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.

Tarefa

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!

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Tudo estava claro?

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Seção 1. Capítulo 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.

Tarefa

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!

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

Obrigado pelo seu feedback!

Seção 1. Capítulo 9

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo