cdfi-data 🏦

ETL pipeline for US Treasury CDFI Fund public datasets.

Download, clean, and analyze Transaction Level Report (TLR), Consumer Loan Report (CLR), and Awards data from the US Department of Treasury's CDFI Fund — in one line of Python.

Why cdfi-data?

The CDFI Fund releases massive public datasets covering millions of loans and investments in low-income communities. But the raw files are messy, inconsistently formatted, and require significant cleaning before analysis. cdfi-data standardizes the entire pipeline.

Installation

pip install cdfidata

Quickstart

from cdfidata import TLRLoader, CLRLoader, AwardsLoader

# Load a single TLR fiscal year (downloads & caches automatically)
tlr = TLRLoader()
df = tlr.load(year=2022)

# Load the full cumulative TLR (FY2020–FY2022), stacked with provenance
cum = tlr.load_cumulative()
# ...or an explicit range:
cum = tlr.load_range(2020, 2022)

# Filter to Illinois
il = tlr.filter_state("IL")

# Filter by loan type and amount
small_biz = tlr.filter_loan_type("Business")
large = tlr.filter_amount(min_amount=500_000)

# Summary stats
tlr.summary()

# Export
tlr.to_csv("cdfi_transactions.csv")
tlr.to_sqlite("cdfi.db", table="tlr")

Caveat — cumulative frames stack overlapping releases. load_cumulative() / load_range() concatenate releases with no dedup: each row carries a source_release column (FY2020/FY2021/FY2022), and releases overlap on fiscal_year (FY2022 restates and expands prior-year data). Filter by source_release and prefer the latest release for a given fiscal year — don't naively aggregate the full frame, or restated rows double-count. Field completeness (rate/term/NAICS) is also era-dependent. See docs/CANONICAL_SCHEMA.md.

Sample Data (No Download Required)

from cdfidata import TLRLoader, CLRLoader, AwardsLoader

tlr = TLRLoader()
df = tlr.load_sample(n=1000)

clr = CLRLoader()
df = clr.load_sample(n=1000)

awards = AwardsLoader()
df = awards.load_sample(n=500)

Datasets Supported

Data Sources

CDFI Fund datasets (TLR, CLR, Awards) come from the US Department of Treasury CDFI Fund: https://www.cdfifund.gov/research-data

All data is released under open government data principles.

Running Tests

PYTHONPATH=. pytest tests/ -v

44 tests across all modules.

Who This Is For

• Impact investors analyzing CDFI loan portfolios
• Academic researchers studying community development finance
• Policy analysts evaluating CDFI Fund program outcomes
• CDFIs benchmarking their own performance against peers
• Anyone who needs clean, analysis-ready CDFI Fund data

License

MIT 2026 Jaypatel1511