Metadata-Version: 2.1
Name: bae0n-utils
Version: 0.0.17
Summary: Utility functions to be used in Python
Home-page: https://github.com/aeonwilliams/bae0n_utils/blob/main/README.md
Author: Aeon Williams
Author-email: aeonwilliams@gmail.com
License: UNKNOWN
Description: # bae0n_utils
        
        Collection of utility functions to be used in Python. 
        
        ### ActivateCellDoneChime
        #### ex: CellDoneChime()
        Plays a sound effect when a cell is complete. Currently kind of buggy with a failed cell.    
        
        ### ActivateCellFailChime
        #### ex: CellFailChime()
        Plays a sound effect if the cell execution fails.
        
        ### ClearDir
        #### ex: ClearDir('./images')
        Removes all files from a directory.
            
        params:
        - path - The source directory of the images to turn into a gif. Must include preceding ./, should not include ending /
        
        ### MakeGif
        #### ex: MakeGif('./data', './', 'test', 100, 'jpg')
        Turns a directory of images into a gif.
            
        params:
        - source_dir - The source directory of the images to turn into a gif. Must include preceding ./
        - out_dir    - The directory to save the gif to. Must include preceding ./
        - gif_name   - The name of the gif. Do not include filetype.
        - duration   - Number of frames in the gif...I think.
        - file_type  - File extension for the images. Do not include preceding .
        
        ### CorrMatrixAnalysis
        Displays in depth analysis of the correlation between features. Currently only addresses correlation of dependent feature to independent features, but will be updated soon.
        
        params:
        - df          - The dataframe to analyze.
        - dep_feature - The dependent feature.
        
        #### example call:
        df = pd.read_csv('Iris.csv')
        
        CorrMatrixAnalysis(df, 'species')
        <details>
          <summary>Example output</summary>
          
          Features With High Correlation to diagnosis:
            -0.79  - concave points_worst
            -0.78  - perimeter_worst
            -0.78  - concave points_mean
            -0.78  - radius_worst
            -0.74  - perimeter_mean
            -0.73  - area_worst
            -0.73  - radius_mean
            -0.71  - area_mean
            
            Features With Moderate Correlation to diagnosis:
            -0.70  - concavity_mean
            -0.66  - concavity_worst
            -0.60  - compactness_mean
            -0.59  - compactness_worst
            -0.57  - radius_se
            -0.56  - perimeter_se
            -0.55  - area_se
        
            Features With No Correlation to diagnosis:
            -0.29  - compactness_se
            -0.25  - concavity_se
            -0.08  - fractal_dimension_se
             0.07  - smoothness_se
            -0.04  - id
             0.01  - fractal_dimension_mean
             0.01  - texture_se
             0.01  - symmetry_se
        </details>
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3
Description-Content-Type: text/markdown
