zip MA Agawam \n",
- "3 58197 3911 1002 zip MA Amherst \n",
- "4 58198 8838 1003 zip MA Amherst \n",
- "... ... ... ... ... ... ... \n",
- "31849 827279 7779 72405 zip AR Jonesboro \n",
- "31850 834213 30490 11437 zip NY New York \n",
- "31851 845914 6361 85288 zip AZ Tempe \n",
- "31852 847854 39992 20598 zip VA Arlington \n",
- "31853 847855 30490 34249 zip FL Sarasota \n",
- "\n",
- " Metro County \\\n",
- "0 New York-Newark-Jersey City, NY-NJ-PA Suffolk County \n",
- "1 New York-Newark-Jersey City, NY-NJ-PA Suffolk County \n",
- "2 Springfield, MA Hampden County \n",
- "3 Springfield, MA Hampshire County \n",
- "4 Springfield, MA Hampshire County \n",
- "... ... ... \n",
- "31849 Jonesboro, AR Craighead County \n",
- "31850 New York-Newark-Jersey City, NY-NJ-PA Queens County \n",
- "31851 Phoenix-Mesa-Chandler, AZ Maricopa County \n",
- "31852 Washington-Arlington-Alexandria, DC-VA-MD-WV Arlington County \n",
- "31853 North Port-Sarasota-Bradenton, FL Sarasota County \n",
- "\n",
- " Date Month Over Month % (Smoothed) (Seasonally Adjusted) \\\n",
- "0 2023-12-31 NaN \n",
- "1 2023-12-31 NaN \n",
- "2 2023-12-31 0.4 \n",
- "3 2023-12-31 0.2 \n",
- "4 2023-12-31 NaN \n",
- "... ... ... \n",
- "31849 2023-12-31 NaN \n",
- "31850 2023-12-31 NaN \n",
- "31851 2023-12-31 NaN \n",
- "31852 2023-12-31 NaN \n",
- "31853 2023-12-31 NaN \n",
- "\n",
- " Quarter Over Quarter % (Smoothed) (Seasonally Adjusted) \\\n",
- "0 NaN \n",
- "1 NaN \n",
- "2 0.9 \n",
- "3 0.7 \n",
- "4 NaN \n",
- "... ... \n",
- "31849 NaN \n",
- "31850 NaN \n",
- "31851 NaN \n",
- "31852 NaN \n",
- "31853 NaN \n",
- "\n",
- " Year Over Year % (Smoothed) (Seasonally Adjusted) Month Over Month % \\\n",
- "0 NaN -0.7 \n",
- "1 NaN -0.7 \n",
- "2 3.2 -0.6 \n",
- "3 2.7 -0.6 \n",
- "4 NaN -0.7 \n",
- "... ... ... \n",
- "31849 NaN -0.7 \n",
- "31850 NaN -0.7 \n",
- "31851 NaN -1.0 \n",
- "31852 NaN -0.4 \n",
- "31853 NaN -0.9 \n",
- "\n",
- " Quarter Over Quarter % Year Over Year % \n",
- "0 -0.9 0.6 \n",
- "1 -0.9 0.6 \n",
- "2 0.0 3.0 \n",
- "3 0.0 2.9 \n",
- "4 0.0 3.4 \n",
- "... ... ... \n",
- "31849 0.0 2.5 \n",
- "31850 -0.9 0.6 \n",
- "31851 0.0 4.5 \n",
- "31852 0.9 1.2 \n",
- "31853 -0.1 5.4 \n",
- "\n",
- "[31854 rows x 15 columns]"
- ]
- },
- "execution_count": 4,
- "metadata": {},
- "output_type": "execute_result"
+ "ename": "NameError",
+ "evalue": "name 'combined_df' is not defined",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
+ "Cell \u001b[0;32mIn[1], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;66;03m# Adjust columns\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m final_df \u001b[38;5;241m=\u001b[39m \u001b[43mcombined_df\u001b[49m\n\u001b[1;32m 3\u001b[0m final_df \u001b[38;5;241m=\u001b[39m combined_df\u001b[38;5;241m.\u001b[39mdrop(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mStateName\u001b[39m\u001b[38;5;124m\"\u001b[39m, axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m)\n\u001b[1;32m 4\u001b[0m final_df \u001b[38;5;241m=\u001b[39m final_df\u001b[38;5;241m.\u001b[39mrename(\n\u001b[1;32m 5\u001b[0m columns\u001b[38;5;241m=\u001b[39m{\n\u001b[1;32m 6\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCountyName\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCounty\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 11\u001b[0m }\n\u001b[1;32m 12\u001b[0m )\n",
+ "\u001b[0;31mNameError\u001b[0m: name 'combined_df' is not defined"
+ ]
  }
  ],
  "source": [
@@ -760,6 +443,7 @@
  " \"CountyName\": \"County\",\n",
  " \"BaseDate\": \"Date\",\n",
  " \"RegionName\": \"Region\",\n",
+ " \"RegionType\": \"Region Type\",\n",
  " \"RegionID\": \"Region ID\",\n",
  " \"SizeRank\": \"Size Rank\",\n",
  " }\n",
@@ -767,7 +451,7 @@
  "\n",
  "# iterate over rows of final_df and populate State and City columns if the regionType is msa\n",
  "for index, row in final_df.iterrows():\n",
- " if row[\"RegionType\"] == \"msa\":\n",
+ " if row[\"Region Type\"] == \"msa\":\n",
  " regionName = row[\"Region\"]\n",
  " # final_df.at[index, 'Metro'] = regionName\n",
  "\n",

