Why array creation matters in NumPy - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a NumPy array from a Python list.

NumPy

import numpy as np
arr = np.[1]([1, 2, 3, 4])
print(arr)

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Aseries

Barray

Cmatrix

Dlist

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'list' instead of 'array' causes an AttributeError.

Using 'matrix' creates a different NumPy object, not a simple array.

Use np.array to create a NumPy array from a list.

2fill in blank

medium

Complete the code to create a 3x3 array of zeros using NumPy.

NumPy

import numpy as np
zeros_array = np.[1]((3, 3))
print(zeros_array)

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Azeros

Bempty

Cones

Dfull

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'ones' creates an array of ones, not zeros.

Using 'empty' creates an uninitialized array with random values.

np.zeros creates an array filled with zeros of the given shape.

3fill in blank

hard

Fix the error in the code to create an array of ones with shape 2x4.

NumPy

import numpy as np
arr = np.ones[1](2, 4)
print(arr)

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A2, 4

B[2, 4]

C(2, 4)

D{2, 4}

Attempts:

3 left

💡 Hint

Common Mistakes

Using square brackets creates a list, which is not accepted as shape.

Passing dimensions without parentheses causes a TypeError.

The shape argument must be a tuple, so use parentheses around the dimensions.

4fill in blank

hard

Fill both blanks to create a NumPy array of integers from 0 to 9 and reshape it to 2 rows and 5 columns.

NumPy

import numpy as np
arr = np.[1](10).[2]((2, 5))
print(arr)

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Aarange

Breshape

Carray

Dflatten

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'array' instead of 'arange' does not generate a sequence automatically.

Using 'flatten' changes shape to 1D, not reshapes to 2D.

np.arange(10) creates numbers from 0 to 9, and reshape((2, 5)) changes the shape to 2 rows and 5 columns.

5fill in blank

hard

Fill all three blanks to create a 4x4 identity matrix, convert it to float type, and print its shape.

NumPy

import numpy as np
identity = np.[1](4).[2](dtype=[3])
print(identity.shape)

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Aidentity

Bastype

Cfloat64

Dzeros

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'zeros' creates a zero matrix, not identity.

Passing dtype directly to identity instead of using astype causes an error.

np.identity(4) creates a 4x4 identity matrix, astype(float64) converts its type to float, and shape prints its dimensions.