In this article, we are going to see how to access an index of the last element in the pandas Dataframe. To achieve this, we can use Dataframe.iloc, Dataframe.iget, and Dataframe.index. let’s go through all of them one by one.
Dataframe.iloc – Pandas Dataframe.iloc is used to retrieve data by specifying its index. In python negative index starts from the end so we can access the last element of the dataframe by specifying its index to -1.
Syntax: pandas.DataFrame.iloc[]
Parameters:
Index Position: Index position of rows in integer or list of integer.
Return type: Data frame or Series depending on parameters
Example 1: The following program is to access the index of the last element from the entire Dataframe.
Python3
# import pandasimport pandas as pd # create dataframedf = pd.DataFrame({'Name': ['Mukul', 'Rohan', 'Rahul', 'Krish', 'Rohit'], 'Course': ['BCA', 'MBA', 'MBA', 'BCA', 'BBA'], 'Address': ['Saharanpur', 'Mohali', 'Saharanpur', 'Mohali', 'Noida']}) # Display original dataframeprint("Original dataframe")print(df) # Display last index value of dataframe# iloc[-1] is return the last element of # all columns in DataFrame.print("value of last index column")print(df.iloc[-1]) |
Output:
Example 2:
The following program is to access the index of the last element from a specific column.
Python3
# import pandasimport pandas as pd # create dataframedf = pd.DataFrame({'Name': ['Mukul', 'Rohan', 'Rahul', 'Krish', 'Rohit'], 'Course': ['BCA', 'MBA', 'MBA', 'BCA', 'BBA'], 'Address': ['Saharanpur', 'Mohali', 'Saharanpur', 'Mohali', 'Noida']}) # Display original dataframeprint("Original dataframe")print(df) # Display last index value of Address dataframeprint("last index value of Address Column: ", df['Address'].iloc[-1]) |
Output:
Dataframe.iat() function – Pandas iat[] method is used to return data in a dataframe at the passed location. The passed location is in the format [position in the row, position in the column]. This method works similarly to Pandas iloc[] but iat[] is used to return only a single value and hence works faster than it.
Syntax: Dataframe.iat[row, column]
Parameters:
- position: Position of element in column
- label: Position of element in row
Return type: Single element at passed position
Example 3:
Under, this example we will be using the df.iat() function.
Python3
# import pandasimport pandas as pd # create dataframedf = pd.DataFrame({'Name': ['sanjay', 'suresh', 'Rahul', 'Krish', 'vihan'], 'Address': ['Haridwar', 'Mohali', 'mohali', 'Mohali', 'saharanpur']}) # Display original dataframeprint(" Original dataframe ")print(df) # Display last index value of 0 index columnprint("last index value of 0 index column is ", df.iat[-1, 0]) |
Output:
Example 4:
In this example, we are using the df.index() function to access the last element of the given data frame in python language.
Python3
# import pandasimport pandas as pd # create dataframedf = pd.DataFrame({'Name': ['Mukul', 'Rohan', 'Rahul', 'Krish', 'Rohit'], 'Address': ['Saharanpur', 'Mohali', 'Saharanpur', 'Mohali', 'Noida']}) # Display original dataframeprint(" Original dataframe ")print(df) # Display last index value of dataframe# iloc[-1] is return the last element of# all columns in DataFrame.print(" last index is ", df.index[-1]) |
Output:
