---
language:
- en
license: other
task_categories:
- tabular-regression
- time-series-forecasting
pretty_name: Zillow
description: 'This dataset is comprised of seven different configurations of data
  covering different aspects of the housing market in the United States. All data
  is provided by Zillow. The seven configurations are: home_values_forecasts, new_construction,
  for_sale_listings, rentals, sales, home_values, and days_on_market. Each configuration
  has a different set of features and target variables. The data is provided in JSONL
  format.'
homepage: https://www.zillow.com/research/data/
dataset_info:
- config_name: days_on_market
  features:
  - name: Region ID
    dtype: string
    id: Region ID
  - name: Size Rank
    dtype: int32
    id: Size Rank
  - name: Region
    dtype: string
    id: Region
  - name: Region Type
    dtype:
      class_label:
        names:
          '0': zip
          '1': city
          '2': county
          '3': msa
          '4': state
          '5': country
  - name: State
    dtype: string
    id: State
  - name: Home Type
    dtype:
      class_label:
        names:
          '0': multifamily
          '1': condo/co-op
          '2': SFR
          '3': all homes
          '4': all homes plus multifamily
  - name: Date
    dtype: timestamp[ms]
    id: Date
  - name: Mean Listings Price Cut Amount (Smoothed)
    dtype: float32
    id: Mean Listings Price Cut Amount (Smoothed)
  - name: Percent Listings Price Cut
    dtype: float32
    id: Percent Listings Price Cut
  - name: Mean Listings Price Cut Amount
    dtype: float32
    id: Mean Listings Price Cut Amount
  - name: Percent Listings Price Cut (Smoothed)
    dtype: float32
    id: Percent Listings Price Cut (Smoothed)
  - name: Median Days on Pending (Smoothed)
    dtype: float32
    id: Median Days on Pending (Smoothed)
  - name: Median Days on Pending
    dtype: float32
    id: Median Days on Pending
  splits:
  - name: train
    num_bytes: 50107320
    num_examples: 586714
  download_size: 229118598
  dataset_size: 50107320
- config_name: for_sale_listings
  features:
  - name: Region ID
    dtype: string
    id: Region ID
  - name: Size Rank
    dtype: int32
    id: Size Rank
  - name: Region
    dtype: string
    id: Region
  - name: Region Type
    dtype:
      class_label:
        names:
          '0': county
          '1': city
          '2': zip
          '3': country
          '4': msa
  - name: State
    dtype: string
    id: State
  - name: Home Type
    dtype:
      class_label:
        names:
          '0': all homes
          '1': all homes plus multifamily
          '2': SFR
          '3': condo/co-op
          '4': multifamily
  - name: Date
    dtype: timestamp[ms]
    id: Date
  - name: Median Listing Price
    dtype: float32
    id: Median Listing Price
  - name: Median Listing Price (Smoothed)
    dtype: float32
    id: Median Listing Price (Smoothed)
  - name: New Listings
    dtype: int32
    id: New Listings
  - name: New Listings (Smoothed)
    dtype: int32
    id: New Listings (Smoothed)
  - name: New Pending (Smoothed)
    dtype: int32
    id: New Pending (Smoothed)
  - name: New Pending
    dtype: int32
    id: New Pending
  splits:
  - name: train
    num_bytes: 49412198
    num_examples: 578653
  download_size: 180206592
  dataset_size: 49412198
- config_name: home_values
  features:
  - name: Region ID
    dtype: string
    id: Region ID
  - name: Size Rank
    dtype: int32
    id: Size Rank
  - name: Region
    dtype: string
    id: Region
  - name: Region Type
    dtype:
      class_label:
        names:
          '0': zip
          '1': city
          '2': county
          '3': msa
          '4': state
          '5': country
  - name: State
    dtype: string
    id: State
  - name: Home Type
    dtype:
      class_label:
        names:
          '0': multifamily
          '1': condo/co-op
          '2': SFR
          '3': all homes
          '4': all homes plus multifamily
  - name: Bedroom Count
    dtype:
      class_label:
        names:
          '0': 1-Bedroom
          '1': 2-Bedrooms
          '2': 3-Bedrooms
          '3': 4-Bedrooms
          '4': 5+-Bedrooms
          '5': All Bedrooms
  - name: Date
    dtype: timestamp[ms]
    id: Date
  - name: Bottom Tier ZHVI (Smoothed) (Seasonally Adjusted)
    dtype: float32
    id: Bottom Tier ZHVI (Smoothed) (Seasonally Adjusted)
  - name: Mid Tier ZHVI (Smoothed) (Seasonally Adjusted)
    dtype: float32
    id: Mid Tier ZHVI (Smoothed) (Seasonally Adjusted)
  - name: Top Tier ZHVI (Smoothed) (Seasonally Adjusted)
    dtype: float32
    id: Top Tier ZHVI (Smoothed) (Seasonally Adjusted)
  splits:
  - name: train
    num_bytes: 9377759
    num_examples: 117912
  download_size: 41145800
  dataset_size: 9377759
- config_name: home_values_forecasts
  features:
  - name: Region ID
    dtype: string
    id: Region ID
  - name: Size Rank
    dtype: int32
    id: Size Rank
  - name: Region
    dtype: string
    id: Region
  - name: Region Type
