Learn Challenge: Using iloc | The Very First Steps

The DataFrame we are working with:

You can also use negative indexing to access rows in the DataFrame. 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.


              123456
            
import pandas

countries_data = {'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(countries_data)
# 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:

Task

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You are given a DataFrame named audi_cars.

Display all the details from the DataFrame for the 'Audi A1' model from the year 2017 and store the result in the audi_A1_2017 variable.
Display all the details from the DataFrame for the 'Audi A1' model from the year 2016 and store the result in the audi_A1_2016 variable.
Display all the details from the DataFrame for the Audi A3 model and store the result in the audi_A3 variable.

Solution

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Section 1. Chapter 14

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The DataFrame we are working with:

To access the seventh row (which refers to Latvia), you can use either index 6 or -1.


              123456
            
import pandas

countries_data = {'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(countries_data)
# 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:

Task

Swipe to start coding

You are given a DataFrame named audi_cars.

Display all the details from the DataFrame for the 'Audi A1' model from the year 2017 and store the result in the audi_A1_2017 variable.
Display all the details from the DataFrame for the 'Audi A1' model from the year 2016 and store the result in the audi_A1_2016 variable.
Display all the details from the DataFrame for the Audi A3 model and store the result in the audi_A3 variable.

Solution

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

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Swipe to show menu

The DataFrame we are working with:

To access the seventh row (which refers to Latvia), you can use either index 6 or -1.


              123456
            
import pandas

countries_data = {'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(countries_data)
# 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:

Task

Swipe to start coding

You are given a DataFrame named audi_cars.

Display all the details from the DataFrame for the 'Audi A1' model from the year 2017 and store the result in the audi_A1_2017 variable.
Display all the details from the DataFrame for the 'Audi A1' model from the year 2016 and store the result in the audi_A1_2016 variable.
Display all the details from the DataFrame for the Audi A3 model and store the result in the audi_A3 variable.

Solution

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

Everything was clear?

Thanks for your feedback!

Challenge: Using iloc

Solution

Awesome!

Challenge: Using iloc

Solution

Awesome!

Challenge: Using iloc

Solution