Home Â» How to Calculate the Mode of NumPy Array (With Examples)

# How to Calculate the Mode of NumPy Array (With Examples)

You can use the following basic syntax to find the mode of a NumPy array:

```#find unique values in array along with their counts
vals, counts = np.unique(array_name, return_counts=True)

#find mode
mode_value = np.argwhere(counts == np.max(counts))```

Recall that the mode is the value that occurs most often in an array.

Note that itâ€™s possible for an array to have one mode or multiple modes.

The following examples show how to use this syntax in practice.

### Example 1: Calculating Mode of NumPy Array with Only One Mode

The following code shows how to find the mode of a NumPy array in which there is only one mode:

```import numpy as np

#create NumPy array of values with only one mode
x = np.array([2, 2, 2, 3, 4, 4, 5, 5, 5, 5, 7])

#find unique values in array along with their counts
vals, counts = np.unique(x, return_counts=True)

#find mode
mode_value = np.argwhere(counts == np.max(counts))

#print list of modes
print(vals[mode_value].flatten().tolist())

[5]

#find how often mode occurs
print(np.max(counts))

4```

From the output we can see that the mode is 5 and it occurs 4 times in the NumPy array.

### Example 2: Calculating Mode of NumPy Array with Multiple Modes

The following code shows how to find the mode of a NumPy array in which there are multiple modes:

```import numpy as np

#create NumPy array of values with multiple modes
x = np.array([2, 2, 2, 3, 4, 4, 4, 5, 5, 5, 7])

#find unique values in array along with their counts
vals, counts = np.unique(x, return_counts=True)

#find mode
mode_value = np.argwhere(counts == np.max(counts))

#print list of modes
print(vals[mode_value].flatten().tolist())

[2, 4, 5]

#find how often mode occurs
print(np.max(counts))

3```

From the output we can see that this NumPy array has three modes: 2, 4, and 5.

We can also see that each of these values occurs 3 times in the array.