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DataWhys API wrapper

Project description

DataWhys Python SDK

DataWhys Python SDK is a python wrapper for the DataWhys API that provides additional functionality such as dataframe ingest and one-off processing

Installation

Use the package manager pip to install datawhys.

pip install datawhys

Dependencies

Install from source

In the mondobrain-python directory (same directory as this README.md file), run this command in your terminal:

pip install -e .

Usage

import datawhys as dw

# Set your credentials
dw.api_key = "<API-KEY>"

# Build a pandas dataframe and store in `df` (not shown)

# Convert your pandas df to a datawhys df
dwf = dw.DataWhysFrame(df)

# Select a column as your outcome column & specify a target class
outcome = dwf["column_name"]

# for a discrete column
outcome.target_class = "Some_modality"

# for a continuous column the value should be `min` or `max`
outcome.target_class = "max"

# Get a dataframe of all columns you want to explor
explorable = dwf[["column_a", "column_b"]]

# Create a solver instance
solver = dw.Solver()

# Fit your data
solver.fit(explorable, outcome)

# Check your results
solver.rule

See documentation and SDK Example.ipynb in the mondobrain-python directory for more in depth examples.

The package includes documentation to provide explanation and examples of usage.

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change. Take a look at CONTRIBUTING.md for more info

Please make sure to update tests as appropriate.

License

MIT

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