"sampleData" value is defined using Seq() function with values input. The SparkRenameColumn object is created in which spark session is initiated. Implementing Spark withColumnRenamed method in Databricks This recipe explains the Spark withColumnRenamed method() method and demonstrates the Spark withColumnRenamed with an example. The Apache Spark runs on Hadoop, Kubernetes, Apache Mesos, standalone in the cloud, and can access diverse data sources. Apache Spark achieves high performance for both the batch and the streaming data using a state-of-the-art DAG scheduler, the query optimizer, and a physical execution engine. Spark provides the interface for entire programming clusters with implicit data parallelism and fault tolerance. Apache Spark is the open-source unified analytics engine for large-scale data processing used in Big Data technology. The withColumnRenamed() method or function takes two parameters: the first is the existing column name, and the second is the new column name as per user needs. The Spark provides the withColumnRenamed() function on the DataFrame to change a column name, and it's the most straightforward approach.
Depending upon the DataFrame schema, the renaming columns might get complex from simple is especially when the column is nested with the struct type, and it gets complicated. The Spark withColumnRenamed() method is used to rename the one column or multiple DataFrame column names. The resulting dataframe has both the column names renamed.Recipe Objective - Explain Spark withColumnRenamed() method to rename a column? # rename Emp_Age to Age and Emp_Department to DepartmentĮmployees_df = rename(employees_df, "Age"="Emp_Age", "Department"="Emp_Department") You can also use the rename() function to rename more than one column at a time.įor example, let’s now rename the “Emp_Age” column to “Age” and the “Emp_Department” column to “Department” in one go. Rename multiple columns using the rename() function You can see that the “Emp_Name” column is now the “Name” column. We store the resulting dataframe to the original dataframe variable. # rename Emp_Name to NameĮmployees_df = rename(employees_df, "Name"="Emp_Name") Let’s now rename the “Emp_Name” column to “Name” using the rename() function. Step 3 – Rename column name using rename() function Here we use the library() function to import the dplyr package. The rename() function is defined in the dplyr package which has to be imported before we can actually use it. We’ll do that by renaming these columns using the rename() function. You can see that the column names have the prefix “Emp_” which can be removed. The dataframe has columns “Emp_Name”, “Emp_Age”, and “Emp_Department”. We now have a dataframe containing information about some employees working in an office. "Emp_Department"= c("Sales", "Sales", "Accounting", "HR", "Accounting") Step 1 – Create a dataframeįirst, we will create a dataframe that we will be using throughout this tutorial. Let’s now look at a step-by-step example of changing the name of a column in a dataframe. Steps to rename a column in R using rename() function It returns an R dataframe with the updated column names. Pass the dataframe as the first argument and then new_column_name=old_column_name for each column you want to rename. The following is the syntax – rename(dataframe_input, new_column_name=old_column_name) You can use the rename() function available in the dplyr package to rename one or more column names in a dataframe in R.
#RENAME COLUMN R HOW TO#
How to rename a column in an R dataframe? In this tutorial, we will look at how to rename one or more column names in an R dataframe with the help of some examples. A dataframe in R is a two-dimensional data structure used to store the data in rows and columns and perform different operations on it.
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