# NumPy - hsplit() function

The NumPy hsplit() function splits an array into multiple sub-arrays horizontally (column-wise).

### Syntax

```numpy.hsplit(ary, indices_or_sections)
```

### Parameters

 `ary` `Required. `Specify the array (ndarray) to be divided into sub-arrays.. `indices_or_sections` `Required. ` Specify indices_or_sections as int or 1-D array. If indices_or_sections is an integer, N, the array will be divided into N equal arrays horizontally. If such a split is not possible, an error is raised. If indices_or_sections is a 1-D array of sorted integers, the entries indicate where the array is split horizontally. If an index exceeds the dimension of the array horizontally, an empty sub-array is returned correspondingly.

### Return Value

Returns a list of sub-arrays as views into ary.

### Example:

In the example below, hsplit() function is used to split a given array.

```import numpy as np

Arr = np.array([[10, 20, 30],
[30, 40, 60],
[70, 80, 90]])

#splitting the array
Arr1 = np.hsplit(Arr, 3)

#displaying results
print("Arr is:")
print(Arr)
print("\nArr1 is:")
print(Arr1)
```

The output of the above code will be:

```Arr is:
[[10 20 30]
[30 40 60]
[70 80 90]]

Arr1 is:
[array([,
,
]), array([,
,
]), array([,
,
])]
```

### Example: indices_or_sections as 1-D array

When indices_or_sections is passed as 1-D array of sorted integers, the entries indicate where the array is split horizontally. Consider the following example.

```import numpy as np

Arr = np.array([[10, 20, 30, 40],
[50, 60, 70, 80],
[90, 100, 200, 300]])

#splitting the array
Arr1 = np.hsplit(Arr, [2,3])

#displaying results
print("Arr is:")
print(Arr)
print("\nArr1 is:")
print(Arr1)
```

The output of the above code will be:

```Arr is:
[[ 10  20  30  40]
[ 50  60  70  80]
[ 90 100 200 300]]

Arr1 is:
[array([[ 10,  20],
[ 50,  60],
[ 90, 100]]), array([[ 30],
[ 70],
]), array([[ 40],
[ 80],
])]
```

❮ NumPy - Array Manipulation

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