How to Use np.vstack in NumPy: Stack Arrays Vertically

Use np.vstack to stack arrays vertically (row-wise) in NumPy. It takes a sequence of arrays with the same number of columns and joins them into one array by adding rows.

Syntax

The basic syntax of np.vstack is:

• np.vstack(tup): where tup is a tuple or list of arrays to stack.
• All arrays must have the same number of columns (same shape except for the first dimension).
• The result is a new array with rows stacked vertically.

python

np.vstack(tup)

Example

This example shows how to stack two 2D arrays vertically using np.vstack. The arrays must have the same number of columns.

python

import numpy as np

array1 = np.array([[1, 2], [3, 4]])
array2 = np.array([[5, 6], [7, 8]])

result = np.vstack((array1, array2))
print(result)

Output

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

Common Pitfalls

Common mistakes when using np.vstack include:

• Trying to stack arrays with different numbers of columns, which causes a ValueError.
• Passing arrays not wrapped in a tuple or list.
• Confusing vstack with hstack, which stacks arrays horizontally (column-wise).

python

import numpy as np

# Wrong: arrays have different number of columns
try:
    a = np.array([[1, 2]])
    b = np.array([[3, 4, 5]])
    np.vstack((a, b))
except ValueError as e:
    print(f"Error: {e}")

# Right: arrays have the same number of columns
c = np.array([[3, 4]])
result = np.vstack((a, c))
print(result)

Output

Error: all the input array dimensions except for the concatenation axis must match exactly
[[1 2]
 [3 4]]

Quick Reference

Function	Description
np.vstack(tup)	Stack arrays vertically (row-wise)
np.hstack(tup)	Stack arrays horizontally (column-wise)
np.concatenate(tup, axis=0)	General concatenation along rows
np.concatenate(tup, axis=1)	General concatenation along columns

Key Takeaways

np.vstack stacks arrays vertically by adding rows.

All arrays must have the same number of columns to use np.vstack.

Pass arrays as a tuple or list to np.vstack.

np.vstack differs from np.hstack which stacks arrays horizontally.

Mismatched column sizes cause errors with np.vstack.