icd-mappings
This python tool enables a variety of mappings between ICD diagnostic codes (International Classification of Diseases) with a single line of code.
Decision gist · record as of 2026-08-14
Yes. The package is actively maintained, has no known vulnerabilities, low install friction, and solves a real problem in healthcare data workflows. It is well-suited for anyone working with ICD codes in Python, from data analysts to healthcare IT teams. The MIT license poses no restrictions for typical use.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Low friction: pure Python wheel with only importlib-resources as a runtime dependency.
- Active maintenance with a recent release on 2026-04-27 and last commit on 2026-06-25.
License · maintenance · safety
MIT (permissive) — MIT license permits commercial and private use, modification, and distribution with minimal restrictions—suitable for most healthcare applications.
last release 2026-04-27 (109 days) · last repo commit 2026-06-25 · 47 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 210,310 downloads/mo, #9,498 on PyPI
Alternatives
Verify before relying
pip install icd-mappings
from icdmappings import Mapper
mapper = Mapper()
result = mapper.map('29410', source='icd9', target='ccs')
print(result) # '653'- Whether mappings reflect the most current ICD-10 and clinical classification standards beyond the 2026-04-27 extraction date
- Performance characteristics when mapping large batches of codes (thousands or millions)
- Completeness of coverage for all valid ICD-9 and ICD-10 diagnostic codes in the underlying datasets
What it is and what it does
ICD-Mappings is a Python library that translates between ICD diagnostic code systems and clinical classification ontologies. It provides two main classes: Mapper for converting codes between systems (ICD-9 CM to ICD-10 CM, ICD-9 to CCS, ICD-10 to CCSR, and several others), and Validator for checking whether a code is valid within a given ontology. The library handles both single codes and iterables like lists or pandas Series, returning None for unmapped or invalid codes.
The package bundles pre-computed mappings for multiple clinical classification systems including Clinical Classification Software (CCS and CCSR), Chronic Condition Indicators (CCI and CCIR), and Pediatric Complex Chronic Conditions categories. It supports parent-code inference for certain targets (CCI and CCIR) by default, allowing truncated codes to map when all their children agree. Data was last refreshed on 2026-04-27 for ICD-10 chapter and block ranges.
Use it for
- Convert ICD-9 diagnostic codes to ICD-10 equivalents for healthcare data migration or compliance with updated coding standards.
- Classify ICD codes into broader clinical categories (CCS) to aggregate diagnoses for epidemiological analysis or quality reporting.
- Identify chronic conditions from diagnostic codes using CCI or CCIR for risk stratification or comorbidity tracking.
- Validate incoming ICD-9 or ICD-10 diagnostic and procedure codes in healthcare data pipelines before processing.
- Map pediatric diagnoses to complex chronic condition categories for specialized pediatric population studies.
- Batch-process healthcare claims or EHR data to standardize coding across multiple ICD versions.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package is actively maintained, has no known vulnerabilities, low install friction, and solves a real problem in healthcare data workflows. It is well-suited for anyone working with ICD codes in Python, from data analysts to healthcare IT teams. The MIT license poses no restrictions for typical use.
Install
icd-mappings on PyPI
Before you install
Low friction: pure Python wheel with only importlib-resources as a runtime dependency. Active maintenance with a recent release on 2026-04-27 and last commit on 2026-06-25.
License in practice
MIT license permits commercial and private use, modification, and distribution with minimal restrictions—suitable for most healthcare applications.
Quickstart
pip install icd-mappings
from icdmappings import Mapper
mapper = Mapper()
result = mapper.map('29410', source='icd9', target='ccs')
print(result) # '653'Verify before relying
- Whether mappings reflect the most current ICD-10 and clinical classification standards beyond the 2026-04-27 extraction date
- Performance characteristics when mapping large batches of codes (thousands or millions)
- Completeness of coverage for all valid ICD-9 and ICD-10 diagnostic codes in the underlying datasets
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release <4.0,>=3.8 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packageimportlib-resources |
| Maintenance | Actively maintained 109 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 210,310 / month, #9,498 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9 |
Evidence: icd_mappings-0.6.2-py3-none-any.whl
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