processors/{home_value_forecasts.py → home_values_forecasts.py}

@@ -69,6 +69,7 @@ final_df = final_df.rename(
  "CountyName": "County",
  "BaseDate": "Date",
  "RegionName": "Region",
+ "RegionType": "Region Type",
  "RegionID": "Region ID",
  "SizeRank": "Size Rank",
  }
@@ -76,7 +77,7 @@ final_df = final_df.rename(
 
 # iterate over rows of final_df and populate State and City columns if the regionType is msa
 for index, row in final_df.iterrows():
- if row["RegionType"] == "msa":
+ if row["Region Type"] == "msa":
  regionName = row["Region"]
  # final_df.at[index, 'Metro'] = regionName
 

zillow.py

@@ -88,7 +88,9 @@ class Zillow(datasets.GeneratorBasedBuilder):
  "Region ID": datasets.Value(dtype="string", id="Region ID"),
  "Size Rank": datasets.Value(dtype="int32", id="Size Rank"),
  "Region": datasets.Value(dtype="string", id="Region"),
- "RegionType": datasets.Value(dtype="string", id="RegionType"),
+ "Region Type": datasets.ClassLabel(
+ num_classes=3, names=["zip", "country", "msa"]
+ ),
  "State": datasets.Value(dtype="string", id="State"),
  "City": datasets.Value(dtype="string", id="City"),
  "Metro": datasets.Value(dtype="string", id="Metro"),
@@ -123,9 +125,13 @@ class Zillow(datasets.GeneratorBasedBuilder):
  "Region ID": datasets.Value(dtype="string", id="Region ID"),
  "Size Rank": datasets.Value(dtype="int32", id="Size Rank"),
  "Region": datasets.Value(dtype="string", id="Region"),
- "Region Type": datasets.Value(dtype="string", id="Region Type"),
+ "Region Type": datasets.ClassLabel(
+ num_classes=2, names=["country", "msa"]
+ ),
  "State": datasets.Value(dtype="string", id="State"),
- "Home Type": datasets.Value(dtype="string", id="Home Type"),
+ "Home Type": datasets.ClassLabel(
+ num_classes=3, names=["SFR", "all homes", "condo/co-op only"]
+ ),
  "Date": datasets.Value(dtype="string", id="Date"),
  "Median Sale Price": datasets.Value(
  dtype="float32", id="Median Sale Price"
@@ -142,9 +148,13 @@ class Zillow(datasets.GeneratorBasedBuilder):
  "Region ID": datasets.Value(dtype="string", id="Region ID"),
  "Size Rank": datasets.Value(dtype="int32", id="Size Rank"),
  "Region": datasets.Value(dtype="string", id="Region"),
- "Region Type": datasets.Value(dtype="string", id="Region Type"),
+ "Region Type": datasets.ClassLabel(
+ num_classes=2, names=["country", "msa"]
+ ),
  "State": datasets.Value(dtype="string", id="State"),
- "Home Type": datasets.Value(dtype="string", id="Home Type"),
+ "Home Type": datasets.ClassLabel(
+ num_classes=2, names=["SFR", "all homes"]
+ ),
  "Date": datasets.Value(dtype="string", id="Date"),
  "Median Listing Price": datasets.Value(
  dtype="float32", id="Median Listing Price"
@@ -168,9 +178,14 @@ class Zillow(datasets.GeneratorBasedBuilder):
  "Region ID": datasets.Value(dtype="string", id="Region ID"),
  "Size Rank": datasets.Value(dtype="int32", id="Size Rank"),
  "Region": datasets.Value(dtype="string", id="Region"),
- "Region Type": datasets.Value(dtype="string", id="Region Type"),
+ "Region Type": datasets.ClassLabel(
+ num_classes=5, names=["county", "city", "zip", "country", "msa"]
+ ),
  "State": datasets.Value(dtype="string", id="State"),
- "Home Type": datasets.Value(dtype="string", id="Home Type"),
