Join my Academy, learn Data & AI skills and land a job👇 Data cleaning is supposed to be boring and tedious, yet here you'll see real mistakes, debugging, and a practical Python approach that turns theory upside down. In this video, I walk you through real-life data cleaning with Python, tackling messy data issues like duplicates, nulls, wrong data types, and negative values - showing the thought process and debugging you need for effective analysis. 📸 SOCIAL Instagram and TikTok - @Loresowhat @loresowhat 📩 Get in touch: loresowhat@ 🔎 CONTENT 0:00 Introduction to Data Cleaning with Python 1:34 Setting up Google Colab Environment 2:21 Using Synthetic Data for Cleaning 3:44 Initial Data Exploration and Inspection 5:54 Identifying and Removing Duplicate Rows 9:06 Analyzing Numerical Data and Detecting Anomalies 10:16 Handling Negative Values in Data 13:06 Filling Missing Numerical Values Using Mean Autofill 20:57 Converting Data Types for Accuracy 23:44 Summary and Final Recommendations on Data Cleaning #DataCleaning #PythonDataAnalysis #PandasTutorial