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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

  1. Install the required dependencies:

    pip install -r requirements.txt

  2. 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)