Drop rows with missing values with pandas dropna // Python pandas dropna, subset, axis, thresh
Learn how to drop rows with missing values using the Python pandas dropna method. In this video, I'll show you how to drop rows with a missing value in any column as well as how to only drop rows that are missing all column values. Then level up by using pandas to drop missing values in a specific column using the subset property. You can also use pandas dropna subset to drop based on multiple columns by passing a list to subset. I'll demonstrate how to drop columns with missings as well, though using how='any' or how='all' doesn't work as well for columns. Instead, use the property thresh to drop based on a threshold number of missing values. Using Python pandas dropna thresh is a great way to clean out columns with too many missings before doing machine learning problems. Finally, make your changes permanent by switching the pandas dropna inplace property to True. Check out this and other videos in my Pandas Tips series to experience my pandas tutorial and level up your Python pandas programming skills.
0:00 Introduction
0:23 Set up and load data
1:25 Drop rows with ANY missings
2:36 Drop rows with ALL missings
3:30 Level UP! Drop based on one column (subset)
4:38 Drop based on multiple columns
5:43 Drop COLUMNS with missings
7:02 Threshold for missings (thesh)
9:31 Save changes with inplace
10:20 Conclusion
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