# What is the numpy.delete() Method

Numpy.delete() method “returns a new array with the deletion of sub-arrays along with the mentioned axis.”

## Syntax

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

## Parameters

The np.delete() function takes three parameters:

1. array: This is the input array.
2. object: This can be any single number or a subarray.
3. axis: This indicates the axis to be deleted from the array.

## Return Value

The numpy delete() function returns the array by deleting the subarray, which was mentioned during the function call.

## Example 1: How to Use numpy.delete() Method

``````# Importing numpy
import numpy as np

# We will create an 1D array

# this will create an array with values 0 to 5
arr1 = np.arange(6)
# Printing the array
print("The array is: ", arr1)

# Now we will call delete() function
# To delete the element 3
object = 3 # 3 is to be deleted

# here arr1 is the main array
# object is the number which is to be deleted
arr = np.delete(arr1, object)

# Printing new array
print("After deleting ", object, " new array is: ")
print(arr)``````

Output

``````The array is: [0 1 2 3 4 5]
After deleting 3 new array is:
[0 1 2 4 5]``````

## Example 2: Remove elements from 2D array

We can also remove elements from a 2D array using the numpy delete() function.

``````# Importing numpy
import numpy as np

# We will create a 2D array
# Of shape 4x3
arr1 = np.array([(1, 2, 3), (4, 5, 6), (7, 8, 9), (50, 51, 52)])
# Printing the array
print("The array is: ")
print(arr1)

# Now we will call delete() function
# To delete the subarray present in array

# This indicates this will delete 3rd column
# Of the array
obj = 2 # 3rd column
axis = 1 # column wise

# here arr1 is the main array
# object is the number which is to be deleted
arr = np.delete(arr1, obj, axis)

# Printing new array
print("After deleting column wise new array is: ")
print(arr)

# Now we will delete 2nd row of the array
arr = np.delete(arr, 1, 0)

# Printing new array
print("After deleting row wise new array is: ")
print(arr)``````

Output

``````The array is:
[[ 1 2 3]
[ 4 5 6]
[ 7 8 9]
[50 51 52]]
After deleting column wise new array is:
[[ 1 2]
[ 4 5]
[ 7 8]
[50 51]]
After deleting row wise new array is:
[[ 1 2]
[ 7 8]
[50 51]]``````

That’s it.

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