18. Modify Existing Column Values in Dataframe | PySpark

PySpark is an Application Programming Interface (API) for Apache Spark in Python . The Apache Spark framework is often used for. Large scale big data processing and machine learning workloads. Apache Spark is a huge improvement in big data processing capabilities from previous frameworks such as Hadoop MapReduce. This is due to its use of RDD’s or Resilient Distributed Datasets.

As greater amounts of data are being generated at rates faster than ever before in history. Skilled individuals are required, who have the ability to handle this data and use it to derive insights and provide value.

In this session, We will teach you how to modify an existing column in a dataframe in pyspark within databricks. Databricks is a cloud-based big data processing platform. It has a community edition which gives you most of the platforms capabilities for free.

Modify column in a dataframe
Modify existing column in a dataframe
Modify existing column values
Modify column
Alter column
Alter values in a column in dataframe
Change values in a column in dataframe pyspark
Modify values in a column in dataframe

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GITHUB REPOSITORY:-
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Mockaroo :-
Tool to create sample data (csv etc..)

What is PySpark Introduction Video :-

Databricks Community Edition Setup Guide (Free Access to PySpark) :-

This video is part of a PySpark Tutorial playlist that will take you from beginner to pro.

✔ Topics You’ll Learn:

Modify column
Edit column
Dataframe
Spark
With column
Withcolumn
withcolumn()
Modify column values
Edit column values
Change column values

Keywords :-

Pyspark
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Apache
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Azure Databricks
Azure Synapse
RDDDataframe
Databricks
Pyspark tutorial GitHub
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Simply learning
Big Data
Using pyspark
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Data with Dominic

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