This was made during my final week in the Data Bootcamp

This project uses Google Colab and the pandas library to upload, inspect, and explore a dataset stored in an Excel file. It demonstrates essential data‑analysis techniques such as previewing rows, selecting specific ranges, and isolating individual columns for closer inspection.

Executive Summary

The script introduces a practical workflow for working with tabular data in Python. It begins by uploading an Excel file into Google Colab, loading it into a pandas DataFrame, and then applying common exploratory commands to understand the structure and content of the dataset. Through operations like head(), tail(), iloc, and column selection, the project highlights how pandas enables fast, flexible, and intuitive data exploration.

What the Code Does

• Uploads an Excel file directly into Google Colab

• Loads the file into a pandas DataFrame

• Displays the first and last ten rows for quick inspection

• Extracts a specific row‑and‑column range using .iloc

• Shows a single column (name)

• Displays multiple selected columns (name and mark)

Link to Github: OwenMasterson/Python_Students