# NumPy - argmax() function

The NumPy argmax() function returns the indices of the maximum values along an axis. It is calculated over the flattened array by default, otherwise over the specified axis.

### Syntax

```numpy.argmax(a, axis=None, out=None)
```

### Parameters

 `a` `Required. `Specify the input array (array_like). `axis` `Optional. `Specify axis or axes along which the indices of the maximum values are computed. The default is to compute it over the flattened array. `out` `Optional. `Specify output array for the result. The default is None. If provided, it must have the same shape as output.

### Return Value

Returns an array containing indices of the maximum values when out=None, otherwise returns a reference to the output array.

### Example:

In the example below, argmax() function is used to find out index of the maximum value in the whole array.

```import numpy as np
Arr = np.arange(12).reshape(3,4)

print("Array is:")
print(Arr)

#index of maximum value
idx = np.argmax(Arr)
print("\nIndex of maximum value is:", idx)
```

The output of the above code will be:

```Array is:
[[ 0  1  2  3]
[ 4  5  6  7]
[ 8  9 10 11]]

Index of maximum value is: 11
```

### Example:

When axis parameter is provided, index of maximum value can be calculated over the specified axes. Consider the following example.

```import numpy as np
Arr = np.arange(12).reshape(3,4)

print("Array is:")
print(Arr)

#Index of maximum value along axis=0
print("\nIndex of maximum value along axis=0")
print(np.argmax(Arr, axis=0))

#Index of maximum value along axis=1
print("\nIndex of maximum value along axis=1")
print(np.argmax(Arr, axis=1))
```

The output of the above code will be:

```Array is:
[[ 0  1  2  3]
[ 4  5  6  7]
[ 8  9 10 11]]

Index of maximum value along axis=0
[2 2 2 2]

Index of maximum value along axis=1
[3 3 3]
```

### Example:

When the array contains more than one maximum value, the function returns index of first occurrence of it.

```import numpy as np
Arr = [10, 20, 50, 20, 30, 50, 50]

print("Array is:", Arr)

#Index of maximum value
print("Index of maximum value is:", np.argmax(Arr))
```

The output of the above code will be:

```Array is: [10, 20, 50, 20, 30, 50, 50]
Index of maximum value is: 2
```

❮ NumPy - Functions

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