Python Day 18 – Data Wrangling with Pandas

Welcome to Day 18 of the Python Programming Series

In this video, you’ll learn how to wrangle and clean real-world datasets using Python and Pandas. Data Wrangling is the process of transforming raw data into a clean and usable format — a critical step before performing analysis or machine learning.

This session focuses on practical techniques to fix, format, and transform data with ease.

✅ What You Will Learn
What is data wrangling and why it matters

Identifying and handling missing values

Replacing, imputing, or dropping nulls

Standardizing column names and fixing data types

Removing duplicate rows

String operations and text cleaning

Handling categorical values (label encoding, mapping)

Parsing dates and extracting components (day, month, year)

Merging, joining, and concatenating multiple datasets

Reindexing, reshaping, and melting dataframes

Preparing datasets for analysis or machine learning

Technologies Used
Python 3

Pandas

Jupyter Notebook or Google Colab

Perfect For
Anyone working with messy or unstructured data who wants to clean and prepare data efficiently for analytics, dashboards, or machine learning.

Resources
Practice Notebook: https://colab.research.google.com/drive/1puzFKRcLEqj-y9lVuVn4WpPrCKzrE8kJ?usp=sharing

Dataset : https://drive.google.com/file/d/1Vr0GhmIGT6YUxKF6xBFp95dvp-2l0z0O/view?usp=sharing
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Видео Python Day 18 – Data Wrangling with Pandas канала Abhishek Mishra