Introduction
In this tutorial, we want to join NumPy arrays along different axes. In order to do this, we use the functions hstack(), vstack() and dstack() of NumPy.
Import Libraries
First, we import the following python module:
import numpy as np
Define Data
Let's consider two arrays a and b.
Array a
a = np.array([5,7,8])
print(a)
a.shape
Array b
b = np.array([4,2,1])
print(b)
b.shape
Horizontal Stacking
For stacking a sequence of arrays horizontally (column wise), the NumPy function hstack() can be used. The arrays are joined together along the first axis.
hstacked = np.hstack((a,b))
print(hstacked)
hstacked.shape
Vertical Stacking
For stacking a sequence of arrays vertically (row wise), the NumPy function vstack() can be used. The arrays are joined together along the second axis.
vstacked = np.vstack((a,b))
print(vstacked)
vstacked.shape
Depth Wise Stacking
For stacking a sequence of arrays depth wise, the NumPy function dstack() can be used. The arrays are joined together along the third axis.
dstacked = np.dstack((a,b))
print(dstacked)
dstacked.shape
Conclusion
Congratulations! Now you are one step closer to become an AI Expert. You have seen that it is very easy to join NumPy arrays along different axes. We can simply use the functions hstack(), vstack() and dstack() of NumPy. Try it yourself!
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