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Common functionality for data science at ERI

Project description

# ERIPY

This package contains commonly useful functions and modules for data science purposes at Elder Research, Inc.

## Submodules

What is provided here is simply a high-level discussion of what is avilable in eri. For detailed instructions, please refer to the sub-module-level README files, and, of course, the function documentation. If any of the above does not exist, please seek out the author and shame them mercilessly

### eri.clean

Useful functions for cleaning your data (usually assumes pandas data frames).

### eri.config

Shared configuration details.

### eri.html

HTML parsing and munging utilities.

### eri.validate

Useful functions for validating the data we have (often just logging useful facts about a particular dataframe).

## Testing

to test, install pytest and coverage and then run the following:

` python # run all tests coverage run -m pytest `

` python # print coverage statistics coverage report -m `

## Deploying to PyPi

I’m using twine. Instructions are [here](https://github.com/pypa/twine). to summarize, though:

` bash python setup.py sdist bdist_wheel twine upload --repository-url https://test.pypi.org/legacy/ dist/* twine upload --skip-existing dist/* twine upload --skip-existing -r eri dist/* `

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