How to select last row and access PySpark dataframe by index ?

In this article, we will discuss how to select the last row and access pyspark dataframe by index.

Creating dataframe for demonstration:

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"],
       ["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)

# show dataframe
dataframe.show()

Output:

Select last row from dataframe

Example 1: Using tail() function.

This function is used to access the last row of the dataframe

Syntax: dataframe.tail(n)

where 

1. n is the number of rows to be selected from the last.
2. dataframe is the input dataframe

We can use n = 1 to select only last row.

Example 1: Selecting last row.

Python3

# access last row of the dataframe
dataframe.tail(1)

Output:

[Row(student ID=’5′, student NAME=’gnanesh’, college=’iit’)]

Example 2: Python program to access last N rows.

Python3

# access last 5 rows of the
# dataframe
dataframe.tail(5)

Output:

[Row(student ID='2', student NAME='ojaswi', college='vvit'),
Row(student ID='3', student NAME='rohith', college='vvit'),
Row(student ID='4', student NAME='sridevi', college='vignan'),
Row(student ID='1', student NAME='sravan', college='vignan'),
Row(student ID='5', student NAME='gnanesh', college='iit')]

Access the dataframe by column index

Here we are going to select the dataframe based on the column number. For selecting a specific column by using column number in the pyspark dataframe, we are using select() function

Syntax: dataframe.select(dataframe.columns[column_number]).show()

where,

1. dataframe is the dataframe name
2. dataframe.columns[]: is the method which can take column number as an input and select those column
3. show() function is used to display the selected column

Example 1: Python program to access column based on column number

Python3

# select column with column number 1
dataframe.select(dataframe.columns[1]).show()

Output:

+------------+
|student NAME|
+------------+
|      sravan|
|      ojaswi|
|      rohith|
|     sridevi|
|      sravan|
|     gnanesh|
+------------+

Example 2: Accessing multiple columns based on column number, here we are going to select multiple columns by using the slice operator, It can access upto n columns

Syntax: dataframe.select(dataframe.columns[column_start:column_end]).show()

where: column_start is the starting index and column_end is the ending index.

Python3

# select column with column number slice
# operator
dataframe.select(dataframe.columns[0:3]).show()

Output: