Data Types
The main tool we will use to manipulate data is pandas. We can start right away by loading the data:
12345import pandas as pd df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/9c23bf60-276c-4989-a9d7-3091716b4507/datasets/penguins.csv') print(df.head())
As you understand, each dataset can contain many different data types, for example, numeric (integers, floating point numbers), strings (str), and datetime. To find out what data type a column has, you can call the .dtypes property:
12345import pandas as pd df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/9c23bf60-276c-4989-a9d7-3091716b4507/datasets/penguins.csv') print(df.dtypes)
Let's say you have a column with numeric values but in string format and want to change the data type to numeric. To do this, use the .astype() method:
df['column'] = df['column'].astype(float)
Swipe to start coding
Read the penguins.csv dataset and change the data type in the body_mass_g column from float to int.
Don't modify the initial code, only replace the gaps ___ with the correct code.
Once you've completed this task, click the button below the code to check your solution.
Oplossing
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The main tool we will use to manipulate data is pandas. We can start right away by loading the data:
12345import pandas as pd df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/9c23bf60-276c-4989-a9d7-3091716b4507/datasets/penguins.csv') print(df.head())
As you understand, each dataset can contain many different data types, for example, numeric (integers, floating point numbers), strings (str), and datetime. To find out what data type a column has, you can call the .dtypes property:
12345import pandas as pd df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/9c23bf60-276c-4989-a9d7-3091716b4507/datasets/penguins.csv') print(df.dtypes)
Let's say you have a column with numeric values but in string format and want to change the data type to numeric. To do this, use the .astype() method:
df['column'] = df['column'].astype(float)
Swipe to start coding
Read the penguins.csv dataset and change the data type in the body_mass_g column from float to int.
Don't modify the initial code, only replace the gaps ___ with the correct code.
Once you've completed this task, click the button below the code to check your solution.
Oplossing
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Awesome!
Completion rate improved to 3.33single
