How to create a PySpark dataframe from multiple lists ?

Last Updated : 30 May, 2021

In this article, we will discuss how to create Pyspark dataframe from multiple lists.

Approach

Create data from multiple lists and give column names in another list. So, to do our task we will use the zip method.

zip(list1,list2,., list n)

Pass this zipped data to spark.createDataFrame() method

dataframe = spark.createDataFrame(data, columns)

Examples

Example 1: Python program to create two lists and create the dataframe using these two lists

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 college data with dictionary
# with two lists in three elements each
data = [1, 2, 3]
data1 = ["sravan", "bobby", "ojaswi"]

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

# creating a dataframe by zipping the two lists
dataframe = spark.createDataFrame(zip(data, data1), columns)

# show data frame
dataframe.show()

Output:

Example 2: Python program to create 4 lists and create the 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 college data with dictionary
# with four lists in three elements each
data = [1, 2, 3]
data1 = ["sravan", "bobby", "ojaswi"]
data2 = ["iit-k", "iit-mumbai", "vignan university"]
data3 = ["AP", "TS", "UP"]

# specify column names
columns = ['ID', 'NAME', 'COLLEGE', 'ADDRESS']

# creating a dataframe by zipping 
# the two lists
dataframe = spark.createDataFrame(
  zip(data, data1, data2, data3), columns)

# show data frame
dataframe.show()