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NumPy | insert method

schedule Aug 10, 2023
Last updated
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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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Published by Isshin Inada
Edited by 0 others
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