Using iloc

The DataFrame we are working with:

In the DataFrame we're working with, you can also use negative indexing. Negative indexing starts from the end of the DataFrame: index -1 points to the last row, -2 to the second to last, and so on.

To access the seventh row (which refers to Latvia), you can use either index 6 or -1. Let's see how this works in practice.


              123456
            
import pandas

dataset = {'country' : ['Thailand', 'Philippines', 'Monaco', 'Malta', 'Sweden', 'Paraguay', 'Latvia'], 'continent' : ['Asia', 'Asia', 'Europe', 'Europe', 'Europe', 'South America', 'Europe'], 'capital':['Bangkok', 'Manila', 'Monaco', 'Valletta', 'Stockholm', 'Asuncion', 'Riga']}
countries = pandas.DataFrame(dataset)
# Accessing to the seventh row using negative indexing
print(countries.iloc[-1])

Running the above code will return the row highlighted in the image below:

It's time to practice!

Task

Swipe to show code editor

We have a DataFrame called audi_cars.

Display all the details from the DataFrame for the Audi A1 model from the year 2017. To do this, you'll need to use positive indexing.
Display all the details from the DataFrame for the Audi A1 model from the year 2016 using negative indexing.
Display all the details from the DataFrame for the Audi A3 model using positive indexing.

Make sure to use the iloc attribute. Give it a try!

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Section 1. Chapter 14

Using iloc

The DataFrame we are working with:

To access the seventh row (which refers to Latvia), you can use either index 6 or -1. Let's see how this works in practice.


              123456
            
import pandas

dataset = {'country' : ['Thailand', 'Philippines', 'Monaco', 'Malta', 'Sweden', 'Paraguay', 'Latvia'], 'continent' : ['Asia', 'Asia', 'Europe', 'Europe', 'Europe', 'South America', 'Europe'], 'capital':['Bangkok', 'Manila', 'Monaco', 'Valletta', 'Stockholm', 'Asuncion', 'Riga']}
countries = pandas.DataFrame(dataset)
# Accessing to the seventh row using negative indexing
print(countries.iloc[-1])

Running the above code will return the row highlighted in the image below:

It's time to practice!

Task

Swipe to show code editor

We have a DataFrame called audi_cars.

Display all the details from the DataFrame for the Audi A1 model from the year 2017. To do this, you'll need to use positive indexing.
Display all the details from the DataFrame for the Audi A1 model from the year 2016 using negative indexing.
Display all the details from the DataFrame for the Audi A3 model using positive indexing.

Make sure to use the iloc attribute. Give it a try!

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Section 1. Chapter 14

Switch to desktop for real-world practiceContinue from where you are using one of the options below