How to Choose Last 3 Rows of Dataframe in Python
To get the last 3 rows of a dataframe in Python, you can use the iloc() function along with negative indexing.
The following example shows how to get the last 3 rows of a dataframe using the iloc() function in Python.
Using iloc() Function
We can use the iloc() function to select the last 3 rows of a dataframe.
Suppose we have the following dataframe:
# Importing pandas library
import pandas as pd
# Creating a dataframe
Office_Stuff = pd.DataFrame({
'Date': ['01-03-2023', '01-03-2023', '01-03-2023', '01-03-2023', '02-03-2023', '02-03-2023'],
'Product_Code': ['A-101', 'A-102', 'A-103', 'B-101', 'B-102', 'B-104'],
'Product_Name': ['Laptop', 'Mobile', 'Printer', 'Keyboard', 'Scanner', 'Mouse'],
'Price': [4500, 550, 250, 50, 350, 50],
'Status': [1, 1, 1, 0, 1, 1]
})
# Selecting last 3 rows of dataframe
last_3_rows = Office_Stuff.iloc[-3:]
# Printing the last 3 rows of dataframe
print(last_3_rows)
Output: 👇️
Date Product_Code Product_Name Price Status
3 01-03-2023 B-101 Keyboard 50 0
4 02-03-2023 B-102 Scanner 350 1
5 02-03-2023 B-104 Mouse 50 1
In this example, we use the iloc() function to select the last 3 rows of the dataframe Office_Stuff.
Conclusion
We can use the iloc() function along with negative indexing to choose the last 3 rows of a dataframe in Python. This method provides a convenient way to access specific rows from the end of a dataframe.