How to Detect and Treat Missing Values in Python | Missing Value Treatment | IvyProSchool

In this video, we'll demonstrate how to find missing values across numerous columns in a DataFrame and treat them with various Pandas methods respectively. Then, we will show how to eliminate such missing values by dropping them or replacing them with aggregate functions like mean, median etc. Eliminating records with numerous missing values, and eliminating columns with a large percentage of missing values. By using those steps, we can lower the number of missing values in our dataset and get the data ready for further analysis.

00:00 Introduction
00:25 Importing packages and dataset
02:20 Checking for missing values
08:22 Replacing null values by mean value
11:31 Dropping rows with multiple null values
17:16 Dropping columns with multiple null values
20:05 Conclusion

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