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NumPy | append method

schedule Aug 12, 2023
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Numpy's `append(~)` method returns a new Numpy array with the specified values appended to the input array.

Parameters

1. `a` | `array_like`

The source array.

2. `values` | `array_like`

The values to append to the source array.

3. `axis` | `int` | `optional`

The axis along which to perform the append. For 2D arrays, the allowed values and their meaning are:

Axis

Meaning

0

Appending rows

1

Appending columns

None

Appending into a flattened array

By default, `axis=None`.

Return value

A new Numpy array with the specified values appended to `a`.

Examples

Appending to a 1D array

``` a = np.array([3,4,5])np.append(a, 8) array([3, 4, 5, 8]) ```

Appending to a 2D array

Consider the following array:

``` a = np.array([[3,4],[5,6]])a array([[3, 4], [5, 6]]) ```

Appending to a flattened 2D array

``` np.append(a, [8,9]) array([3, 4, 5, 6, 8, 9]) ```

Appending rows to a 2D array

Considering the following array:

``` a = np.array([[3,4],[5,6]])a array([[3, 4], [5, 6]]) ```

Appending a single row

``` np.append(a, [[8,9]], axis=0) # axis=0 represents row appends array([[3, 4], [5, 6], [8, 9]]) ```

Appending multiple rows

``` np.append(a, [[8,9], [10,11]], axis=0) array([[ 3, 4], [ 5, 6], [ 8, 9], [10, 11]]) ```

Appending columns to a 2D array

Considering the following array:

``` a = np.array([[3,4],[5,6]])a array([[3, 4], [5, 6]]) ```

Appending a single column

``` np.append(a, [[8],[9]], axis=1) array([[3, 4, 8], [5, 6, 9]]) ```

Appending multiple columns

``` np.append(a, [[8,9],[10,11]], axis=1) array([[ 3, 4, 8, 9], [ 5, 6, 10, 11]]) ```
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