Data Cleaning with Python & Pandas | Complete Tutorial | Data Science Project for Beginners
In this video, we will walk through Data Cleaning in Python Pandas. You will learn to clean the different formats of strings into a proper format, handle missing values, convert the strings with numbers to numeric values, deal with date format, and many more.
This video is designed for data science beginners and enthusiasts alike!
In this tutorial, you’ll learn:
How to identify, handle, and fix missing values in real datasets
Removing duplicates, correcting data types, and transforming messy columns
Using powerful Pandas methods for value replacement, categorical data cleaning
Timestamps:
00:00 Introduction
02:20 Loading a raw dataset
03:55 Detecting and removing duplicates
05:45 Detecting missing values
06:35 Cleaning the name column
09:13 Removing missing values (age column)
12:10 Cleaning categorical data (gender, grade columns)
16:21 Dealing with Score columns (both numeric and categorical)
21:18 Dealing with Dates
26:11 Cleaning again categorical data
28:45 Outro
Ready to build a real data science project? Watch now, and don’t forget to like, comment with your questions, and subscribe for more in-depth Python and data science tutorials!
Github Repository: https://github.com/binary-study/data-...
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