TODO 11 Using the clean_df split our columns into features and labels. Index/slice our label 'area' and store the output into the variable y. Index/slice all other features EXCEPT 'area' into the variable X. To do so you can use the Pandas DataFrame drop() method or slicing with iloc, loc or [ ]. #TODO 11.1   # TODO 11.2 X =  display(X) todo_check([     (X.shape == (517, 29), 'X does not have the correct shape of (517, 29)! Make sure the `area` column is not included!'),     (np.all(np.isclose(X.values[-5:, -4], np.array([27.8, 21.9, 21.2, 25.6, 11.8]),rtol=.01)),'X has the incorrect values'), ])

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
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TODO 11

Using the clean_df split our columns into features and labels.

  1. Index/slice our label 'area' and store the output into the variable y.
  2. Index/slice all other features EXCEPT 'area' into the variable X. To do so you can use the Pandas DataFrame drop() method or slicing with iloc, loc or [ ].

#TODO 11.1

 

# TODO 11.2
X = 
display(X)

todo_check([
    (X.shape == (517, 29), 'X does not have the correct shape of (517, 29)! Make sure the `area` column is not included!'),
    (np.all(np.isclose(X.values[-5:, -4], np.array([27.8, 21.9, 21.2, 25.6, 11.8]),rtol=.01)),'X has the incorrect values'),
])

Expert Solution
Step 1

Introduction

Index:

Index in a data structure refers to a label or a set of labels that can be used to identify the rows or elements in that data structure. In the context of a Pandas DataFrame, the index refers to a label for each row in the DataFrame, allowing you to easily select or reference specific rows based on their label or index. By default, Pandas assigns integer-based indices to a DataFrame, starting from 0 for the first row, 1 for the second row, and so on. However, you can also set a custom index for a DataFrame using one of its columns or defining your own set of labels.

Slice:

In Python, slicing is a way of extracting a portion of a sequence, such as a list, string, tuple, etc. The slice operation is performed by using the syntax sequence[start:end:step].

The start and end parameters specify the starting and ending indices (inclusive and exclusive, respectively) of the slice. The step parameter specifies the increment between elements in the slice. If start and end are omitted, the slice will include the entire sequence from start to end. If step is omitted, the slice will include every element in the sequence.

For example, if we have a list a = [1, 2, 3, 4, 5], the slice a[1:4] would return [2, 3, 4], and the slice a[::2] would return [1, 3, 5].

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