Course Content
Pandas First Steps
Pandas First Steps
Working with Columns
When working with a DataFrame, you can access each column individually. Here's the syntax for doing so:
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.
Let's look at an example using a DataFrame.
import pandas as pd 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 = pd.DataFrame(dataset) capitals = countries['capital'] print(capitals)
Executing this code will display just the column containing capital cities, rather than the entire DataFrame.
You can also access multiple columns like this:
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 — meaning you'll use double square brackets. Check out the example below.
import pandas as pd 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 = pd.DataFrame(dataset) columns = countries[['country', 'capital']] print(columns)
Task
Retrieve the columns 'model'
, 'year'
, and 'price'
(in that order) from the audi_cars
DataFrame. Give it a try!
Task
Retrieve the columns 'model'
, 'year'
, and 'price'
(in that order) from the audi_cars
DataFrame. Give it a try!
Everything was clear?
Working with Columns
When working with a DataFrame, you can access each column individually. Here's the syntax for doing so:
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.
Let's look at an example using a DataFrame.
import pandas as pd 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 = pd.DataFrame(dataset) capitals = countries['capital'] print(capitals)
Executing this code will display just the column containing capital cities, rather than the entire DataFrame.
You can also access multiple columns like this:
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 — meaning you'll use double square brackets. Check out the example below.
import pandas as pd 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 = pd.DataFrame(dataset) columns = countries[['country', 'capital']] print(columns)
Task
Retrieve the columns 'model'
, 'year'
, and 'price'
(in that order) from the audi_cars
DataFrame. Give it a try!
Task
Retrieve the columns 'model'
, 'year'
, and 'price'
(in that order) from the audi_cars
DataFrame. Give it a try!
Everything was clear?
Working with Columns
When working with a DataFrame, you can access each column individually. Here's the syntax for doing so:
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.
Let's look at an example using a DataFrame.
import pandas as pd 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 = pd.DataFrame(dataset) capitals = countries['capital'] print(capitals)
Executing this code will display just the column containing capital cities, rather than the entire DataFrame.
You can also access multiple columns like this:
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 — meaning you'll use double square brackets. Check out the example below.
import pandas as pd 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 = pd.DataFrame(dataset) columns = countries[['country', 'capital']] print(columns)
Task
Retrieve the columns 'model'
, 'year'
, and 'price'
(in that order) from the audi_cars
DataFrame. Give it a try!
Task
Retrieve the columns 'model'
, 'year'
, and 'price'
(in that order) from the audi_cars
DataFrame. Give it a try!
Everything was clear?
When working with a DataFrame, you can access each column individually. Here's the syntax for doing so:
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.
Let's look at an example using a DataFrame.
import pandas as pd 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 = pd.DataFrame(dataset) capitals = countries['capital'] print(capitals)
Executing this code will display just the column containing capital cities, rather than the entire DataFrame.
You can also access multiple columns like this:
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 — meaning you'll use double square brackets. Check out the example below.
import pandas as pd 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 = pd.DataFrame(dataset) columns = countries[['country', 'capital']] print(columns)
Task
Retrieve the columns 'model'
, 'year'
, and 'price'
(in that order) from the audi_cars
DataFrame. Give it a try!