How to Fix: ‘numpy.ndarray’ object has no attribute ‘index’

‘numpy.ndarray’ object has no attribute ‘index’ is an attribute error which indicates that there is no index method or attribute available to use in Numpy array.

This error occurs when we try to find the index of a particular element in a Numpy array using the index method. Below code is an example when that ‘numpy.ndarray’ object has no attribute ‘index’ error can be thrown

Example:

# import necessary packages
import numpy as np

# Create a Numpy array
numbers = np.array([0, 1, 2, 9, 8, 0])

# finding the index value of 9 in 
# numbers array
numbers.index(9)

Output

 As there is no method called index in Numpy it throws an attribute error.

Solution

To fix this error instead of using index method to find the index of an element use where method which returns an array consists of indexes of a specified element.

Syntax

Numpy.where(arrayName==value_to_find_index)

Example 1:

Specify an element in where method which exist in a Numpy array

# import necessary packages
import numpy as np

# Create a Numpy array
numbers = np.array([0, 1, 2, 9, 8, 0])

# finding the index value of 9 in 
# numbers array
np.where(numbers == 9)

Output

(array([3], dtype=int64),)

 As Indexes in array starts from 0, Here in the numbers array 0^th index consists of value 0, 1^st index has value 1, 2^nd index has value 2 and 3^rd index has value 9 which is specified so it returned an array which contains a value 3.

Example 2:

Specify an element in where method such that the element we specified is occurred more than once in an array.

# import necessary packages
import numpy as np

# Create a Numpy array
numbers = np.array([0, 1, 2, 9, 8, 0])

# finding the index values of 0 in
# numbers array
np.where(numbers == 0)

Output:

(array([0, 5], dtype=int64),)

 As element 0 occurred 2 times in numbers array at 0^th & 5^th index so it return an array consists of 2 index values of element 0.

Example 3:

Pass an element to where method which is actually not in an array.

# import necessary packages
import numpy as np

# Create a Numpy array
numbers = np.array([0, 1, 2, 9, 8, 0])

# finding the index value of a number 
# which is not in numbers array
np.where(numbers == 7)

Output

(array([], dtype=int64),)

If we pass an element to where method which is not in an array then it returns an empty array because there is no specified element at any index of an array. Here 7 is not present in numbers array so it returned an empty array.