Selecting rows from a dataframe is now one of the most common tasks anyone can do with pandas. In this tutorial, we will look at how to get the last row of a dataframe in pandas with the help of some examples.

## Select the last row of a dataframe

Sometimes you may need to select the last row of a pandas data frame. There are multiple ways to select the last row of a dataframe. For example –

- Use the pandas dataframe
`iloc`

property. - Use the pandas
`tail()`

function.

# Using the iloc[] Property to Retrieve the DataFrame’s Last Row df.iloc[-1] # Retrieve the Last Row of All or a Specific Column Using the tail() Function df.tail(1)

## Examples

Let’s now look at some examples of using the above syntax.

First, we will create a pandas dataframe that we will be using throughout this tutorial.

import pandas as pd # employee data data = { "Name": ["Ram", "Sita", "Anita", "Abhinash"], "Age": [26, 28, 27, 32], "Department": ["Sales", "Sales", "Accounting", "HR"] } # create pandas dataframe df = pd.DataFrame(data) # display the dataframe df

Output:

Here, we created a dataframe with data with information on some employees in an office. You can see that the column names in the above dataframe are – “Name”, “Age”, and “Department”.

### Example 1: Get the Last Row of a Dataframe using the `iloc[]`

property

The Pandas module in Python defines the `iloc[]`

property which allows you to retrieve a specific column or row from the given DataFrame. Using the index values, we can quickly extract any specific value from a column or a row using the `iloc[]`

property.

The following code shows how to get the last row of a dataframe using the `iloc[]`

property.

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# Using the iloc[] to Retrieve the DataFrame’s Last Row df.iloc[-1]

Output:

Name Abhinash Age 32 Department HR Name: 3, dtype: object

Pandas dataframe rows are indexed starting from 0. Thus, the index of the first row is 0 and that of the last row is n-1 where n is the length of the dataframe. Using a negative index can be helpful here. The index -1 represents the index of the first row from the end of the dataframe, that is, the last row of the dataframe.

So, we can use -1 as the index inside the `iloc[]`

property to get the last row of the “df” DataFrame.

You can similarly get the last value (value in the last row) of a specific column in a pandas dataframe using the `iloc[]`

property.

# Retrieve the Last Row of Name Column Using the iloc[] property df['Name'].iloc[-1]

Output:

'Abhinash'

### Example 2: Get the Last Row of a Dataframe using the `tail()`

function

The `tail()`

function in pandas retrieves the last “n” rows of a dataframe. The last “n” (the default value is 5) DataFrame’s rows or series are returned using this method. To retrieve just the last row, we pass 1 as an argument to the `tail()`

function. The following code shows the same.

# Retrieve the Last Row Using the tail() Function df.tail(1)

Output:

By using the value of 1 inside the `tail()`

function, we retrieved the last row. Just like with the `iloc[]`

property, we can also use the `tail()`

function to retrieve the last row of a specific column of the DataFrame.

# Retrieve the Last Row of Name Column Using the tail() Function df['Name'].tail(1)

Output:

3 Abhinash Name: Name, dtype: object

We get the last value in the “Name” column of the above dataframe.

## Summary

In this tutorial, we looked at how to access the last row of a pandas dataframe using the following methods –

- Using the
`iloc[]`

property. - Using the
`tail()`

function.

We also looked at how to get the value in the last row for a specific column using the above methods.

You might also be interested in –

- Pandas – Drop last n rows of a DataFrame
- Pandas – Select first n rows of a DataFrame
- Pandas – Read only the first n rows of a CSV file
- Pandas – Drop first n rows of a DataFrame
- Get Row Labels of a Pandas DataFrame
- Pandas Groupby – Count of rows in each group

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