TODO 9Using the dummy_array given below, complete the following indexing/slicing TODOs.Index/slice the first (index 0), third (index 2), and last (index 4 or -1) columns of the array dummy_array. Store the output into the variable column_slice.Hint: The output shape should be a (2, 3)!Index ONLY the first row (think about the corresponding index value) of dummy_array. Store the output into the variable row_slice.Index ONLY the second row and first two columns of dummy_array. Store the output into the variable slice_array.dummy_array = np.arange(10).reshape(2, -1)print(f"dummy_array output: \n {dummy_array}")print(f"dummy_array shape: {dummy_array.shape}") # TODO 9.1column_slice = print(f"column_slice output: \n {column_slice}")print(f"column_slice shape: {column_slice.shape}")todo_check([ (column_slice.shape == (2, 3), 'column_slice did not return the correct shape of (2, 3)'), (np.all(column_slice == np.array([[0, 2, 4], [5, 7, 9]])), 'column_slice did not return the correct values!')])

Algorithm: Start Import the numpy library as np Create a 2x5 dummy_array using np.arange and…

Answered: TODO 9 Using the dummy_array given…

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 9

Using the dummy_array given below, complete the following indexing/slicing TODOs.

Index/slice the first (index 0), third (index 2), and last (index 4 or -1) columns of the array dummy_array. Store the output into the variable column_slice.
1. Hint: The output shape should be a (2, 3)!
Index ONLY the first row (think about the corresponding index value) of dummy_array. Store the output into the variable row_slice.
Index ONLY the second row and first two columns of dummy_array. Store the output into the variable slice_array.

dummy_array = np.arange(10).reshape(2, -1)
print(f"dummy_array output: \n {dummy_array}")
print(f"dummy_array shape: {dummy_array.shape}")

# TODO 9.1
column_slice =

print(f"column_slice output: \n {column_slice}")
print(f"column_slice shape: {column_slice.shape}")

todo_check([
(column_slice.shape == (2, 3), 'column_slice did not return the correct shape of (2, 3)'),
(np.all(column_slice == np.array([[0, 2, 4], [5, 7, 9]])), 'column_slice did not return the correct values!')
])

Expert Solution

Step 1

Algorithm:

Start
Import the numpy library as np
Create a 2x5 dummy_array using np.arange and np.reshape functions
Print the dummy_array and its shape
Slice the first (column 0), third (column 2), and last (column 4) columns of dummy_array and store the result in column_slice
To select multiple columns, use the syntax dummy_array[:, [column_indices]], where column_indices is a list of desired column indices
Print column_slice and its shape
Slice only the first row (row 0) of dummy_array and store the result in row_slice
To select a single row, use the syntax dummy_array[row_index, :], where row_index is the desired row index
Print row_slice and its shape
Slice only the second row (row 1) and first two columns (columns 0 and 1) of dummy_array and store the result in slice_array
To select a single row and multiple columns, use the syntax dummy_array[row_index, [column_indices]], where row_index is the desired row index and column_indices is a list of desired column indices
Print slice_array and its shape
Stop

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