bae0n-utils 0.0.10

Utility functions to be used in Python

bae0n_utils

Collection of utility functions to be used in Python.

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')

Example output

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