NumPy Joining Array
🔗 NumPy Joining Arrays (Complete Guide)
Joining (or concatenating) arrays means combining two or more arrays into a single array.
NumPy provides multiple functions to join arrays:
✔ concatenate()
✔ stack()
✔ hstack()
✔ vstack()
✔ dstack()
✔ column_stack()
✅ 1. Joining Using np.concatenate()
Output:
✔ Works for 1D, 2D, 3D arrays
✔ Must match dimension size except along joining axis.
🔹 Concatenate 2D Arrays
✅ 2. Joining Using stack()
Stack arrays along a new axis:
Output:
🔹 Using axis
Output:
✅ 3. hstack() — Join Horizontally (Row-wise)
Output:
✅ 4. vstack() — Join Vertically (Column-wise)
Output:
✅ 5. dstack() — Join Depth-wise (3D stacking)
Output:
✅ 6. column_stack() — Stack Column Format
Output:
🧠Summary Table of Joining Methods
| Function | Type of Join | Result |
|---|---|---|
concatenate() |
Join along existing axis | Flexible |
stack() |
Create new dimension | 2D/3D stacking |
hstack() |
Horizontal stacking | Side-by-side |
vstack() |
Vertical stacking | Top-bottom |
dstack() |
Depth stacking | 3D |
column_stack() |
Column-wise stacking | Matrix style |