    dtype:
      class_label:
        names:
          '0': county
          '1': city
          '2': zip
          '3': country
          '4': msa
  - name: State
    dtype: string
    id: State
  - name: City
    dtype: string
    id: City
  - name: Metro
    dtype: string
    id: Metro
  - name: County
    dtype: string
    id: County
  - name: Date
    dtype: timestamp[ms]
    id: Date
  - name: Month Over Month % (Smoothed) (Seasonally Adjusted)
    dtype: float32
    id: Month Over Month % (Smoothed) (Seasonally Adjusted)
  - name: Quarter Over Quarter % (Smoothed) (Seasonally Adjusted)
    dtype: float32
    id: Quarter Over Quarter % (Smoothed) (Seasonally Adjusted)
  - name: Year Over Year % (Smoothed) (Seasonally Adjusted)
    dtype: float32
    id: Year Over Year % (Smoothed) (Seasonally Adjusted)
  - name: Month Over Month %
    dtype: float32
    id: Month Over Month %
  - name: Quarter Over Quarter %
    dtype: float32
    id: Quarter Over Quarter %
  - name: Year Over Year %
    dtype: float32
    id: Year Over Year %
  splits:
  - name: train
    num_bytes: 3976869
    num_examples: 31854
  download_size: 14081979
  dataset_size: 3976869
- config_name: new_construction
  features:
  - name: Region ID
    dtype: string
    id: Region ID
  - name: Size Rank
    dtype: int32
    id: Size Rank
  - name: Region
    dtype: string
    id: Region
  - name: Region Type
    dtype:
      class_label:
        names:
          '0': county
          '1': city
          '2': zip
          '3': country
          '4': msa
  - name: State
    dtype: string
    id: State
  - name: Home Type
    dtype:
      class_label:
        names:
          '0': all homes
          '1': all homes plus multifamily
          '2': SFR
          '3': condo/co-op
          '4': multifamily
  - name: Date
    dtype: timestamp[ms]
    id: Date
  - name: Median Sale Price
    dtype: float32
    id: Median Sale Price
  - name: Median Sale Price per Sqft
    dtype: float32
    id: Sale Price per Sqft
  - name: Sales Count
    dtype: int32
    id: Sales Count
  splits:
  - name: train
    num_bytes: 3624631
    num_examples: 49487
  download_size: 10937317
  dataset_size: 3624631
- config_name: rentals
  features:
  - name: Region ID
    dtype: string
    id: Region ID
  - name: Size Rank
    dtype: int32
    id: Size Rank
  - name: Region
    dtype: string
    id: Region
  - name: Region Type
    dtype:
      class_label:
        names:
          '0': county
          '1': city
          '2': zip
          '3': country
          '4': msa
  - name: State
    dtype: string
    id: State
  - name: Home Type
    dtype:
      class_label:
        names:
          '0': all homes
          '1': all homes plus multifamily
          '2': SFR
          '3': condo/co-op
          '4': multifamily
  - name: Date
    dtype: timestamp[ms]
    id: Date
  - name: Rent (Smoothed)
    dtype: float32
    id: Rent (Smoothed)
  - name: Rent (Smoothed) (Seasonally Adjusted)
    dtype: float32
    id: Rent (Smoothed) (Seasonally Adjusted)
  splits:
  - name: train
    num_bytes: 92914681
    num_examples: 1258740
  download_size: 447425069
  dataset_size: 92914681
- config_name: sales
  features:
  - name: Region ID
    dtype: string
    id: Region ID
  - name: Size Rank
    dtype: int32
    id: Size Rank
  - name: Region
    dtype: string
    id: Region
  - name: Region Type
    dtype:
      class_label:
        names:
          '0': county
          '1': city
          '2': zip
          '3': country
          '4': msa
  - name: State
    dtype: string
    id: State
  - name: Home Type
    dtype:
      class_label:
        names:
          '0': all homes
          '1': all homes plus multifamily
          '2': SFR
          '3': condo/co-op
          '4': multifamily
  - name: Date
    dtype: timestamp[ms]
    id: Date
  - name: Mean Sale to List Ratio (Smoothed)
    dtype: float32
    id: Mean Sale to List Ratio (Smoothed)
  - name: Median Sale to List Ratio
    dtype: float32
    id: Median Sale to List Ratio
  - name: Median Sale Price
    dtype: float32
    id: Median Sale Price
  - name: Median Sale Price (Smoothed) (Seasonally Adjusted)
    dtype: float32
    id: Median Sale Price (Smoothed) (Seasonally Adjusted)
  - name: Median Sale Price (Smoothed)
    dtype: float32
    id: Median Sale Price (Smoothed)
  - name: Median Sale to List Ratio (Smoothed)
    dtype: float32
    id: Median Sale to List Ratio (Smoothed)
  - name: '% Sold Below List'
    dtype: float32
    id: '% Sold Below List'
  - name: '% Sold Below List (Smoothed)'
    dtype: float32
    id: '% Sold Below List (Smoothed)'
  - name: '% Sold Above List'
    dtype: float32
    id: '% Sold Above List'
  - name: '% Sold Above List (Smoothed)'
    dtype: float32
    id: '% Sold Above List (Smoothed)'
  - name: Mean Sale to List Ratio
    dtype: float32
    id: Mean Sale to List Ratio
  splits:
  - name: train
    num_bytes: 27088039
    num_examples: 255024
  download_size: 139297577
  dataset_size: 27088039
---

