Deleting a Row/Column

At times, certain columns may not provide valuable information, making it advantageous to remove them. The pandas library offers the drop() method for this purpose. Let's delve into the function's syntax.

index: Specifies the row indexes to be deleted (used when axis=0);
columns: Identifies the column names to be deleted (used when axis=1);
axis: Choose whether to remove labels from the rows (0) or columns (1). The default is 0.

In this section, we're going to work with a specific DataFrame. Let's examine it.


              1234567
            
import pandas as pd 

dataset = {'country' : ['Thailand', 'Philippines', 'Monaco', 'Malta', 'Sweden', 'Paraguay', 'Latvia'],
          'continent' : [None, None, 'Europe', None, 'Europe', None, 'Europe'],
          'capital':['Bangkok', 'Manila', 'Monaco', 'Valletta', 'Stockholm', 'Asuncion', 'Riga']}
countries = pd.DataFrame(dataset)
print(countries)

We notice that the continent column contains numerous empty rows, making it less informative. Consequently, we'll remove it.


              12345678
            
import pandas

dataset = {'country' : ['Thailand', 'Philippines', 'Monaco', 'Malta', 'Sweden', 'Paraguay', 'Latvia'],
          'continent' : [None, None, 'Europe', None, 'Europe', None, 'Europe'],
          'capital':['Bangkok', 'Manila', 'Monaco', 'Valletta', 'Stockholm', 'Asuncion', 'Riga']}
countries = pandas.DataFrame(dataset)
countries = countries.drop(columns = ['continent'],axis=1)
print(countries)

Time for some hands-on practice.

Task

Swipe to show code editor

We have a DataFrame called audi_cars. Take a close look at the provided dictionary and eliminate the irrelevant column. 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 9

Deleting a Row/Column

index: Specifies the row indexes to be deleted (used when axis=0);
columns: Identifies the column names to be deleted (used when axis=1);
axis: Choose whether to remove labels from the rows (0) or columns (1). The default is 0.

In this section, we're going to work with a specific DataFrame. Let's examine it.


              1234567
            
import pandas as pd 

dataset = {'country' : ['Thailand', 'Philippines', 'Monaco', 'Malta', 'Sweden', 'Paraguay', 'Latvia'],
          'continent' : [None, None, 'Europe', None, 'Europe', None, 'Europe'],
          'capital':['Bangkok', 'Manila', 'Monaco', 'Valletta', 'Stockholm', 'Asuncion', 'Riga']}
countries = pd.DataFrame(dataset)
print(countries)

We notice that the continent column contains numerous empty rows, making it less informative. Consequently, we'll remove it.


              12345678
            
import pandas

dataset = {'country' : ['Thailand', 'Philippines', 'Monaco', 'Malta', 'Sweden', 'Paraguay', 'Latvia'],
          'continent' : [None, None, 'Europe', None, 'Europe', None, 'Europe'],
          'capital':['Bangkok', 'Manila', 'Monaco', 'Valletta', 'Stockholm', 'Asuncion', 'Riga']}
countries = pandas.DataFrame(dataset)
countries = countries.drop(columns = ['continent'],axis=1)
print(countries)

Time for some hands-on practice.

Task

Swipe to show code editor

We have a DataFrame called audi_cars. Take a close look at the provided dictionary and eliminate the irrelevant column. 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 9

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