ICD10CodeLookUp is a Python library that can be used to look up ICD10 Diagnosis Codes.
Project description
README.md
ICD10CodeLookUp is a Python library that can be used to look up ICD10 Diagnosis Codes.
Installation
You can install ICD10CodeLookUp using pip:
pip install ICD10CodeLookUp
Example usage
import pandas as pd
import numpy as np
from ICD10CodeLookUp import DiagnosisCodeLookUp
Create an instance of the ICD10CodeLookUp class
lookup = DiagnosisCodeLookUp()
Search for ICD10 diagnosis codes based on a keyword
keyword = 'heart failure' # Let's use Heart failure as an example keyword
codes = lookup.search_by_keyword(keyword)
print("ICD10 diagnosis codes for keyword '{}': {}".format(keyword, codes))
Retrieve the ICD10 diagnosis code mapping as a dataframe
df_mapping = lookup.get_mapping_dataframe(keyword)
print("\nICD10 diagnosis code Mapping (DataFrame):")
df_mapping
Retrieve the ICD10 diagnosis code mapping as a tuple list
tuple_mapping = lookup.get_mapping_tuple_list(keyword)
print("\nICD10 diagnosis code Mapping Tuple List:")
tuple_mapping
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
ICD10CodeLookUp-0.0.2.tar.gz
(3.2 kB
view details)
Built Distribution
File details
Details for the file ICD10CodeLookUp-0.0.2.tar.gz
.
File metadata
- Download URL: ICD10CodeLookUp-0.0.2.tar.gz
- Upload date:
- Size: 3.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.7
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5b9a49d36ca8e0b901cb5a724130e131ae5b95a9ac0eadb8bb1166fd4c5236b3 |
|
MD5 | d0ac9d9d414d4a7a9aa20db4967ec5b7 |
|
BLAKE2b-256 | 7a370019c43fb9be7b7908618de2558d874e96c7a387c99d406844ecd5bb0729 |
File details
Details for the file ICD10CodeLookUp-0.0.2-py3-none-any.whl
.
File metadata
- Download URL: ICD10CodeLookUp-0.0.2-py3-none-any.whl
- Upload date:
- Size: 3.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.7
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | f57df7548466d0509373dc6bd25fe3b0f40c9d4700b71bdff9026701fc2625ae |
|
MD5 | 74e50ec2f2e974ae603c0ad9ec450c0e |
|
BLAKE2b-256 | e2665d28694eb2b1bf1a0805f1e62d35fe78ea80fdf5360bca02f1164b55bb73 |