# Housing Data Provided by Zillow
Updated: 2023-02-01

This dataset contains several configs produced based on files available at https://www.zillow.com/research/data/.

# Viewer Notes

Because this repository includes the code used to process the raw Zillow data, the dataset viewer is not enabled. This is because the dataset viewer is not enabled for datasets that run arbitrary python code. For a normal viewer experience, please see the simplified version of this dataset at https://huggingface.co/datasets/misikoff/zillow-viewer. The viewer should be enabled there and the config files should match what is found here.

Supported configs:
- [`days_on_market`](#days-on-market): Days to pending, days to close, share of listings with a price cut, and price cuts.
- [`for_sale_listings`](#for-sale-listings): Median listing price, new listings, and new pending listings.
- [`home_values`](#home-values): Zillow Home Value Index (ZHVI) for all homes, mid-tier, bottom-tier, and top-tier homes.
- [`home_values_forecasts`](#home-values-forecasts): Zillow Home Value Forecast (ZHVF) for all homes, mid-tier, bottom-tier, and top-tier homes.
- [`new_construction`](#new-construction): Median sale price, median sale price per square foot, and sales count.
- [`rentals`](#rentals): Zillow Observed Rent Index (ZORI) for all homes, mid-tier, bottom-tier, and top-tier homes.
- [`sales`](#sales): Median sale price, median sale price per square foot, and sales count.

