In this tutorial we'll learn how to handle missing data in pandas using fillna, interpolate and dropna methods. You can fill missing values using a value or list of values or use one of the interpolation methods. Topics that are covered in this Python Pandas Video: 0:00 Introduction 2:30 Convert string column into the date type 3:15 Use date as an index of dataframe usine set_index() method 4:10 Use fillna() method in dataframe 7:35 Use fillna(method="ffill") method in dataframe 8:57 Use fillna(method="bfill") method in dataframe 9:56 "axis" parameter in fillna() method in dataframe 11:18 "limit" parameter in fillna() method in dataframe 13:46 interpolate() to do interpolation in dataframe 15:34 interpolate() method "time" 16:50 dropna() method Drop all the rows which has "na" in dataframe 17:50 "how" parameter in dropna() method 18:33 "thresh" parameter in dropna() method Code link: Do you want to learn technology from me? Check for my affordable video courses. Popular Playlist: Complete python course: Data science course: Machine learning tutorials: Pandas tutorials: Git github tutorials: Matplotlib course: Data structures course: Data Science Project - Real Estate Price Prediction: To download csv and code for all tutorials: go to , click on a green button to clone or download the entire repository and then go to relevant folder to get access to that specific file. 🌎 My Website For Video Courses: Need help building software or data analytics and AI solutions? My company can help. Click on the Contact button on that website. #️⃣ Social Media #️⃣ 🔗 Discord: 📸 Dhaval's Personal Instagram: 📸 Instagram: 🔊 Facebook: 📝 Linkedin (Personal): 📝 Linkedin (Codebasics): 📱 Twitter: 🔗 Patreon: