In this article, we are going to display the distinct column values from dataframe using pyspark in Python. For this, we are using distinct() and dropDuplicates() functions along with select() function.
Let’s create a sample dataframe.
Python3
# 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 employee data with 5 row values data =[["1", "sravan", "company 1"], ["3", "bobby", "company 3"], ["2", "ojaswi", "company 2"], ["1", "sravan", "company 1"], ["3", "bobby", "company 3"], ["4", "rohith", "company 2"], ["5", "gnanesh", "company 1"]] # specify column names columns = ['Employee ID','Employee NAME','Company Name'] # creating a dataframe from the lists of data dataframe = spark.createDataFrame(data,columns) dataframe.show() |
Output:
Method 1: Using distinct()
This function returns distinct values from column using distinct() function.
Syntax: dataframe.select(“column_name”).distinct().show()
Example1: For a single column.
Python3
# select first column to get # unique data using distinct function() dataframe.select("Employee ID").distinct().show() |
Output:
+-----------+ |Employee ID| +-----------+ | 3| | 5| | 1| | 4| | 2| +-----------+
Example 2: For multiple columns.
Python code to display unique data from 2 columns using distinct() function.
Syntax: dataframe.select(“column_name 1, column_name 2 “).distinct().show()
Code:
Python3
# select first and second column # to get unique data using distinct function() dataframe.select(["Employee ID", "Employee NAME"]).distinct().show() |
Output:
+-----------+-------------+ |Employee ID|Employee NAME| +-----------+-------------+ | 5| gnanesh| | 4| rohith| | 1| sravan| | 2| ojaswi| | 3| bobby| +-----------+-------------+
Method 2: Using dropDuplicates()
This function displays unique data in one column from dataframe using dropDuplicates() function.
Syntax: dataframe.select(“column_name”).dropDuplicates().show()
Example 1: For single columns.
Python3
#select first column to get # unique data using dropDuplicates function() dataframe.select("Employee ID").dropDuplicates().show() |
Output:
+-----------+ |Employee ID| +-----------+ | 3| | 5| | 1| | 4| | 2| +-----------+
Example 2: For multiple columns
Python code to display unique data from 2 columns using dropDuplicates() function
Python3
#select first and second column # to get unique data using dropDuplicates function() dataframe.select(["Employee ID", "Employee NAME"]).dropDuplicates().show() |
Output:
+-----------+-------------+ |Employee ID|Employee NAME| +-----------+-------------+ | 5| gnanesh| | 4| rohith| | 1| sravan| | 2| ojaswi| | 3| bobby| +-----------+-------------+
