Pandas Data Visualization Guide

An interactive data science portfolio project demonstrating end-to-end data profiling, pivot table transformations, and modern interactive data visualizations using Python.

📊 Project Features

• Dataset Overview: Loading, cleaning, and filtering missing values from raw demographic data.
• Pivot Table Manipulation: Aggregating raw multi-row records into readable structural summaries.
• Interactive Visualizations: Building dynamic, interactive line charts and pie charts using Plotly Express.

📁 Repository Structure

• population_total.csv - The raw global population source dataset.
• 1.Dataset Overview and Making Pivot Table and Data Visulization.ipynb - Data exploration and data preparation.
• Interactive Visualization with pandas .ipynb - Advanced interactive charting workflows.

🚀 How to Run Locally

1. How to Run Locally

git clone https://github.com/lmao2124345/pandas-data-visualization-guide

2. Install the required dependencies:

   pip install -r requirements.txt

3. Launch Jupyter Notebook to view the files:

   jupyter notebook

🛠️ Technologies Used

• Python 3
• Pandas (Data manipulation)
• Plotly Express (Interactive rendering engine)
• OpenPyXL (Excel spreadsheet exporting)