Check the setup
- Python 3.10 or newer
- A notebook environment such as Jupyter or Google Colab
- An internet connection
Repeat-sales indexes of U.S. single-family house prices for building local housing-market monitors and regional comparison tools.
From source to product signal
The FHFA House Price Index measures average price changes from repeat mortgage transactions on the same single-family properties. Start with purchase-only monthly series for a few states. The index is not a list of sale prices, and coverage is strongest where Fannie Mae and Freddie Mac purchase or securitize mortgages.
Install the packages, then run the notebook cell.
python -m pip install pandas
import pandas as pd
prices = pd.read_csv("https://www.fhfa.gov/hpi/download/monthly/hpi_master.csv")
state_prices = prices[
(prices["hpi_flavor"] == "purchase-only")
& (prices["frequency"] == "monthly")
& (prices["level"] == "State")
& (prices["place_name"].isin(["California", "Texas", "Florida"]))
].copy()
state_prices["retrieved_at_utc"] = pd.Timestamp.now(tz="UTC")
print(state_prices[["place_name", "yr", "period", "index_nsa", "index_sa"]].tail(24))Test a useful signal
Describe how purchase-only monthly indexes moved for three states over the last two years.
Federal Housing Finance Agency is a government source. Last verified 2026-08-14. Temporal coverage: mid-1970s-present depending on geography and index flavor.