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You're reading from  Essential PySpark for Scalable Data Analytics

Product typeBook
Published inOct 2021
Reading LevelBeginner
PublisherPackt
ISBN-139781800568877
Edition1st Edition
Languages
Python
Tools
PySpark
Concepts
Big Data
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Author (1)
Sreeram Nudurupati
Sreeram Nudurupati
author image
Sreeram Nudurupati

Sreeram Nudurupati is a data analytics professional with years of experience in designing and optimizing data analytics pipelines at scale. He has a history of helping enterprises, as well as digital natives, build optimized analytics pipelines by using the knowledge of the organization, infrastructure environment, and current technologies.
Read more about Sreeram Nudurupati

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Considerations for PySpark to pandas conversion

This section will introduce pandas, demonstrate the differences between pandas and PySpark, and the considerations that need to be kept in mind while converting datasets between PySpark and pandas.

Introduction to pandas

pandas is one of the most widely used open source data analysis libraries for Python. It contains a diverse set of utilities for processing, manipulating, cleaning, munging, and wrangling data. pandas is much easier to work with than Pythons lists, dictionaries, and loops. In some ways, pandas is like other statistical data analysis tools such as R or SPSS, which makes it very popular with data science and machine learning enthusiasts.

The primary abstractions of pandas are Series and DataFrames, with the former essentially being a one-dimensional array and the latter a two-dimensional array. One of the fundamental differences between pandas and PySpark is that pandas represents its datasets as one- and two-dimensional...

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Essential PySpark for Scalable Data Analytics
Published in: Oct 2021Publisher: PacktISBN-13: 9781800568877
© 2021 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Sreeram Nudurupati

Sreeram Nudurupati is a data analytics professional with years of experience in designing and optimizing data analytics pipelines at scale. He has a history of helping enterprises, as well as digital natives, build optimized analytics pipelines by using the knowledge of the organization, infrastructure environment, and current technologies.
Read more about Sreeram Nudurupati

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