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Please enable JavaScript in your browser settings or update your browser.Learn Working with Columns | The Very First Steps
Pandas First Steps

bookWorking with Columns

When working with a DataFrame, you can access each column individually.

df['column_name']

To clarify this syntax:

  • Start by writing the name of the DataFrame you're working with;
  • Next, place the column name you want to access inside square brackets. Remember to enclose the column name in quotation marks.

Alternatively, you can use dot notation to access a column if the column name:

  1. Is a valid Python identifier (e.g., no spaces, special characters, or starting with a number);
  2. Does not conflict with an existing pandas attribute or method name.
df.column_name


              
12345678910111213

            
import pandas as pd

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 = pd.DataFrame(countries_data)

capitals = countries['capital']

# Second option
# capitals = countries.capital

print(capitals)
copy

Executing this code will display just the column containing capital cities, rather than the entire DataFrame.

You can also access multiple columns like this:

df[['column1', 'column2', 'column3']]

Compared to accessing a single column, there is only one difference. This time, you'll need to put the list of column names inside an additional set of square brackets β€” meaning you'll use double square brackets.


              
12345678

            
import pandas as pd

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 = pd.DataFrame(countries_data)
columns = countries[['country', 'capital']]
print(columns)
copy
Task

Swipe to start coding

You are given a DataFrame named audi_cars.

  • Retrieve the data for the columns 'model', 'year', and 'price' and store the result in the columns variable.

Solution

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

SectionΒ 1. ChapterΒ 11
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bookWorking with Columns

When working with a DataFrame, you can access each column individually.

df['column_name']

To clarify this syntax:

  • Start by writing the name of the DataFrame you're working with;
  • Next, place the column name you want to access inside square brackets. Remember to enclose the column name in quotation marks.

Alternatively, you can use dot notation to access a column if the column name:

  1. Is a valid Python identifier (e.g., no spaces, special characters, or starting with a number);
  2. Does not conflict with an existing pandas attribute or method name.
df.column_name


              
12345678910111213

            
import pandas as pd

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 = pd.DataFrame(countries_data)

capitals = countries['capital']

# Second option
# capitals = countries.capital

print(capitals)
copy

Executing this code will display just the column containing capital cities, rather than the entire DataFrame.

You can also access multiple columns like this:

df[['column1', 'column2', 'column3']]

Compared to accessing a single column, there is only one difference. This time, you'll need to put the list of column names inside an additional set of square brackets β€” meaning you'll use double square brackets.


              
12345678

            
import pandas as pd

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 = pd.DataFrame(countries_data)
columns = countries[['country', 'capital']]
print(columns)
copy
Task

Swipe to start coding

You are given a DataFrame named audi_cars.

  • Retrieve the data for the columns 'model', 'year', and 'price' and store the result in the columns variable.

Solution

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

SectionΒ 1. ChapterΒ 11
single

single

close

Awesome!

Completion rate improved to 3.03

bookWorking with Columns

Swipe to show menu

When working with a DataFrame, you can access each column individually.

df['column_name']

To clarify this syntax:

  • Start by writing the name of the DataFrame you're working with;
  • Next, place the column name you want to access inside square brackets. Remember to enclose the column name in quotation marks.

Alternatively, you can use dot notation to access a column if the column name:

  1. Is a valid Python identifier (e.g., no spaces, special characters, or starting with a number);
  2. Does not conflict with an existing pandas attribute or method name.
df.column_name


              
12345678910111213

            
import pandas as pd

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 = pd.DataFrame(countries_data)

capitals = countries['capital']

# Second option
# capitals = countries.capital

print(capitals)
copy

Executing this code will display just the column containing capital cities, rather than the entire DataFrame.

You can also access multiple columns like this:

df[['column1', 'column2', 'column3']]

Compared to accessing a single column, there is only one difference. This time, you'll need to put the list of column names inside an additional set of square brackets β€” meaning you'll use double square brackets.


              
12345678

            
import pandas as pd

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 = pd.DataFrame(countries_data)
columns = countries[['country', 'capital']]
print(columns)
copy
Task

Swipe to start coding

You are given a DataFrame named audi_cars.

  • Retrieve the data for the columns 'model', 'year', and 'price' and store the result in the columns variable.

Solution

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

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