claritystorm/fema-nfip-flood-insurance-claims

FEMA NFIP Redacted Claims v3 — free sample

This free 1,000-row sample spans all 49 loss years 1978–2026. The complete ClarityStorm snapshot contains 2,725,989 records through 2026-09-07, as of 2026-09-08, in CSV and Parquet for $99 once. Future updates are not included. The underlying FEMA source is free.

All 84 agency fields are preserved, plus totalpaidnominal, paymentstatus and coordinatestatus. Native camelCase names replace the old schema. The sample selects evenly spaced IDs within each year; it is not statistically representative. Rows are redacted claims transactions, not unique properties or all paid claims.

A total is null if any of the three gross payment components is missing. Complete source totals include 2,117,326 positive, 41,505 zero and 86 negative values; 567,072 totals are incomplete. Monetary values are nominal dollars. Net-payment and recovery fields have separate meanings. No ZIP risk score or exposure-based risk rate is provided.

62,433 county codes and 41,493 coordinate pairs are missing. 55,827 ZIPs are empty and 303 others have irregular shapes. One state is empty and 16,441 contain UN. Every city field says Currently Unavailable. Coordinates are rounded to one decimal place and may land in the wrong county/state. They are not property locations. ratedFloodZone and floodZoneCurrent are separate fields; respectively 139,030 and 1,949,806 values are missing. No missing geography or flood zones have been inferred. The latest year is partial and claims can be revised.

This sample CSV quotes empty strings and leaves nulls unquoted. The following reader preserves those distinctions and all codes as text. Use the full Parquet for typed exact-decimal analysis.

import pyarrow as pa
import pyarrow.csv as csv
import csv as standard_csv
with open("sample_1000.csv", newline="") as stream:
    names = next(standard_csv.reader(stream))
df = csv.read_csv("sample_1000.csv", convert_options=csv.ConvertOptions(
    column_types={name: pa.string() for name in names},
    null_values=[""], strings_can_be_null=True, quoted_strings_can_be_null=False))
assert df.num_rows == 1000
print(df.select(["id", "yearOfLoss", "state", "payment_status"]).slice(0, 5))

The full source CSV and Parquet were reconciled by id across all 84 fields. Independent source/persisted checks cover row identity, dates, 49 annual exact financial totals and all delivered values. Source accuracy is not independently certified. The full package includes the agency dictionary, source hashes and QA.

This product uses the Federal Emergency Management Agency’s OpenFEMA API, but is not endorsed by FEMA. The Federal Government or FEMA cannot vouch for the data or analyses derived from these data after the data have been retrieved from the Agency's website(s). This is not an official federal report. OpenFEMA terms.

Retrieved September 19, 2026. Use for statistical research or reporting. OpenFEMA prohibits attempting to reidentify individuals or making determinations affecting an individual’s rights or eligibility for benefits.