# NumPy - hstack() function

The NumPy hstack() function stacks arrays in sequence horizontally (column wise). This is equivalent to concatenation along the second axis, except for 1-D arrays where it concatenates along the first axis.

### Syntax

```numpy.hstack(tup)
```

### Parameters

 `tup` `Required. `Specify sequence of ndarrays to be horizontally stacked. The arrays must have the same shape along all but the second axis, except 1-D arrays which can be any length.

### Return Value

Returns the array formed by stacking the given arrays.

### Example:

In the example below, hstack() function is used to stack two given arrays.

```import numpy as np

Arr1 = np.array([[10,20],[30, 40]])
Arr2 = np.array([[50,60],[70, 80]])

#stacking arrays horizontally
Arr3 = np.hstack((Arr1, Arr2))

#displaying results
print("Arr1 is:")
print(Arr1)
print("\nArr2 is:")
print(Arr2)
print("\nArr3 is:")
print(Arr3)
```

The output of the above code will be:

```Arr1 is:
[[10 20]
[30 40]]

Arr2 is:
[[50 60]
[70 80]]

Arr3 is:
[[10 20 50 60]
[30 40 70 80]]
```

### Example:

Consider one more example, where two arrays has same shape along all except different second axis.

```import numpy as np

Arr1 = np.array([[10,20],[30, 40]])
Arr2 = np.array([[50,60,70],[80,90,100]])

#stacking arrays horizontally
Arr3 = np.hstack((Arr1, Arr2))

#displaying results
print("Arr1 is:")
print(Arr1)
print("\nArr2 is:")
print(Arr2)
print("\nArr3 is:")
print(Arr3)
```

The output of the above code will be:

```Arr1 is:
[[10 20]
[30 40]]

Arr2 is:
[[ 50  60  70]
[ 80  90 100]]

Arr3 is:
[[ 10  20  50  60  70]
[ 30  40  80  90 100]]
```

❮ NumPy - Array Manipulation

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