This project is part of my journey to become a data analyst. I wanted to explore real-world datasets and practice the core tools used in data analysis — especially Python, pandas, and Jupyter notebooks.

I chose population data because it's relevant, global, and easy to understand while still offering interesting insights. Through this project, I practiced:

Loading and reading a real CSV dataset

Exploring data using pandas methods like .head(), .info(), .sort_values(), and .sum()

Cleaning and analyzing tabular data to extract meaningful trends

This project was completed using Google Colab and uploaded to GitHub using GitHub Desktop. It is my first complete public data project — and more are coming soon!

data/population.csv — raw dataset

notebooks/population_analysis.ipynb — Jupyter Notebook with pandas code

README.md — project overview and instructions

Loads and explores global population data (CSV)

Displays top 10 most populous countries in 2023

Calculates total world population

Demonstrates real use of pandas for sorting, filtering, and summarizing

Download or clone this repo

Open the notebook in Google Colab or Jupyter Notebook

Upload the population.csv file if prompted

Run the code cells and explore!

Add visualizations (bar chart, pie chart, etc.)

Clean column names more precisely

Create reusable functions for reporting

Made with ❤️ by @persiacooper