Challenge: Encoding Categorical Variables
To summarize the previous three chapters, here is a table showing what encoder you should use:
In this challenge, you have the penguins dataset file (with no missing values). You need to deal with all the categorical values, including the target ('species' column).
Here is the reminder of the data you will work with:
import pandas as pd df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/a65bbc96-309e-4df9-a790-a1eb8c815a1c/penguins_imputed.csv') print(df.head())
Keep in mind that 'island' and 'sex' are categorical features and 'species' is a categorical target.
Taak
Swipe to start coding
Encode all the categorical values. For this, you need to choose the correct encoder for the 'island', and 'sex' columns and follow the steps.
- Import
OnehotEncoderandLabelEncoder. - Initialize the features encoder object.
- Encode the categorical feature columns using the
feature_encobject. - Initialize the target encoder object.
- Encode the target using the
label_encobject.
Oplossing
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