📊 Data Analysis Practice
This repository contains my practice work while learning Data Analysis using Python. It includes exercises, notebooks, and experiments using popular data analysis libraries.
The goal of this repository is to improve my skills in data exploration, data cleaning, and analysis.
🛠 Tools & Libraries
Python
NumPy
Pandas
Matplotlib
Seaborn
📂 Repository Structure
data-analysis-practice
│
├── numpy/
│ └── NUmpy.py
│
├── pandas/
│ └── pandas_prac.py
| └──PAndas.py
├── eda-and-small-project/
│ └── Exploratory_Data_Analysis_of_Bank_Customer_Churn
| └──Cleaning.py
| └──EDA_blackfriday.py
├──matplot/
│ └── matplot.py
│
└── datasets/
📚 Topics Covered
NumPy arrays and operations
Data manipulation with Pandas
Handling missing data
Data cleaning techniques
Exploratory Data Analysis (EDA)
Basic data visualization
🎯 Purpose
This repository serves as my practice space for strengthening data analysis fundamentals before moving into Machine Learning projects.
Real-world dataset analysis
Mini data analysis projects