NumPy Stacking & Splitting Arrays 📊
1. Vertical stacking with vstack()
vstack() stacks arrays vertically (row-wise), adding arrays on top of each other.
Long form
import numpy as np
a = np.array([1, 2, 3])
b = np.array([4, 5, 6])
stacked = np.vstack((a, b))
One-liner
stacked = __import__('numpy').vstack((__import__('numpy').array([1,2,3]), __import__('numpy').array([4,5,6])))
Here, two 1D arrays become a 2×3 matrix:
[[1, 2, 3],
[4, 5, 6]]
2. Horizontal stacking with hstack()
hstack() stacks arrays horizontally (column-wise), joining them side by side.
Long form
import numpy as np
a = np.array([1, 2, 3])
b = np.array([4, 5, 6])
stacked = np.hstack((a, b))
One-liner
stacked = __import__('numpy').hstack((__import__('numpy').array([1,2,3]), __import__('numpy').array([4,5,6])))
This results in [1, 2, 3, 4, 5, 6], a longer 1D array.
3. Column stacking with column_stack()
column_stack() stacks 1D arrays as columns into a 2D array.
Long form
import numpy as np
a = np.array([1, 2, 3])
b = np.array([4, 5, 6])
stacked = np.column_stack((a, b))
One-liner
stacked = __import__('numpy').column_stack((__import__('numpy').array([1,2,3]), __import__('numpy').array([4,5,6])))
Here, arrays are stacked as columns, producing:
[[1, 4],
[2, 5],
[3, 6]]
4. Splitting arrays with split()
The split() function divides arrays into multiple sub-arrays of equal size.
Long form
import numpy as np
arr = np.arange(9)
split_arr = np.split(arr, 3)
One-liner
split_arr = __import__('numpy').split(__import__('numpy').arange(9),3)
This splits [0,1,2,3,4,5,6,7,8] into three arrays: [0,1,2], [3,4,5], [6,7,8].
5. Splitting arrays with hsplit() and vsplit()
These functions split arrays horizontally (columns) or vertically (rows).
Long form
import numpy as np
matrix = np.arange(16).reshape(4, 4)
h_split = np.hsplit(matrix, 2)
v_split = np.vsplit(matrix, 2)
One-liner
h_split,v_split = __import__('numpy').hsplit(__import__('numpy').arange(16).reshape(4,4),2), __import__('numpy').vsplit(__import__('numpy').arange(16).reshape(4,4),2)
Here, hsplit divides the 4×4 matrix into two 4×2 arrays (columns), while vsplit divides it into two 2×4 arrays (rows).
5 Interview Questions (with Answers):
Q: What is the difference between vstack() and hstack()?
A: vstack() stacks arrays vertically (row-wise), while hstack() stacks them horizontally (column-wise).
Q: When should you use column_stack()?
A: Use it when you want to combine multiple 1D arrays into columns of a 2D array.
Q: What happens if you try to split an array into unequal parts using split()?
A: NumPy raises a ValueError; for unequal splits, use array_split() instead.
Q: What’s the difference between split() and array_split()?
A: split() requires equal division, while array_split() allows unequal division of arrays.
Q: How are hsplit() and vsplit() different from split()?
A: hsplit() and vsplit() specifically split along horizontal (columns) or vertical (rows) axes, whereas split() works on any axis.
Hashtags:
#numpy #Python #DataScience #MachineLearning #ArrayStacking #ArraySplitting #CodingTips #InterviewPrep
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