## DAYS ON MARKET AND PRICE CUTS

Days to Pending: How long it takes homes in a region to change to pending status on Zillow.com after first being shown as for sale. The reported figure indicates the number of days (mean or median) that it took for homes that went pending during the week being reported, to go pending. This differs from the old “Days on Zillow” metric in that it excludes the in-contract period before a home sells.
Days to Close (mean/median): Number of days between the listing going pending and the sale date.
Share of Listings With a Price Cut: The number of unique properties with a list price at the end of the month that’s less than the list price at the beginning of the month, divided by the number of unique properties with an active listing at some point during the month.
Price Cuts: The mean and median price cut for listings in a given region during a given time period, expressed as both dollars ($) and as a percentage (%) of list price.

Base Columns
- `Region ID`: dtype="string", a unique identifier for the region
- `Size Rank`: dtype="int32", a rank of the region's size
- `Region`: dtype="string", the name of the region
- `Region Type`: dtype="class_label", the type of region
  - '0': zip
  - '1': city
  - '2': county
  - '3': msa
  - '4': state
  - '5': country
- `State`: dtype="string", the US state abbreviation for the state containing the region
- `Home Type`: dtype="string", the type of home
  - '0': multifamily
  - '1': condo/co-op
  - '2': SFR
  - '3': all homes
  - '4': all homes plus multifamily
- `Date`: dtype="timestamp[ms]", the date of the last day of the week for this data
  
Value Columns
- `Mean Listings Price Cut Amount (Smoothed)`: dtype="float32"
- `Percent Listings Price Cut`: dtype="float32", The number of unique properties with a list price at the end of the month that’s less than the list price at the beginning of the month, divided by the number of unique properties with an active listing at some point during the month.
- `Mean Listings Price Cut Amount`: dtype="float32"
- `Percent Listings Price Cut (Smoothed)`: dtype="float32"
- `Median Days on Pending (Smoothed)`: dtype="float32", median number of days it takes for homes in a region to change to pending status on Zillow.com after first being shown as for sale. (smoothed)
- `Median Days on Pending`: dtype="float32", median number of days it takes for homes in a region to change to pending status on Zillow.com after first being shown as for sale.

## FOR-SALE LISTINGS

Base Columns
- `Region ID`: dtype="string", a unique identifier for the region
- `Size Rank`: dtype="int32", a rank of the region's size
- `Region`: dtype="string", the name of the region
- `Region Type`: dtype="class_label", the type of region
  - '0': zip
  - '1': city
  - '2': county
  - '3': msa
  - '4': state
- `State`: dtype="string", the US state abbreviation for the state containing the region
- `Home Type`: dtype="string", the type of home
  - '0': all homes
  - '1': all homes plus multifamily
  - '2': SFR
  - '3': condo/co-op
  - '4': multifamily
- `Date`: dtype="timestamp[ms]", the date of the last day of the month for this data
  
Value Columns
- `Median Listing Price`: dtype="float32",  The median price at which homes across various geographies were listed.
- `Median Listing Price (Smoothed)`: dtype="float32",  The median price at which homes across various geographies were listed. (smoothed)
- `New Listings`: dtype="int32", how many new listings have come on the market in a given month
- `New Listings (Smoothed)`: dtype="int32", how many new listings have come on the market in a given month. (smoothed)
- `New Pending (Smoothed)`: dtype="int32", The count of listings that changed from for-sale to pending status on Zillow.com in a given time period. (smoothed)
- `New Pending`: dtype="int32", The count of listings that changed from for-sale to pending status on Zillow.com in a given time period.


## HOME VALUES

<!-- Zillow Home Value Index (ZHVI): A measure of the typical home value and market changes across a given region and housing type. It reflects the typical value for homes in the 35th to 65th percentile range. Available as a smoothed, seasonally adjusted measure and as a raw measure. -->

<!-- Zillow publishes top-tier ZHVI (\$, typical value for homes within the 65th to 95th percentile range for a given region) and bottom-tier ZHVI (\$, typical value for homes within the 5th to 35th percentile range for a given region). -->

<!-- Zillow also publishes ZHVI for all single-family residences (\$, typical value for all single-family homes in a given region), for condo/coops (\$), for all homes with 1, 2, 3, 4 and 5+ bedrooms (\$), and the ZHVI per square foot (\$, typical value of all homes per square foot calculated by taking the estimated home value for each home in a given region and dividing it by the home’s square footage). -->

