Various code to aid in data science projects for tasks involving data cleaning, ETL, EDA, NLP, viz, feature engineering, feature selection, model training and validation etc.
You can install from PyPI using the pip package manager by running
pip install data-science-toolbox
You can install the latest version by cloning this repo and installing from src
git clone https://github.com/safurrier/data_science_toolbox
cd data_science_toolbox
pip install .
├── README.md
├── data_science_toolbox <- Project source code
│ │
│ ├── gists <- Code gists with commonly used code (change to root
│ │ directory, connect to database, profile data, etc)
│ ├── data_checks <- Code for data checks and assertions
│ ├── io <- Code for input/output utilities
│ ├── etl <- For building reproducible ETL pipelines, including data
│ │ checks and transformers
│ ├── ml <- Machine Learning utility code (feature engineering, etc)
│ ├── pandas <- Pandas related utility code
│ │ ├── analysis
│ │ ├── cleaning
│ │ ├── engineering
│ │ ├── text
│ │ ├── datetime
│ │ ├── optimization
│ │ └── profiling
│ ├── project_utils.py <- For project specific utilities
│ │
│ ├── text <- Code for dealing with text. Includes distributed loading of text corpus,
│ │ entity statement extraction, sentiment analysis, pii removal etc.
│ └── __init__.py <- Makes data_science_toolbox a Python module
├── tests <- Pytest unit tests
├── dist <- tars and whls of version builds
├── LICENSE
├── poetry.lock
└── pyproject.toml