+ "Home Type": datasets.ClassLabel(
+ num_classes=3,
+ names=["all homes plus multifamily", "SFR", "multifamily"],
+ ),
  "Date": datasets.Value(dtype="string", id="Date"),
  "Rent (Smoothed)": datasets.Value(
  dtype="float32", id="Rent (Smoothed)"
@@ -186,9 +201,14 @@ class Zillow(datasets.GeneratorBasedBuilder):
  "Region ID": datasets.Value(dtype="string", id="Region ID"),
  "Size Rank": datasets.Value(dtype="int32", id="Size Rank"),
  "Region": datasets.Value(dtype="string", id="Region"),
- "Region Type": datasets.Value(dtype="string", id="Region Type"),
+ "Region Type": datasets.ClassLabel(
+ num_classes=2, names=["country", "msa"]
+ ),
  "State": datasets.Value(dtype="string", id="State"),
- "Home Type": datasets.Value(dtype="string", id="Home Type"),
+ "Home Type": datasets.ClassLabel(
+ num_classes=2,
+ names=["SFR", "all homes"],
+ ),
  "Date": datasets.Value(dtype="string", id="Date"),
  "Mean Sale to List Ratio (Smoothed)": datasets.Value(
  dtype="float32", id="Mean Sale to List Ratio (Smoothed)"
@@ -232,9 +252,22 @@ class Zillow(datasets.GeneratorBasedBuilder):
  "Region ID": datasets.Value(dtype="string", id="Region ID"),
  "Size Rank": datasets.Value(dtype="int32", id="Size Rank"),
  "Region": datasets.Value(dtype="string", id="Region"),
- "Region Type": datasets.Value(dtype="string", id="Region Type"),
+ "Region Type": datasets.ClassLabel(num_classes=1, names=["state"]),
  "State": datasets.Value(dtype="string", id="State"),
- "Home Type": datasets.Value(dtype="string", id="Home Type"),
+ "Home Type": datasets.ClassLabel(
+ num_classes=3, names=["all homes (SFR/condo)", "SFR", "condo"]
+ ),
+ "Bedroom Count": datasets.ClassLabel(
+ num_classes=6,
+ names=[
+ "1-Bedroom",
+ "2-Bedrooms",
+ "3-Bedrooms",
+ "4-Bedrooms",
+ "5+-Bedrooms",
+ "All Bedrooms",
+ ],
+ ),
  "Date": datasets.Value(dtype="string", id="Date"),
  "Bottom Tier ZHVI (Smoothed) (Seasonally Adjusted)": datasets.Value(
  dtype="float32",
@@ -261,7 +294,10 @@ class Zillow(datasets.GeneratorBasedBuilder):
  num_classes=2, names=["country", "msa"]
  ),
  "State": datasets.Value(dtype="string", id="State"),
- "Home Type": datasets.Value(dtype="string", id="Home Type"),
+ # "Home Type": datasets.Value(dtype="string", id="Home Type"),
+ "Home Type": datasets.ClassLabel(
+ num_classes=2, names=["SFR", "all homes (SFR + Condo)"]
+ ),
  "Date": datasets.Value(dtype="string", id="Date"),
  "Mean Listings Price Cut Amount (Smoothed)": datasets.Value(
  dtype="float32", id="Mean Listings Price Cut Amount (Smoothed)"
@@ -342,7 +378,7 @@ class Zillow(datasets.GeneratorBasedBuilder):
  "Region ID": data["Region ID"],
  "Size Rank": data["Size Rank"],
  "Region": data["Region"],
- "RegionType": data["RegionType"],
+ "Region Type": data["Region Type"],
  "State": data["State"],
  "City": data["City"],
  "Metro": data["Metro"],
@@ -449,6 +485,7 @@ class Zillow(datasets.GeneratorBasedBuilder):
  "Region Type": data["Region Type"],
  "State": data["State"],
  "Home Type": data["Home Type"],
+ "Bedroom Count": data["Bedroom Count"],
  "Date": data["Date"],
  "Bottom Tier ZHVI (Smoothed) (Seasonally Adjusted)": data[
  "Bottom Tier ZHVI (Smoothed) (Seasonally Adjusted)"