Python Pandas Tutorial 5: Handle Missing Data: fillna, dropna, interpolate
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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: https://github.com/codebasics/py/tree/master/pandas/5_handling_missing_data_fillna_dropna_interpolate
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