PySpark - How to Add Or Update Multiple Columns in Dataframe

In this tutorial, you will learn " How to Add Or Update Multiple Columns in Dataframe" in PySpark . For this I used PySpark runtime.

ata integrity refers to the quality, consistency, and reliability of data throughout its life cycle. Data engineering pipelines are methods and structures that collect, transform, store, and analyse data from many sources.

If you are working as a PySpark developer, data engineer, data analyst, or data scientist for any organisation requires you to be familiar with dataframes because data manipulation is the act of transforming, cleansing, and organising raw data into a format that can be used for analysis and decision making.

0:00 Introduction 0:21 Import PySpark Libraries and Compute Cluster 1:40 Sample data from DBFS 2:12 Create Spark Session 3:38 Load data from DBFS to PySpark Dataframe 6:05 Add Multiple Columns - SalesAmt and Discount 8:10 Select Specific Columns from PySpark Dataframe 9:45 Update Multiple Columns - SalesAmtDis and DisAmt

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