Unit Testing for Student Code

Description

This repository contains a unit test script (test_code.py) designed to validate code in a Data Science project. The project involves data manipulation and analysis using Python, Pandas, and other relevant libraries.

How to Use

Clone the Repository

Clone this repository into your Google Colab environment:

!git clone https://github.com/Brritany/TestCode.git

Import and Run the Unit Tests

After cloning, import the TestCode class from test_code.py and run the unit tests as follows:

from TestCode.test_code import TestCode
import unittest

suite = unittest.TestLoader().loadTestsFromTestCase(TestCode)
unittest.TextTestRunner().run(suite)

Test Cases

The unit tests include the following:

1. test_discharge_summary: Checks if all 'Discharge summary' records are filtered from NOTEEVENTS.
2. test_merged_data: Confirms whether the columns 'SUBJECT_ID' and 'HADM_ID' exist in the DataFrame, indicating successful merging of NOTEEVENTS, PATIENTS, and ADMISSIONS tables.
3. test_final_admission: Ensures that each 'SUBJECT_ID' appears only once in the final final_admission.csv.
4. test_exclude_newborn: Checks if all newborns have been excluded.
5. test_exclude_dih: Checks if all in-hospital deaths have been excluded.
6. test_final_count: Ensures that the final final_admission.csv has 32,174 records (as per your setup).

Requirements

• Python 3.x
• Pandas

Author

Yong Zhen Huang

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