Skip to content

Latest commit

 

History

History
26 lines (19 loc) · 660 Bytes

File metadata and controls

26 lines (19 loc) · 660 Bytes

This project performs Exploratory Data Analysis (EDA) using Python in a Jupyter Notebook.

The goal of this project is to clean, analyze, and visualize the dataset to uncover patterns, trends, and insights.

Tools & Libraries Used

Python
Pandas
NumPy
Matplotlib
Seaborn
Skitlearn

In this project, I performed:

Data cleaning and preprocessing.
Handling missing values.
Exploratory data analysis (EDA).
Data visualization.
Correlation analysis.
Identification of churn-related patterns.

Future update

Analysis churn using powerBI
Organize the code again to be more readable