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# How to append two NumPy Arrays?

Prerequisites: Numpy

Two arrays in python can be appended in multiple ways and all possible ones are discussed below.

### Method 1: Using append() method

This method is used to Append values to the end of an array.

Syntax :

numpy.append(array, values, axis = None)

Parameters :

• array: [array_like]Input array.
• values : [array_like]values to be added in the arr. Values should be
shaped so that arr[…,obj,…] = values. If the axis is defined values can be of any
shape as it will be flattened before use.

• axis : Axis along which we want to insert the values. By default, array is flattened.

Return :

A copy of array with values being appended at the end as per the mentioned object, along a given axis.

Example:

## Python3

 `import` `numpy`  `array1 ``=` `numpy.array([``1``, ``2``, ``3``, ``4``, ``5``])``array2 ``=` `numpy.array([``6``, ``7``, ``8``, ``9``, ``10``])` `# Appending both arrays using Append method``array1 ``=` `numpy.append(array1, array2)``print``(array1)`

Output:

[ 1  2  3  4  5  6  7  8  9 10]

### Method 2: Using concatenate() method

Concatenate method Joins a sequence of arrays along an existing axis.

Syntax :

numpy.concatenate((arr1, arr2, …), axis=0, out=None)

Parameters :

• arr1, arr2, … : [sequence of array_like] The arrays must have the same shape, except in the dimension corresponding to axis.
• axis : [int, optional] The axis along which the arrays will be joined. If axis is None, arrays are flattened before use. Default is 0.
• out : [ndarray, optional] If provided, the destination to place the result. The shape must be correct, matching that of what concatenate would have returned if no out argument were specified.

Return : [ndarray] The concatenated array.

Example:

## Python3

 `import` `numpy`  `array1 ``=` `numpy.array([``1``, ``2``, ``3``, ``4``, ``5``])``array2 ``=` `numpy.array([``6``, ``7``, ``8``, ``9``, ``10``])` `# Appending both Arrays using concatenate() method.``array1 ``=` `numpy.concatenate([array1, array2])``print``(array1)`

Output:

[ 1  2  3  4  5  6  7  8  9 10]

### Method 3: Using stack() method

Stack method Joins a sequence of arrays along a new axis.

Syntax : numpy.stack(arrays, axis)

Parameters :

• arrays : [array_like] Sequence of arrays of the same shape.
• axis : [int] Axis in the resultant array along which the input arrays are stacked.

Return : [stacked ndarray] The stacked array of the input arrays which has one more dimension than the input arrays.

Example:

## Python3

 `import` `numpy`  `array1 ``=` `numpy.array([``1``, ``2``, ``3``, ``4``, ``5``])``array2 ``=` `numpy.array([``6``, ``7``, ``8``, ``9``, ``10``])` `# Join a sequence of arrays along a new axis.``array1 ``=` `numpy.stack([array1, array2])``print``(array1)`

Output:

[[ 1  2  3  4  5]

[ 6  7  8  9 10]]

### Method 4: Using hstack() method

hstack method Stacks arrays in sequence horizontally (column wise).

Syntax : numpy.hstack(tup)

Parameters :

• tup : [sequence of ndarrays] Tuple containing arrays to be stacked. The arrays must have the same shape along all but the second axis.

Return : [stacked ndarray] The stacked array of the input arrays.

Example:

## Python3

 `import` `numpy`  `array1 ``=` `numpy.array([``1``, ``2``, ``3``, ``4``, ``5``])``array2 ``=` `numpy.array([``6``, ``7``, ``8``, ``9``, ``10``])` `# Stack arrays in sequence horizontally (column wise).``array1 ``=` `numpy.hstack([array1, array2])``print``(array1)`

Output:

[ 1  2  3  4  5  6  7  8  9 10]

### Method 5: Using vstack() method

vstack method Stacks arrays in sequence vertically (row wise).

Syntax : numpy.vstack(tup)

Parameters :

• tup : [sequence of ndarrays] Tuple containing arrays to be stacked. The arrays must have the same shape along all but the first axis.

Return : [stacked ndarray] The stacked array of the input arrays.

Example:

## Python3

 `import` `numpy`  `array1 ``=` `numpy.array([``1``, ``2``, ``3``, ``4``, ``5``])``array2 ``=` `numpy.array([``6``, ``7``, ``8``, ``9``, ``10``])` `# Stack arrays in sequence vertically (row wise).``array1 ``=` `numpy.vstack([array1, array2])``print``(array1)`

Output:

[[ 1  2  3  4  5]

[ 6  7  8  9 10]]

### Method 6: Using column_stack() method

The column_stack() method Stacks arrays as columns into a 2-D array.

Syntax: column_stack( array)

## Python3

 `import` `numpy`  `array1 ``=` `numpy.array([``1``, ``2``, ``3``, ``4``, ``5``])``array2 ``=` `numpy.array([``6``, ``7``, ``8``, ``9``, ``10``])` `# Stack 1-D arrays as columns into a 2-D array.``array1 ``=` `numpy.column_stack([array1, array2])``print``(array1)`

Output:

```[[ 1  6]
[ 2  7]
[ 3  8]
[ 4  9]
[ 5 10]]```

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