<!-- Note: Starting with the January 2023 data release, and for all subsequent releases, the full ZHVI time series has been upgraded to harness the power of the neural Zestimate. -->

<!-- More information about what ZHVI is and how it’s calculated is available on this overview page. Here’s a handy ZHVI User Guide for information about properly citing and making calculations with this metric. -->

Base Columns
- `Region ID`: dtype="string", a unique identifier for the region
- `Size Rank`: dtype="int32", a rank of the region's size
- `Region`: dtype="string", the name of the region
- `Region Type`: dtype="class_label", the type of region
  - '0': zip
  - '1': city
  - '2': county
  - '3': msa
  - '4': state
  - '5': country"
- `State`: dtype="string", the US state abbreviation for the state containing the region
- `Home Type`: dtype="class_label", the type of home
  - '0': multifamily
  - '1': condo/co-op
  - '2': SFR
  - '3': all homes
  - '4': all homes plus multifamily
- `Bedroom Count`: dtype="class_label", the number of bedrooms
  - '0': 1-Bedroom
  - '1': 2-Bedrooms
  - '2': 3-Bedrooms
  - '3': 4-Bedrooms
  - '4': 5+-Bedrooms
  - '5': All Bedrooms
- `Date`: dtype="timestamp[ms]", the date of the last day of the month for this data

Value Columns
- `Mid Tier ZHVI (Smoothed) (Seasonally Adjusted)`: dtype="float32",
- `Bottom Tier ZHVI (Smoothed) (Seasonally Adjusted)`: dtype="float32",
- `Top Tier ZHVI (Smoothed) (Seasonally Adjusted)`: dtype="float32",
- `ZHVI`: dtype="float32",
- `Mid Tier ZHVI`: dtype="float32"


## HOME VALUES FORECASTS

<!-- Zillow Home Value Forecast (ZHVF): A month-ahead, quarter-ahead and year-ahead forecast of the Zillow Home Value Index (ZHVI). ZHVF is created using the all homes, mid-tier cut of ZHVI and is available both raw and smoothed, seasonally adjusted. -->

<!-- Note: Starting with the January 2023 forecast (made available in February 2023), Zillow’s Home Value Forecast is based on the upgraded ZHVI that harnesses the power of the neural Zestimate. More information about what ZHVI is and how it’s calculated is available on this overview page. -->

Base Columns
- `Region ID`: dtype="string", a unique identifier for the region
- `Size Rank`: dtype="int32", a rank of the region's size
- `Region`: dtype="string", the name of the region
- `Region Type`: dtype="class_label", the type of region
  - '0': county
  - '1': city
  - '2': zip
  - '3': country
  - '4': msa
- `State`: dtype="string", the US state abbreviation for the state containing the region
- `City`: dtype="string",
- `Metro`: dtype="string",
- `County`: dtype="string",
- `Home Type`: dtype="string", the type of home
- `Date`: dtype="timestamp[ms]", the date of these forecasts

Value Columns
- `Month Over Month % (Smoothed)`: dtype="float32",
- `Quarter Over Quarter % (Smoothed)`: dtype="float32",
- `Year Over Year % (Smoothed)`: dtype="float32"
- `Month Over Month % (Raw)`: dtype="float32"
- `Quarter Over Quarter % (Raw)`: dtype="float32"
- `Year Over Year % (Raw)`: dtype="float32"

## NEW CONSTRUCTION

Base Columns
- `Region ID`: dtype="string", a unique identifier for the region
- `Size Rank`: dtype="int32", a rank of the region's size
- `Region`: dtype="string", the name of the region
- `Region Type`: dtype="class_label", the type of region
  - '0': county
  - '1': city
  - '2': zip
  - '3': country
  - '4': msa
- `State`: dtype="string", the US state abbreviation for the state containing the region
- `Home Type`: dtype="class_label", the type of home
  -  '0': all homes
  -  '1': all homes plus multifamily
  -  '2': SFR
  -  '3': condo/co-op
  -  '4': multifamily
- `Date`: dtype="timestamp[ms]", the date of the last day of the month for this data
  
