klib 0.0.68

Customized data preprocessing functions for frequent tasks.

klib

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 a color-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 inside ".data_cleaning()"
- klib.drop_missing() # drops missing values, also called in ".data_cleaning()"

Examples

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

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

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