np.vstack() and np.hstack() in NumPy - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of np.vstack() with 1D arrays

What is the output of this code?

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

NumPy

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

A

[[1 4]
 [2 5]
 [3 6]]

B

[[1 2 3]
 [4 5 6]]

C [1 2 3 4 5 6]

D

[[1 2 3]
 [4 5 6]
 [1 2 3]]

💡 Hint

np.vstack stacks arrays vertically, adding rows.

np.vstack stacks arrays vertically, so two 1D arrays become two rows in a 2D array.

❓ Predict Output

intermediate

Output of np.hstack() with 2D arrays

What is the output of this code?

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

NumPy

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

A [[1 2 3 4 5 6 7 8]]

B

[[1 2]
 [3 4]
 [5 6]
 [7 8]]

C

[[1 5]
 [2 6]
 [3 7]
 [4 8]]

D

[[1 2 5 6]
 [3 4 7 8]]

💡 Hint

np.hstack stacks arrays horizontally, adding columns.

np.hstack joins arrays side by side, so columns are added horizontally.

❓ data_output

advanced

Shape after stacking arrays with np.vstack and np.hstack

Given these arrays:

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

What is the shape of the result after applying np.vstack((arr1, arr2)) and np.hstack((arr1, arr2)) respectively?

NumPy

import numpy as np
arr1 = np.array([[1, 2, 3]])
arr2 = np.array([[4, 5, 6]])
vstack_result = np.vstack((arr1, arr2))
hstack_result = np.hstack((arr1, arr2))
print(vstack_result.shape, hstack_result.shape)

A (2, 3) and (1, 6)

B (2, 6) and (1, 3)

C (3, 2) and (6, 1)

D (1, 6) and (2, 3)

💡 Hint

vstack adds rows, hstack adds columns.

vstack stacks arrays vertically increasing rows; hstack stacks horizontally increasing columns.

🔧 Debug

advanced

Error when stacking arrays with incompatible shapes

What error does this code raise?

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

NumPy

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

A TypeError: unsupported operand type(s) for +: 'int' and 'list'

B No error, runs successfully

C ValueError: all the input arrays must have same number of dimensions

D IndexError: index out of range

💡 Hint

np.vstack requires arrays to have the same number of dimensions.

vstack requires all arrays to have the same number of dimensions; mixing 1D and 2D arrays causes ValueError.

🚀 Application

expert

Combining arrays for data analysis

You have two numpy arrays representing data from two sensors:

sensor1 = np.array([[10, 20], [30, 40]])
sensor2 = np.array([[50, 60], [70, 80]])

You want to create a single array where sensor2 data is stacked below sensor1 data, and then another array where sensor2 data is stacked to the right of sensor1 data.
Which code correctly creates these two arrays?

NumPy

import numpy as np
sensor1 = np.array([[10, 20], [30, 40]])
sensor2 = np.array([[50, 60], [70, 80]])

A

vertical_stack = np.concatenate((sensor1, sensor2), axis=0)
horizontal_stack = np.concatenate((sensor1, sensor2), axis=1)

B

vertical_stack = np.hstack((sensor1, sensor2))
horizontal_stack = np.vstack((sensor1, sensor2))

C

vertical_stack = np.vstack((sensor1, sensor2))
horizontal_stack = np.hstack((sensor1, sensor2))

D

vertical_stack = np.concatenate((sensor1, sensor2), axis=1)
horizontal_stack = np.concatenate((sensor1, sensor2), axis=0)

💡 Hint

axis=0 stacks rows (vertical), axis=1 stacks columns (horizontal).

np.vstack is equivalent to np.concatenate with axis=0; np.hstack is equivalent to np.concatenate with axis=1.