Introduction

Hands-on Analytics and Visualization of Kaggle’s Public Data (Brazilian E-Commerce Public Dataset by Olist, https://www.kaggle.com/competitions/house-prices-advanced-regression-techniques) to practice Large Customer Data’s handling experience.

Datasets

Brazilian E-Commerce Public Dataset by Olist

Libraries used

Pandas, Matplotlib, Statsmodel, Scikit-learn

Methodology used

RFM (Recency, Frequency, Monetary) Analytics (Scoring, Mining)

Data Pre-Processing

• Categorizing and Adding Features
• Clarifying/Grouping/Choosing the ideal Database to use

Modeling

• K-means Clustering (For categorizing)
• Customer Segmentation

Visualization

Kaggle_Customer_Tableau.pdf

(Link: https://drive.google.com/file/d/1i2cNhqRBEc_ntKzeBWEP0tc_5wVIr5_t/view?usp=sharing)