Pandas Project for Beginners | CSV Dataset Cleaning & Analysis in Google Colab
In this beginner-friendly Pandas data analysis project, you’ll learn how to load, clean, and analyze an employee dataset (CSV file) step by step in Google Colab.
Pandas is one of the most powerful Python libraries for data analysis, cleaning, and manipulation — making this project perfect for beginners, students, and anyone new to data handling in Python.
You’ll learn essential Pandas functions and practical techniques for real-world data analysis, including:
Reading data with read_csv(),
Exploring data with info(), describe(), head(), tail(),
Adding/removing columns with drop(),
Statistical functions like count(), mean(), and value_counts(),
Grouping data using groupby(),
Handling missing values using isna(), dropna(), fillna(), and bfill(),
Saving cleaned data with to_csv()
⏱️ Timestamps
00:00 - Introduction
00:24 - Loading a CSV File
01:14 - Reading CSV with read_csv()
01:50 - Using head() and tail()
03:15 - Dataset shape and overview
03:38 - info() and describe()
05:52 - Adding and dropping columns
08:20 - Using count() and mean()
09:19 - value_counts()
10:16 - groupby()
11:42 - Handling Missing Data
12:02 - dropna(), fillna(), bfill()
18:38 - Saving with to_csv()
19:43 - Quick Recap
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