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Datasets:
misikoff
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zillow

Tasks:
Tabular Regression
Time Series Forecasting
Languages: English
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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 to pending, days to close, share of listings with a price cut, and price cuts.
  • for_sale_listings: Median listing price, new listings, and new pending listings.
  • home_values: Zillow Home Value Index (ZHVI) for all homes, mid-tier, bottom-tier, and top-tier homes.
  • home_values_forecasts: Zillow Home Value Forecast (ZHVF) for all homes, mid-tier, bottom-tier, and top-tier homes.
  • new_construction: Median sale price, median sale price per square foot, and sales count.
  • rentals: Zillow Observed Rent Index (ZORI) for all homes, mid-tier, bottom-tier, and top-tier homes.
  • 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

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

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

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.

Example Usage 

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

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