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# NumPy | insert method

schedule Aug 10, 2023
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Numpy's `insert(~)` method returns a new Numpy array with the specified values inserted.

# Parameters

1. `a` | `array-like`

The source array.

2. `obj` | `slice` or `int` or `array` of `int`

The subset of indices to insert along the specified axis.

3. `values` | `array-like`

The values to insert into the source array.

4. `axis` | `int` | `optional`

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

Axis

Meaning

0

Insert rows

1

Insert columns

None

Insert into a flattened array

By default, the `axis=None`.

# Return value

A new Numpy array with the specified values inserted.

# Examples

## Inserting into a 1D array

To insert the value 8 at index 1:

``` a = np.array([4,5,6])np.insert(a, 1, 8) array([4, 8, 5, 6]) ```

## Inserting to a flattened 2D array

Consider the following 2D array:

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

### Inserting a single value

To insert into the flattened version of the array:

``` np.insert(a, 1, 9) array([3, 9, 4, 5, 6]) ```

Here, we're inserting the value 9 at index 1 of the flattened version of `a`.

### Inserting multiple values

To insert multiple values into the flattened version of the array:

``` np.insert(a, [0,3], [8,9]) array([8, 3, 4, 5, 9, 6]) ```

Here, we're inserting the values 8 and 9 into indices 0 and 3.

## Inserting rows to a 2D array

### Inserting a single row

Consider the following:

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

To insert a single row at index 1:

``` np.insert(a, 1, [8,9], axis=0) # axis=0 represents row-insertion array([[ 3, 4], [ 8, 9], [ 5, 6]]) ```

### Inserting multiple rows

Consider the following:

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

To insert two distinct rows at index 0 and 1:

``` np.insert(a, [0,1], [[10,11],[12,13]], axis=0) array([[10, 11], [ 3, 4], [12, 13], [ 5, 6]]) ```

Notice how the row `[12,13]` is added to the 1st index of the original array.

## Inserting columns to a 2D array

### Inserting a single column

Consider the following:

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

To insert a single column at index 1:

``` np.insert(a, 1, [8,9], axis=1) # axis=1 represents column-insertion array([[ 3, 8, 4], [ 5, 9, 6]]) ```

### Inserting multiple columns

Consider the following:

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

To insert two distinct columns at index 0 and 2:

``` np.insert(a, [0,2], [[10,11],[12,13]], axis=1) # axis=1 represents column-insertion array([[10, 3, 4, 11], [12, 5, 6, 13]]) ```
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