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

One error you may encounter when using NumPy is:

```AttributeError: 'numpy.ndarray' object has no attribute 'index'
```

This error occurs when you attempt to use the index() function on a NumPy array, which does not have an index attribute available to use.

The following example shows how to address this error in practice.

### How to Reproduce the Error

Suppose we have the following NumPy array:

```import numpy as np

#create NumPy array
x = np.array([4, 7, 3, 1, 5, 9, 9, 15, 9, 18])
```

We can use the following syntax to find the minimum and maximum values in the array:

```#find minimum and maximum values of array
min_val = np.min(x)
max_val = np.max(x)

#print minimum and maximum values
print(min_val, max_val)

1 18```

Now suppose we attempt to find the index position of the minimum and maximum values in the array:

```#attempt to print index position of minimum value
x.index(min_val)

AttributeError: 'numpy.ndarray' object has no attribute 'index'
```

We receive an error because we can’t apply an index() function to a NumPy array.

### How to Address the Error

To find the index position of the minimum and maximum values in the NumPy array, we can use the NumPy where() function:

```#find index position of minimum value
np.where(x == min_val)

(array(),)

#find index position of maximum value
np.where(x == max_val)

(array(),)
```

From the output we can see:

• The minimum value in the array is located in index position 3.
• The maximum value in the array is located in index position 9.

We can use this same general syntax to find the index position of any value in a NumPy array.

For example, we can use the following syntax to find which index positions are equal to the value 9 in the NumPy array:

```#find index positions that are equal to the value 9
np.where(x == 9)

(array([5, 6, 8]),)
```

From the output we can see that the values in index positions 5, 6, and 8 are all equal to 9.