You're reading from The Pandas Workshop

Product typeBook

Published inJun 2022

Reading LevelBeginner

PublisherPackt

ISBN-139781800208933

Edition1st Edition

Languages

Python

Tools

NumPy Pandas

Concepts

Data Science

Authors (4):

Blaine Bateman

Saikat Basak

Thomas V. Joseph

William So

View More author details

Dealing with missing data

You might have already encountered missing data in your studies or career while performing any kind of data analysis. Missing data is a very common issue that you will encounter in most datasets. It's extremely rare to find a "perfect" dataset. Missing data is not just a nuisance. It is a serious problem that you need to account for as it can affect your results.

What is missing data?

Before you can learn how to deal with missing data, first, you need to understand each of its three types:

Missing at Random (MAR): This refers to data that is missing due to other variables you have information about. For example, in a survey, if you found that some specific demographics show a tendency to not reply to a question, then the missing data is considered to be MAR. An easy way to remember this is that if you can explain why the data is missing by using other variables, but not to the value of the variable with missing values itself, then...

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The Pandas Workshop

Published in: Jun 2022Publisher: PacktISBN-13: 9781800208933

Authors (4)

Blaine Bateman

Blaine Bateman has more than 35 years of experience working with various industries from government R&D to startups to $1B public companies. His experience focuses on analytics including machine learning and forecasting. His hands-on abilities include Python and R coding, Keras/Tensorflow, and AWS & Azure machine learning services. As a machine learning consultant, he has developed and deployed actual ML models in industry.
Read more about Blaine Bateman

Saikat Basak

Saikat Basak is a data scientist and a passionate programmer. Having worked with multiple industry leaders, he has a good understanding of problem areas that can potentially be solved using data. Apart from being a data guy, he is also a science geek and loves to explore new ideas in the frontiers of science and technology.
Read more about Saikat Basak

Thomas V. Joseph

Thomas V. Joseph is a data science practitioner, researcher, trainer, mentor, and writer with more than 19 years of experience. He has extensive experience in solving business problems using machine learning toolsets across multiple industry segments.
Read more about Thomas V. Joseph

William So

William So is a Data Scientist with both a strong academic background and extensive professional experience. He is currently the Head of Data Science at Douugh and also a Lecturer for Master of Data Science and Innovation at the University of Technology Sydney. During his career, he successfully covered the end-end spectrum of data analytics from ML to Business Intelligence helping stakeholders derive valuable insights and achieve amazing results that benefits the business. William is a co-author of the "The Applied Artificial Intelligence Workshop" published by Packt.
Read more about William So

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Dealing with missing data

What is missing data?

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Authors (4)

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