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Pandas First Steps
Pandas First Steps
Working with Columns
When working with a DataFrame, you can access each column individually.
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:
- Is a valid Python identifier (e.g., no spaces, special characters, or starting with a number);
- Does not conflict with an existing
pandasattribute or method name.
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)
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.
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)
Swipe to show code editor
Retrieve the columns 'model', 'year', and 'price' (in that order) from the audi_cars DataFrame.
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Working with Columns
When working with a DataFrame, you can access each column individually.
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:
- Is a valid Python identifier (e.g., no spaces, special characters, or starting with a number);
- Does not conflict with an existing
pandasattribute or method name.
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)
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.
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)
Swipe to show code editor
Retrieve the columns 'model', 'year', and 'price' (in that order) from the audi_cars DataFrame.
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixoObrigado pelo seu feedback!
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo