NumPy Splitting Array
Splitting NumPy Arrays
Splitting is reverse operation of Joining.
Joining merges multiple arrays into one and Splitting breaks one array into multiple.
We use array_split() for splitting arrays, we pass it the array we want to split
and the number of splits.
Example
Split the array in 3 parts:
import numpy as np
arr = np.array([1, 2, 3, 4, 5, 6])
newarr =
np.array_split(arr, 3)
print(newarr)
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Note: The return value is a list containing three arrays.
If the array has less elements than required, it will adjust from the end accordingly.
Example
Split the array in 4 parts:
import numpy as np
arr = np.array([1, 2, 3, 4, 5, 6])
newarr =
np.array_split(arr, 4)
print(newarr)
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Note: We also have the method split() available but it will not adjust the elements when elements are less in
source array for splitting like in example above, array_split() worked properly but
split() would fail.
Split Into Arrays
The return value of the array_split() method is an array containing each of the split as an array.
If you split an array into 3 arrays, you can access them from the result just like any array element:
Example
Access the splitted arrays:
import numpy as np
arr = np.array([1, 2, 3, 4, 5, 6])
newarr =
np.array_split(arr, 3)
print(newarr[0])
print(newarr[1])
print(newarr[2])
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Splitting 2-D Arrays
Use the same syntax when splitting 2-D arrays.
Use the array_split() method, pass in the array
you want to split
and the number of splits you want to do.
Example
Split the 2-D array into three 2-D arrays.
import numpy as np
arr = np.array([[1, 2], [3, 4], [5, 6], [7, 8], [9,
10], [11, 12]])
newarr = np.array_split(arr, 3)
print(newarr)
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The example above returns three 2-D arrays.
Let's look at another example, this time each element in the 2-D arrays contains 3 elements.
Example
Split the 2-D array into three 2-D arrays.
import numpy as np
arr = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9], [10,
11, 12], [13, 14, 15], [16, 17, 18]])
newarr = np.array_split(arr, 3)
print(newarr)
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The example above returns three 2-D arrays.
In addition, you can specify which axis you want to do the split around.
The example below also returns three 2-D arrays, but they are split along the row (axis=1).
Example
Split the 2-D array into three 2-D arrays along rows.
import numpy as np
arr = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9], [10,
11, 12], [13, 14, 15], [16, 17, 18]])
newarr = np.array_split(arr, 3, axis=1)
print(newarr)
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An alternate solution is using hsplit() opposite of
hstack()
Example
Use the hsplit() method to split the 2-D array into three 2-D arrays along rows.
import numpy as np
arr = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9],
[10, 11, 12], [13, 14, 15], [16, 17, 18]])
newarr = np.hsplit(arr, 3)
print(newarr)
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Note: Similar alternates to vstack() and
dstack() are available as
vsplit() and
dsplit().
