np.vstack() and np.hstack() in NumPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does np.vstack() do in numpy?

np.vstack() stacks arrays vertically (row-wise). It joins arrays by adding rows on top of each other.

beginner

What is the difference between np.vstack() and np.hstack()?

np.vstack() stacks arrays vertically (adds rows). <br>np.hstack() stacks arrays horizontally (adds columns).

beginner

Given two arrays a = np.array([1, 2]) and b = np.array([3, 4]), what is the result of np.vstack((a, b))?

array([[1, 2],
       [3, 4]])

intermediate

What shape must arrays have to be stacked using np.hstack()?

Arrays must have the same number of rows (same first dimension) to stack horizontally.

intermediate

Why might np.vstack() or np.hstack() raise an error?

They raise errors if arrays have incompatible shapes for stacking. For vstack, columns must match; for hstack, rows must match.

What does np.hstack() do?

A Stacks arrays vertically (adds rows)

B Stacks arrays horizontally (adds columns)

C Flattens arrays into 1D

D Splits arrays into parts

np.hstack() stacks arrays side by side, adding columns.

If you have two arrays with shapes (2, 3) and (3, 3), can you use np.vstack() to stack them?

A Yes, because rows differ

B No, because rows differ

C Yes, because columns match

D No, because columns differ

np.vstack() requires arrays to have the same number of columns. Here both have 3 columns, so stacking vertically works.

What shape will the result have after np.hstack() of arrays with shapes (2, 3) and (2, 2)?

A (2, 5)

B (4, 3)

C (2, 1)

D (3, 2)

np.hstack() adds columns, so rows stay 2, columns add: 3 + 2 = 5.

Which numpy function would you use to add rows to an existing array?

A np.hstack()

B np.concatenate() with axis=1

C np.split()

D np.vstack()

np.vstack() stacks arrays vertically, adding rows.

What happens if you try to np.hstack() arrays with different number of rows?

A You get an error about shape mismatch

B They stack successfully

C Arrays get flattened

D Arrays get stacked vertically instead

np.hstack() requires arrays to have the same number of rows. Different rows cause a shape mismatch error.

Explain in your own words how np.vstack() and np.hstack() combine arrays. Give a simple example.

Think about stacking blocks either on top or side by side.

What shape conditions must arrays meet to be stacked with np.vstack() and np.hstack()? Why is this important?

Consider how rows and columns align when stacking.