# How to find the mode of a list when there are multiple modes – Python

## Question:

I am trying to find out the mode of a list that works, but when there are multiple modes, an error is returned. How would I fix this error in my code?

I want to make it so that it calculates it like how this would be calculated normally `[3, 3, 4, 4] => (3+4)/2 = 3.5`

if that is possible.

```
import statistics
numbers = ['3', '3', '4', '4']
mode = statistics.mode(numbers)
print(f'Mode: {mode}')
```

this is the error I get: statistics.StatisticsError: no unique mode; found 2 equally common values

## Answers:

You likely have an old python version. In recent versions (≥3.8), this should return the **first** mode.

Output: `Mode: banana`

For multiple modes use `statistics.multimode`

:

```
import statistics
food = ['banana', 'banana', 'apple', 'apple']
mode = statistics.multimode(food)
print(f'Mode: {mode}')
```

output: `Mode: ['banana', 'apple']`

With strings as numbers:

```
from statistics import multimode, mean
numbers = ['3', '3', '4', '4']
mode = mean(map(int, multimode(numbers)))
print(f'Mode: {mode}')
```

Output: `Mode: 3.5`

The statistics module does not work on datasets where there can be multiple "modes". This dataset is called as a bimodal dataset. You can approach the problem programmatically in the following way:

```
from collections import Counter
# The Counter function from collections module helps with counting the
# "frequency" of items occurring inside the list
food = ['banana', 'banana', 'apple', 'apple']
data_dictionary = Counter(food)
print(data_dictionary)
# Now that the count of each data-item has been generated,
# The modal, bimodal or n-modal value of the data set can be decided by
# Finding the maximum count of frequencies.
max = 0 # initiating empty variable
modal_data_items = [] # initiating empty list
for key, value in data_dictionary.items():
# If the frequency-value is more that the previously recorded
# max value, then the max value is updated and the modal_values
# list gets updated to contain the data-item
if value > max:
max = value
modal_data_items = [key]
# In the case where, there are multiple modes in the data,
# there is only a need to append more data-items (key)
# into the list of modal-items
elif value == max:
modal_data_items.append(key)
print("The modes of the given data-set are:", modal_data_items)
```

Hope this helps!

You can first use `collections.Counter`

to count the number of occurrences of the elements, then use list comprehension to get the elements of the mode.

```
from collections import Counter
import statistics
result_dict = Counter(numbers)
result = [float(i) for i in result_dict.keys() if result_dict[i] == max(result_dict.values())]
statistics.mean(result)
3.5
```