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A package for ABC classification

Project description

ABC classification library

ABC classification is an inventory categorisation technique. A typical example of ABC classification is the segmentation of products (entity) based on sales (value). The best-selling products that contribute to up to 70% of the total sales belong to cluster A. The products making up the next 20% of sales are in cluster B, whereas the products representing the last 10% of sales, belong to class C. Hence, the pattern is named after the three clusters (ABC).

Example

Installation

pip install abc-classification

Import

from abc_classification.abc_classifier import ABCClassifier

Let's say we have dataframe

product total sold
fade cream 27000
powders 24000
shadows 18000
mascara 16000
lipstick 6000
concealer 5000
sculptors 4000

You can create ABCClasifier object, pass your dataframe to it and call classify method.

abc_clf = ABCClassifier(df)
abc_df = abc_clf.classify('product', 'total sold')

This way you'll get new dataframe with classified products.

product total sold class
fade cream 27000 A
powders 24000 A
shadows 18000 A
mascara 16000 B
lipstick 6000 B
concealer 5000 C
sculptors 4000 C

You also can use brief_abc method to get aggregated information

abc_clf.brief_abc(abc_df)
class total sold
A 69000
B 16000
C 15000

You can plot pareto chart.

from abc_classification.abc_visualiser import pareto_chart


pareto_chart(abc_df, 'total_sold', 'product')

Pareto chart

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