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data-science-toolbox
Advanced tools
Various code to aid in data science projects for tasks involving data cleaning, ETL, EDA, NLP, viz, feature engineering, feature selection, model validation, etc.
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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 using the pip package manager by running
pip install data-science-toolbox
├── 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
FAQs
Various code to aid in data science projects for tasks involving data cleaning, ETL, EDA, NLP, viz, feature engineering, feature selection, model validation, etc.
We found that data-science-toolbox demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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