Builds BCG Matrix

BCG, Growth, Share, Matrix, Feature, Importance, Clustering
pip install bcganalysis==1.0.1


BCG Analysis

I built this package with the objective is to measure in a simple, fast, but effective way, how the key features of an app/webpage impact over the conversion.

It a feature importance analysis, using BCG (Growth-Share) matrix.

This analysis helps to identify key features, grouping or clustering them into 4 different categories, as the BCG matrix states (see link at the bottom for more information).

To install the package, run this command in the terminal: pip install bcganalysAis

We are going to see the following example.


Important: in this package version, you have to input a dataframe, having as columns: User - Converted - [Features]

So the first column has the users, the second one is the 1 - 0 binary column stating is the user converted or not, and then all the features.

Input dataframe example:

import pandas as pd
from bcg_analysis import Generate_BCG

# you can find the toy_dataset.csv file in the example folder in the repo
df_example = pd.read_csv('toy_dataset.csv',sep=';')

df = Generate_BCG(df_example)

# generate the plot

# generate the table behind the plot

A deeper explanation

About BCG / Growth-Share matrix

Questions / concact

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