La méthode simple pour corriger les valeurs manquantes avec Pandas

In this video, you will learn how to clean a dataset using Pandas in Python. We will work with a real-world dataset containing missing values, duplicates, and errors to see how to transform "dirty" data into clean, usable data. The program includes: Detecting missing values Handling outliers Removing duplicates Cleaning columns (age, salary, email, dates) Converting data types 📚 Chapters: 00:00 Introduction 00:20 Downloading Anaconda 01:33 Jupyter Notebook interface 03:29 Loading the data 05:35 Exploring the data 07:54 Handling missing values 30:20 Handling duplicates 33:21 Conclusion This video is for beginners in data analysis as well as anyone wishing to improve the quality of their data. 👉 Subscribe so you don't miss the next video, where we'll see how to analyze data with Pandas. 📌 Link to the previous video (data extraction): https://lnkd.in/e6SvrqKs #Pandas #Python #DataCleaning #DataAnalysis #DataScience #Beginner #Data