Answered: Utilize pd.get dummies() to transform…

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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TODO 1.1: Utilize pd.get dummies() to transform the inputs X into one-hot embeddings in the transform() method. Put the output into the variable one hot.

TODO 1.2: For our one-hot encoding one_hot, save the column names so we may later retrieve them if necessary. The class variable self should be used to store the output. feature names

class OneHotEncoding(BaseEstimator, TransformerMixin):

def__init__(self):

self.feature_names = None

deffit(self, X: pd.DataFrame, y: pd.DataFrame = None):

# We don't need to set/learn any variables so

# we just need to return a reference to the object with 'self'

returnself

deftransform(self, X: pd.DataFrame, y: pd.DataFrame = None):

# TODO 1.1

one_hot =

# TODO 1.2

self.feature_names =

return one_hot

---

one_hot = OneHotEncoding()

ohe_df = one_hot.fit_transform(forestfire_df[['month', 'day']])

display(ohe_df)

todo_check([

(ohe_df.shape == (517,19),'ohe_df shape did not match (517, 19)'),

('month_nov'in ohe_df.columns,'month_nov not detected in column names!'),

('day_fri'in ohe_df.columns,'day_fri not detected in column names!'),

('month_nov'in one_hot.feature_names,'self.feature_names does not contain the right column name values!'),

])

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