Customized data preprocessing functions for frequent tasks.
Project description
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.dist_plot() # returns a distribution plot for every numeric feature
- klib.missingval_plot() # returns a figure containing information about missing values
klib.clean # tools for cleaning datasets
- klib.data_cleaning() # perform datacleaning (drop duplicates & empty rows/columns, adjust dtypes,...) 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) # providing a pd.DataFrame is sufficient, however, plently of settings and options are available
klib.corr_plot(df, split='pos') # displaying only positive correlations
klib.missingval_plot(df) # default representation of missing values in a DataFrame, plenty of settings are available
Contributing
Pull requests and ideas, especially for further functions are welcome. For major changes or feedback, please open an issue first to discuss what you would like to change.
License
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
klib-0.0.69.tar.gz
(13.6 kB
view hashes)
Built Distribution
klib-0.0.69-py3-none-any.whl
(15.6 kB
view hashes)