Cursusinhoud
Pandas First Steps
Pandas First Steps
Working with Columns
When working with a DataFrame, you can access each column individually.
python
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.
python
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:
python
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 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 thecolumnsvariable.
Oplossing
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Working with Columns
When working with a DataFrame, you can access each column individually.
python
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.
python
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:
python
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 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 thecolumnsvariable.
Oplossing
Schakel over naar desktop voor praktijkervaringGa verder vanaf waar je bent met een van de onderstaande optiesBedankt voor je feedback!
Schakel over naar desktop voor praktijkervaringGa verder vanaf waar je bent met een van de onderstaande opties