np.concatenate() for joining arrays in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to join two numpy arrays along the default axis.

NumPy

import numpy as np
arr1 = np.array([1, 2, 3])
arr2 = np.array([4, 5, 6])
result = np.concatenate((arr1, arr2), axis=[1])
print(result)

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A1

B2

C0

D-1

Attempts:

3 left

💡 Hint

Common Mistakes

Using axis=1 causes an error because 1D arrays have only one axis (0).

Forgetting to put the arrays inside a tuple in np.concatenate.

The default axis for concatenation of 1D arrays is 0, which joins them end-to-end.

2fill in blank

medium

Complete the code to join two 2D numpy arrays vertically.

NumPy

import numpy as np
arr1 = np.array([[1, 2], [3, 4]])
arr2 = np.array([[5, 6], [7, 8]])
result = np.concatenate((arr1, arr2), axis=[1])
print(result)

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A0

B1

C-1

D2

Attempts:

3 left

💡 Hint

Common Mistakes

Using axis=1 stacks arrays horizontally (side by side), not vertically.

Using axis=2 causes an error because 2D arrays have only axes 0 and 1.

Axis 0 means stacking arrays vertically (row-wise) for 2D arrays.

3fill in blank

hard

Fix the error in the code to concatenate two arrays along columns.

NumPy

import numpy as np
arr1 = np.array([[1, 2], [3, 4]])
arr2 = np.array([[5, 6], [7, 8]])
result = np.concatenate((arr1, arr2), axis=[1])
print(result)

Drag options to blanks, or click blank then click option'

A1

B-1

C2

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Using axis=0 stacks arrays vertically, not horizontally.

Using axis=2 causes an error because 2D arrays have only axes 0 and 1.

Axis 1 means concatenating arrays side by side (column-wise) for 2D arrays.

4fill in blank

hard

Fill both blanks to create a dictionary with word lengths for words longer than 3 letters.

NumPy

words = ['apple', 'bat', 'carrot', 'dog']
lengths = {word: [1] for word in words if len(word) [2] 3}
print(lengths)

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Alen(word)

B>

C<

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using word instead of len(word) as dictionary value.

Using '<' instead of '>' in the condition.

The dictionary comprehension uses len(word) as value and filters words with length greater than 3.

5fill in blank

hard

Fill all three blanks to create a dictionary with uppercase keys and values greater than 0.

NumPy

data = {'a': 1, 'b': -2, 'c': 3}
result = { [1]: [2] for k, v in data.items() if v [3] 0 }
print(result)

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Ak.upper()

Bv

C>

Dk

Attempts:

3 left

💡 Hint

Common Mistakes

Using k instead of k.upper() for keys.

Using '<' instead of '>' in the condition.

Using k instead of v for values.

The dictionary comprehension uses uppercase keys, values v, and filters values greater than 0.