Python Pandas Tutorial 5: Handle Missing Data: fillna, dropna, interpolate

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

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[RHCIPHER]

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Thanks very much for this! I'm doing an edX course and I was doing fine until this very topic came up. Your video perfectly cleared everything up which is a great relief!

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I love the way you used the graph/visual to explain the different interpolation techniques!

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[jasonwong]

the threshold parameter is so useful! never heard about this before! thank you!

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[MasterCoder]

Interpolate will definitely boost my kaggle score! Thanks so Much!