A Pyspark companion for data science tasks.
Project description
Pyspark DS Toolbox
The objective of the package is to provide a set of tools that helps the daily work of data science with spark. The documentation can be found here. Feel free to contribute :)
Installation
Directly from PyPi:
pip install pyspark-ds-toolbox
or from github, note that installing from github will install the latest development version:
pip install git+https://github.com/viniciusmsousa/pyspark-ds-toolbox.git
Organization
The package is currently organized in a structure based on the nature of the task, such as data wrangling, model/prediction evaluation, and so on.
pyspark_ds_toolbox # Main Package
├─ causal_inference # Sub-package dedicated to Causal Inferece
│ ├─ diff_in_diff.py
│ └─ ps_matching.py
├─ ml # Sub-package dedicated to ML
│ ├─ data_prep # Sub-package to ML data preparation tools
│ │ ├─ class_weights.py
│ │ └─ features_vector.py
│ ├─ classification # Sub-package decidated to classification tasks
│ │ ├─ eval.py
│ │ └─ baseline_classifiers.py
│ └─ feature_importance # Sub-package with feature importance tools
│ ├─ native_spark.py
│ └─ shap_values.py
├─ wrangling # Sub-package decidated to data wrangling tasks
│ ├─ reshape.py
│ └─ data_quality.py
└─ stats # Sub-package dedicated to basic statistic functionalities
└─ association.py
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