A collection of Jupyter notebooks documenting my learning journey in data analysis using Python.
This repository contains step-by-step examples of data cleaning, transformation, visualization, and analysis with popular Python libraries.
data-analysis-notebooks/
├── CSV_Files/ # Sample datasets
├── Images/ # Supporting images
│
├── 01Import_View_csv.ipynb # Importing & viewing CSV data
├── 02Data_Cleaning_Formatting.ipynb # Data cleaning & formatting
├── 03Data_Normalization.ipynb # Normalization techniques
├── 04Bining_data.ipynb # Data binning
├── 05Value_Count.ipynb # Value counts in datasets
├── 06Boxplot_Scatterplot.ipynb # Boxplot & scatterplot visualization
Clone the repository:
git clone https://github.com/pradipNP/data-analysis-notebooks.git
cd data-analysis-notebooks🛠️ Technologies Used
- Python 3.x
- Jupyter Notebook
- Pandas, NumPy
- Matplotlib, Seaborn
📌 Highlights
- 📂 Organized notebooks for progressive learning
- 🧹 Covers data cleaning, formatting, and normalization
- 📊 Demonstrates visualization techniques like boxplots & scatterplots
- 📝 Includes sample CSV files for practice