How to find the sum of Particular Column in PySpark Dataframe

In this article, we are going to find the sum of PySpark dataframe column in Python. We are going to find the sum in a column using agg() 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 students  data
data = [["1", "sravan", "vignan", 67, 89],
        ["2", "ojaswi", "vvit", 78, 89],
        ["3", "rohith", "vvit", 100, 80],
        ["4", "sridevi", "vignan", 78, 80],
        ["1", "sravan", "vignan", 89, 98],
        ["5", "gnanesh", "iit", 94, 98]]

# specify column names
columns = ['student ID', 'student NAME', 'college',
           'subject 1', 'subject 2']

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

# display dataframe
dataframe.show()

Output:

Using agg() method:

The agg() method returns the aggregate sum of the passed parameter column.

 Syntax:

dataframe.agg({'column_name': 'sum'})

Where,

1. The dataframe is the input dataframe
2. The column_name is the column in the dataframe
3. The sum is the function to return the sum.

Example 1: Python program to find the sum in dataframe column

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 students  data
data = [["1", "sravan", "vignan", 67, 89],
        ["2", "ojaswi", "vvit", 78, 89],
        ["3", "rohith", "vvit", 100, 80],
        ["4", "sridevi", "vignan", 78, 80],
        ["1", "sravan", "vignan", 89, 98],
        ["5", "gnanesh", "iit", 94, 98]]

# specify column names
columns = ['student ID', 'student NAME', 'college',
           'subject 1', 'subject 2']

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


# find sum of subjects column
dataframe.agg({'subject 1': 'sum'}).show()

Output:

Example 2: Get sum value from multiple columns

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 students  data
data = [["1", "sravan", "vignan", 67, 89],
        ["2", "ojaswi", "vvit", 78, 89],
        ["3", "rohith", "vvit", 100, 80],
        ["4", "sridevi", "vignan", 78, 80],
        ["1", "sravan", "vignan", 89, 98],
        ["5", "gnanesh", "iit", 94, 98]]

# specify column names
columns = ['student ID', 'student NAME', 'college',
           'subject 1', 'subject 2']

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


# find sum of multiple  column
dataframe.agg({'subject 1': 'sum', 'student ID': 'sum',
               'subject 2': 'sum'}).show()

Output: