Spark DataFrame Transformation Tutorials

This series includes tutorials about how to transform Spark DataFrame. For example, operations about add, remove, rename, change data types to columns. It also shows how to create DataFrame object in memory. 

Spark DataFrame Transformation Tutorials

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This article shows you how to filter NULL/None values from a Spark data frame using Python. Function DataFrame.filter or DataFrame.where can be used to filter out null values.

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This article shows how to change column types of Spark DataFrame using Python. For example, convert StringType to DoubleType, StringType to Integer, StringType to DateType. Follow article  Convert Python Dictionary List to PySpark DataFrame to construct a dataframe.

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This article shows how to add a constant or literal column to Spark data frame using Python.  Follow article  Convert Python Dictionary List to PySpark DataFrame to construct a dataframe. +----------+---+------+ | Category| ID| Value| +----------+---+------+ |Category A| 1| ...

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This article shows how to 'delete' column from Spark data frame using Python.  Follow article  Convert Python Dictionary List to PySpark DataFrame to construct a dataframe. +----------+---+------+ | Category| ID| Value| +----------+---+------+ |Category A| 1| 12.40| |Category B| ...

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Column renaming is a common action when working with data frames. In this article, I will show you how to rename column names in a Spark data frame using Python.  The following code snippet creates a DataFrame from a Python native dictionary list. PySpark SQL types are used to create the ...

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This articles show you how to convert a Python dictionary list to a Spark DataFrame. The code snippets runs on Spark 2.x environments. The input data (dictionary list looks like the following): data = [{"Category": 'Category A', 'ItemID': 1, 'Amount': 12.40}, {"Category": 'Category B' ...

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This article shows how to convert a Python dictionary list to a DataFrame in Spark using Python. data = [{"Category": 'Category A', "ID": 1, "Value": 12.40}, {"Category": 'Category B', "ID": 2, "Value": 30.10}, {"Category": 'Category C', "ID": 3, "Value": 100.01} ] The ...

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In Spark, SparkContext.parallelize function can be used to convert list of objects to RDD and then RDD can be converted to DataFrame object through SparkSession.

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In Spark, it’s easy to convert Spark Dataframe to Pandas dataframe through one line of code: df_pd = df.toPandas() In this page, I am going to show you how to convert a list of PySpark row objects to a Pandas data frame. The following code snippets create a data frame with schema as: root ...

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In Spark, SparkContext.parallelize function can be used to convert Python list to RDD and then RDD can be converted to DataFrame object. The following sample code is based on Spark 2.x. In this page, I am going to show you how to convert the following list to a data frame: data = [('Category A' ...

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