How to drop multiple column names given in a list from PySpark DataFrame ?

In this article, we are going to drop multiple columns given in the list in Pyspark dataframe in Python.

For this, we will use the drop() function. This function is used to remove the value from dataframe.

Syntax: dataframe.drop(*['column 1','column 2','column n'])

Where,

• dataframe is the input dataframe
• column names are the  columns passed through a list  in the dataframe.

Python code to create student dataframe with three columns:

# importing module
import pyspark

# importing sparksession from pyspark.sql module
from pyspark.sql import SparkSession

# creating sparksession and giving an app name
spark = SparkSession.builder.appName('sparkdf').getOrCreate()

# list  of students  data 
data =[["1","sravan","vignan"],
       ["2","ojaswi","vvit"],
       ["3","rohith","vvit"],
       ["4","sridevi","vignan"],
       ["1","sravan","vignan"], 
       ["5","gnanesh","iit"]]

# specify column names
columns=['student ID','student NAME','college']

# creating a dataframe from the lists of data
dataframe = spark.createDataFrame(data,columns)

print("Actual data in dataframe")

# show dataframe
dataframe.show()

Output:

Actual data in dataframe
+----------+------------+-------+
|student ID|student NAME|college|
+----------+------------+-------+
|         1|      sravan| vignan|
|         2|      ojaswi|   vvit|
|         3|      rohith|   vvit|
|         4|     sridevi| vignan|
|         1|      sravan| vignan|
|         5|     gnanesh|    iit|
+----------+------------+-------+

Example 1: Program to delete multiple column names as a list.

list = ['student NAME','college']

# drop two  columns in dataframe
dataframe = dataframe.drop(*list)
dataframe.show()

Output:

+----------+
|student ID|
+----------+
|         1|
|         2|
|         3|
|         4|
|         1|
|         5|
+----------+

Example 2: Example program to drop one column names as a list.

list = ['college']

# drop two  columns in dataframe
dataframe=dataframe.drop(*list)
dataframe.show()

Output:

+----------+------------+
|student ID|student NAME|
+----------+------------+
|         1|      sravan|
|         2|      ojaswi|
|         3|      rohith|
|         4|     sridevi|
|         1|      sravan|
|         5|     gnanesh|
+----------+------------+

Example 3: Drop all column names as a list.

list = ['student ID','student NAME','college']

# drop all  columns in dataframe
dataframe=dataframe.drop(*list)
dataframe.show()

Output:

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