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
CodePudding user response:
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']
CodePudding user response:
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!