Hands-on Data Cleaning Using Pandas in Google Colab

#datascience #tutorial #challenge #python

Data cleaning is one of the most crucial steps in any data science or analytics project. In this challenge, I worked on a real-world dataset from Kaggle with over 100,000 rows, performing various Pandas operations to clean, preprocess, and prepare it for further analysis.

📂 Dataset Details
For this challenge, I selected the E-commerce Sales Dataset from Kaggle containing around 120,000 rows and 12 columns.

It includes data such as:

🧾 Order ID
👤 Customer Name
🛒 Product & Quantity
💰 Sales & Discount
🌍 Region
📅 Order Date
Before Cleaning:

Rows → 120,000
Columns → 12
File format → .csv

⚙️ Tools & Environment
Python 3
Google Colab
Libraries: Pandas, NumPy, Matplotlib