library of functions for managing and improving data quality in Datasets
Project description
Data-Quality-Kit
Functional Description
A library of functions for managing and improving data quality in Datasets
Owner
For any bugs or questions, please reach out to Dante Pedrozo
Branching Methodology
This project follows a Git Flow simplified branching methodology
- Master Branch: production code
- Develop Branch: main integration branch for ongoing development. Features and fixes are merged into this branch before reaching master
- Feature Branch: created from develop branch to work on new features
Prerequisites
This project uses:
- Language: Python 3.10
- Libraries:
- pandas
- pytest
- assertpy
How to use it
Install the library
pip install data-quality-kit
Functionalities
- df_is_empty: Check if a DataFrame is empty.
- check_nulls: Checks for null values in a specified column of a DataFrame.
- check_type_format: Check if all non-null entries in a specified column of a DataFrame are of the specified data type.
- check_no_duplicates: Checks for duplicate values in the specified primary key column of a DataFrame.
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