A library for Criteria related data wrangling.
Project description
Criteria-ETL
This repository contains general tools for Extracting, Transforming and Loading data in Criteria projects.
Structure of the package
transformers
module
columns_base
: scikit-learn compatible classes which transformpandas.DataFrame
's along the columns axis.rows_base
: scikit-learn compatible classes which transformpandas.DataFrame
's along the rows axis.
utils
module
common_func
: miscellaneous functions which might be useful in any project.config
: placeholder for setting-up global variables of the project, used for loading data.dataload
: functions used for loading data. It imports global variables fromconfig
sub-module.display
: functions used for displaying tables and plotting.expansion_func
: functions designed for handling statistical sources which present an expansion factor.
impute
module
model_based
: scikit-learn compatible classes for imputing observations based on predictive models.
Tests
To run the test it is required to install pytest
in your system. You can do it wiht
pip install pytest
Then, from the root directory you can run
pytest
And it will run every test in the tests
directory.
Issues and Pull Request conventions
Issues are the way each user can report bugs, request new features, ask for help, and so on.
When creating a new issue, please add at least one of this four possible tags: bug, documentation, enhancement, or help wanted.
Pull request should reference an Issue in case the motivation for that PR was that Issue.
Any member of the team has access to code reviews and issues. To be notified via e-mail, please click the watch button in the top-right corner of the repository page.
How to Contribute
Code guidelines are taken from PEP 8 and docstring format used is Numpy's.
Project details
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