You can use the following methods to get the last row in a pandas DataFrame:

**Method 1: Get Last Row (as a Pandas Series)**

last_row = df.iloc[-1]

**Method 2: Get Last Row (as a Pandas DataFrame)**

last_row = df.iloc[-1:]

The following examples show how to use each method in practice with the following pandas DataFrame:

import pandas as pd #create DataFrame df = pd.DataFrame({'assists': [3, 4, 4, 5, 6, 7, 8, 12, 15, 11], 'rebounds': [1, 3, 3, 5, 2, 2, 1, 1, 0, 14], 'points': [20, 22, 24, 25, 20, 28, 15, 29, 11, 12]}) #view DataFrame print(df) assists rebounds points 0 3 1 20 1 4 3 22 2 4 3 24 3 5 5 25 4 6 2 20 5 7 2 28 6 8 1 15 7 12 1 29 8 15 0 11 9 11 14 12

**Example 1: Get Last Row (as a Pandas Series)**

The following code shows how to get the last row of the DataFrame as a pandas Series:

#get last row in Data Frame as Series last_row = df.iloc[-1] #view last row print(last_row) assists 11 rebounds 14 points 12 Name: 9, dtype: int64

We can use the **type()** function to confirm that the result is indeed a pandas Series:

#view type type(last_row) pandas.core.series.Series

The result is indeed a pandas Series.

**Example 2: Get Last Row (as a Pandas DataFrame)**

The following code shows how to get the last row of the DataFrame as a pandas DataFrame:

#get last row in Data Frame as DataFrame last_row = df.iloc[-1:] #view last row print(last_row) assists rebounds points 9 11 14 12

We can use the **type()** function to confirm that the result is indeed a pandas DataFrame:

#view type type(last_row) pandas.core.frame.DataFrame

The result is indeed a pandas DataFrame.

**Additional Resources**

The following tutorials explain how to perform other common tasks in pandas:

How to Select Rows without NaN Values in Pandas

How to Drop All Rows Except Specific Ones in Pandas

How to Sum Specific Columns in Pandas