nmtc-mapper 0.2.1

Automated NMTC eligibility checker — geocode addresses and check Low-Income Community status using CDFI Fund and Census data

nmtc-mapper 🗺️

Automated NMTC eligibility checker for addresses and census tracts.

Pass a DataFrame of addresses and get back a boolean column for NMTC eligibility, distress level, poverty rate, AMI ratio, and more — using official CDFI Fund and Census Bureau data. No manual lookups required.

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Why nmtc-mapper?

The CDFI Fund provides a manual web tool (CIMS) for checking NMTC eligibility one address at a time. nmtc-mapper automates this — pass 10,000 addresses and get results in seconds, using the same official data source.

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Installation

pip install nmtc-mapper

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Quickstart

from nmtcmapper import NMTCMapper

mapper = NMTCMapper()

# Single address (geocodes automatically)
result = mapper.check_address("1234 S Michigan Ave, Chicago, IL 60605")
result.summary()
print(result.nmtc_eligible)    # True
print(result.distress_level)   # "severe"
print(result.poverty_rate)     # 0.38

# Known census tract (no geocoding needed)
result = mapper.check_tract("17031840100")
print(result.nmtc_eligible)    # True

# Batch — enrich a DataFrame of addresses
import pandas as pd
df = pd.read_csv("projects.csv")   # must have 'address' column
df = mapper.enrich(df, address_col="address")
print(df["nmtc_eligible"].value_counts())
print(df["distress_level"].value_counts())

# If you already have census tract IDs
df = mapper.enrich(df, tract_col="tract_id")

# Summary stats
mapper.eligible_count(df)

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Eligibility Rules (2016-2020 ACS — mandatory since Sept 1, 2024)

A census tract qualifies as a Low-Income Community (LIC) if it meets ANY of:

• Poverty rate >= 20%
• Median Family Income <= 80% of metro/state AMI
• Median Family Income <= 85% of state AMI (high migration rural counties)

Distress levels:

• deep — Poverty >= 40% OR AMI <= 50% OR unemployment >= 2x national rate
• severe — Poverty >= 30% OR AMI <= 60% OR unemployment >= 1.5x national rate
• lic — NMTC eligible (meets LIC criteria)
• ineligible — Does not qualify

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Data Sources

• CDFI Fund 2016-2020 ACS Low-Income Community Eligibility File https://www.cdfifund.gov/research-data
• US Census Bureau Geocoding API (free, no API key required) https://geocoding.geo.census.gov

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Output Columns

After running .enrich(), your DataFrame will have:

• nmtc_eligible (bool)
• distress_level (str: deep / severe / lic / ineligible)
• poverty_rate (float)
• ami_ratio (float)
• unemployment_rate (float)
• is_non_metro (bool)
• severe_distress (bool)
• deep_distress (bool)

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Running Tests

PYTHONPATH=. pytest tests/ -v

24 tests across all modules.

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Who This Is For

• CDEs screening project locations for NMTC eligibility
• CDFI analysts qualifying borrower locations at scale
• Researchers analyzing geographic distribution of LIC tracts
• Anyone replacing manual CIMS lookups with automated Python

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License

MIT 2026 Jaypatel1511