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Customized data preprocessing functions for frequent tasks.

Project description

klib

Python package PyPI Version Language Downloads Last Commit Activity Code Quality License

klib is a Python library for importing, cleaning, analyzing and preprocessing data. Future versions will include model creation and optimization to provide an end-to-end solution.

Installation

Use the package manager pip to install klib.

pip install klib
pip install --upgrade klib

Usage

import klib

klib.describe # tools for visualizing datasets
- klib.corr_mat() # returns acolor-encoded correlation matrix
- klib.corr_plot() # returns a color-encoded heatmap, ideal for correlations
- klib.missingval_plot() # returns a figure containing information about missing values

klib.clean # tools for cleaning datasets
- klib.data_cleaning() # perform initial datacleaning on a dataset
- klib.convert_datatypes() # converts existing to more efficient dtypes, also called in ".data_cleaning()"
- klib.drop_missing() # drops missing values, also called in ".data_cleaning()"

Examples

klib.corr_plot(df, split='pos') # displaying only positive correlations

Corr Plot Example

klib.missingval_plot(df) # default representation of missing values in a DataFrame

Corr Plot Example

Contributing

Pull requests and ideas are welcome. For major changes or feedback, please open an issue first to discuss what you would like to change.

License

MIT

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