# NumPy delete()

The `delete()` method deletes the values at specified indices.

### Example

``````import numpy as np

array1 = np.array([0, 1, 2, 3])

# delete at index 2
array2 = np.delete(array1, 2)

print(array2)

# Output: [0 1 3]``````

## delete() Syntax

The syntax of `delete()` is:

``numpy.delete(array, obj, axis = None)``

## delete() Arguments

The `delete()` method takes four arguments:

• `array` - array to delete elements from
• `obj` - indices at which values are deleted
• `axis`(optional) - the axis along which the values are deleted

Note: By default, `axis` is `None`, and the array is flattened.

## delete() Return Value

The `delete()` method returns an array with values deleted.

## Example 1: Delete an Array Element at Given Index

``````import numpy as np

array1 = np.array([0, 1, 2, 3])

# delete values from array1 at index 2
newArray = np.delete(array1, 2)

print(newArray)``````

Output

`[0 1 3]`

## Example 2: Delete an Array Element at Given Indices

We can delete different array elements at different indices.

``````import numpy as np

array1 = np.array([0, 1, 2, 3])
indices = [1, 2]

# delete values  at indices 1 and 2
array3 = np.delete(array1, obj = indices)

print(array3)``````

Output

`[0 3]`

## Example 3: Delete Element of a 2-D Array

Similar to a 1-D array, we can delete elements from a 2-D array at any index.

We can also delete an entire row or column using the axis parameter. If `axis` = 0, row is deleted and if `axis` = 1, column is deleted.

``````import numpy as np

array1 = np.array([[0, 1], [2, 3]])

# no axis, element at index 1 is deleted
array3 = np.delete(array1, 1)

print('Array after deleting element at index 1\n', array3)

# axis = 0, row 1 is deleted
array4 = np.delete(array1, 1, axis = 0)

print('\nArray after deleting row 1\n', array4)

# axis = 1, column 1 is deleted
array5 = np.delete(array1, 1, axis = 1)

print('\nArray after deleting column 1\n', array5)``````

Output

```Array after deleting element at index 1
[0 2 3]

Array after deleting row 1
[[0 1]]

Array after deleting column 1
[[0]
[2]]```

## Example 4: Delete Multiple Elements of a 2-D Array

``````import numpy as np

array1 = np.array([[0, 1, 2],
[3, 4, 5],
[6, 7, 8],
[9, 10, 11]])

# delete elements at indices 0 and 1
array3 = np.delete(array1, [0, 1])

print('\nArray after deleting elements at indices 0 and 1\n', array3)

# axis=0, delete elements of row 0 and 1
array4 = np.delete(array1, [0, 1], axis=0)

print('\nArray after deleting row 0 and 1\n', array4)

# axis=1, delete elements of column 0 and 1
array5 = np.delete(array1, [0, 1], axis=1)

print('\nArray after deleting column 0 and 1\n', array5)``````

Output

```Array after deleting elements at indices 0 and 1
[ 2  3  4  5  6  7  8  9 10 11]

Array after deleting row 0 and 1
[[ 6  7  8]
[ 9 10 11]]

Array after deleting column 0 and 1
[[ 2]
[ 5]
[ 8]
[11]]```

## Example 5: Delete Array Based on Conditions

We can also use `delete()` to eliminate the items of an array that satisfy a given condition.

``````import numpy as np

array1 = np.array([0, 1, 2, 3, 4, 5])

# delete elements that satisfies the condition
array5 = np.delete(array1, array1[array1%2 == 1])

print('Array after deleting odd elements \n', array5)``````

Output

```Array after deleting odd elements
[0 2 4]```

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