Value Columns
- `Median Sale Price`: dtype="float32", the median sale price of new construction homes that sold during the month in the specified region
- `Median Sale Price per Sqft`: dtype="float32", the median sale price per square foot of new construction homes that sold during the month in the specified region
- `Sales Count`: dtype="int32", the number of new construction homes that sold during the month in the specified region

## RENTALS

Base Columns
- `Region ID`: dtype="string", a unique identifier for the region
- `Size Rank`: dtype="int32", a rank of the region's size
- `Region`: dtype="string", the name of the region
- `Region Type`: dtype="class_label", the type of region
  - '0': county
  - '1': city
  - '2': zip
  - '3': country
  - '4': msa
- `State`: dtype="string", the US state abbreviation for the state containing the region
- `Home Type`: dtype="string", the type of home
  - '0': all homes
  - '1': all homes plus multifamily
  - '2': SFR
  - '3': condo/co-op
  - '4': multifamily
- `Date`: dtype="timestamp[ms]", the date of the last day of the month for this data

Value Columns
- `Rent (Smoothed)`: dtype="float32", Zillow Observed Rent Index (ZORI): A smoothed measure of the typical observed market rate rent across a given region. ZORI is a repeat-rent index that is weighted to the rental housing stock to ensure representativeness across the entire market, not just those homes currently listed for-rent. The index is dollar-denominated by computing the mean of listed rents that fall into the 40th to 60th percentile range for all homes and apartments in a given region, which is weighted to reflect the rental housing stock.
- `Rent (Smoothed) (Seasonally Adjusted)`: dtype="float32", Zillow Observed Rent Index (ZORI) :A smoothed measure of the typical observed market rate rent across a given region. ZORI is a repeat-rent index that is weighted to the rental housing stock to ensure representativeness across the entire market, not just those homes currently listed for-rent. The index is dollar-denominated by computing the mean of listed rents that fall into the 40th to 60th percentile range for all homes and apartments in a given region, which is weighted to reflect the rental housing stock.

## SALES
<!-- Sale-to-List Ratio (mean/median): Ratio of sale vs. final list price. -->
<!-- Percent of Sales Below/Above List: Share of sales where sale price below/above the final list price; excludes homes sold for exactly the list price.  -->

Base Columns
- `Region ID`: dtype="string", a unique identifier for the region
- `Size Rank`: dtype="int32", a rank of the region's size
- `Region`: dtype="string", the name of the region
- `Region Type`: dtype="class_label", the type of region
  - '0': county
  - '1': city
  - '2': zip
  - '3': country
  - '4': msa
- `State`: dtype="string", the US state abbreviation for the state containing the region
- `Home Type`: dtype="class_label", the type of home
  - '0': all homes
  - '1': all homes plus multifamily
  - '2': SFR
  - '3': condo/co-op
  - '4': multifamily
- `Date`: dtype="timestamp[ms]", the date of the last day of the month for this data

Value Columns 
- `Median Sale Price`: dtype="float32",  The median price at which homes across various geographies were sold.
- `Median Sale Price per Sqft`: dtype="float32"  The median price per square foot at which homes across various geographies were sold.
- `Sales Count`: dtype="int32", The "Sales Count Nowcast" is the estimated number of unique properties that sold during the month after accounting for the latency between when sales occur and when they are reported.

## DEFINITIONS OF HOME TYPES
- all Homes: Zillow defines all homes as single-family, condominium and co-operative homes with a county record. Unless specified, all series cover this segment of the housing stock.
- SFR: single family residence
- condo/co-op: Condominium and co-operative homes.
- Multifamily 5+ units: Units in buildings with 5 or more housing units, that are not condominiums or co-ops.
<!-- - Duplex/Triplex/Quadplex: Housing units in buildings with 2, 3, or 4 housing units. -->

# Example Usage
```python
from datasets import load_dataset

dataset = load_dataset("misikoff/zillow", 'home_values', trust_remote_code=True)
```

## Example Notebook

Linked below is an example notebook that demonstrates usage and analysis of one of the configs of this dataset.

[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1lEPLbWsOKmNBzkPWT30RCBVxhG1LWkGg?usp=sharing)