abc-classification

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')