Basic Data Analysis

This project involves practicing basic data analysis using .csv files sourced from Kaggle about students trends. The data has been processed and visualized using Python libraries such as pandas, matplotlib, and seaborn.

The visualizations provide insights by presenting the data in various formats, making it easier to interpret trends and patterns.

What I Learned

Data Visualization: I explored how to transform raw datasets into meaningful visual stories. Visual tools help simplify complex data, making it easier to communicate insights to a non-technical audience.

Using .gitignore: Initially, I accidentally committed my entire virtual environment, which bloated the repo with thousands of unnecessary files. This taught me the importance of .gitignore to keep the repository clean and efficient.

Running the Script

Follow these steps to set up and run the project on your local machine:

Create a Virtual Environment

python3 -m venv env

Activate the Virtual Environment

macOS/Linux:

source env/bin/activate

Windows:

call env\Scripts\activate

Install Dependencies

pip install -r requirements.txt