Given a list of items, recall that the mode of the list is the item that occurs most often.
I would like to know how to create a function that can find the mode of a list but that displays a message if the list does not have a mode (e.g., all the items in the list only appear once). I want to make this function without importing any functions. I'm trying to make my own function from scratch.
You can use the max function and a key. Have a look at python max function using 'key' and lambda expression.
max(set(list), key=list.count)
You can use the Counter supplied in the collections package which has a mode-esque function
from collections import Counter
data = Counter(your_list_in_here)
data.most_common() # Returns all unique items and their counts
data.most_common(1) # Returns the highest occurring item
Note: Counter is new in python 2.7 and is not available in earlier versions.
Python 3.4 includes the method statistics.mode, so it is straightforward:
>>> from statistics import mode
>>> mode([1, 1, 2, 3, 3, 3, 3, 4])
3
You can have any type of elements in the list, not just numeric:
>>> mode(["red", "blue", "blue", "red", "green", "red", "red"])
'red'
Taking a leaf from some statistics software, namely SciPy and MATLAB, these just return the smallest most common value, so if two values occur equally often, the smallest of these are returned. Hopefully an example will help:
>>> from scipy.stats import mode
>>> mode([1, 2, 3, 4, 5])
(array([ 1.]), array([ 1.]))
>>> mode([1, 2, 2, 3, 3, 4, 5])
(array([ 2.]), array([ 2.]))
>>> mode([1, 2, 2, -3, -3, 4, 5])
(array([-3.]), array([ 2.]))
Is there any reason why you can 't follow this convention?
There are many simple ways to find the mode of a list in Python such as:
import statistics
statistics.mode([1,2,3,3])
>>> 3
Or, you could find the max by its count
max(array, key = array.count)
The problem with those two methods are that they don't work with multiple modes. The first returns an error, while the second returns the first mode.
In order to find the modes of a set, you could use this function:
def mode(array):
most = max(list(map(array.count, array)))
return list(set(filter(lambda x: array.count(x) == most, array)))
Extending the Community answer that will not work when the list is empty, here is working code for mode:
def mode(arr):
if arr==[]:
return None
else:
return max(set(arr), key=arr.count)
In case you are interested in either the smallest, largest or all modes:
def get_small_mode(numbers, out_mode):
counts = {k:numbers.count(k) for k in set(numbers)}
modes = sorted(dict(filter(lambda x: x[1] == max(counts.values()), counts.items())).keys())
if out_mode=='smallest':
return modes[0]
elif out_mode=='largest':
return modes[-1]
else:
return modes
I wrote up this handy function to find the mode.
def mode(nums):
corresponding={}
occurances=[]
for i in nums:
count = nums.count(i)
corresponding.update({i:count})
for i in corresponding:
freq=corresponding[i]
occurances.append(freq)
maxFreq=max(occurances)
keys=corresponding.keys()
values=corresponding.values()
index_v = values.index(maxFreq)
global mode
mode = keys[index_v]
return mode
Short, but somehow ugly:
def mode(arr) :
m = max([arr.count(a) for a in arr])
return [x for x in arr if arr.count(x) == m][0] if m>1 else None
Using a dictionary, slightly less ugly:
def mode(arr) :
f = {}
for a in arr : f[a] = f.get(a,0)+1
m = max(f.values())
t = [(x,f[x]) for x in f if f[x]==m]
return m > 1 t[0][0] else None
A little longer, but can have multiple modes and can get string with most counts or mix of datatypes.
def getmode(inplist):
'''with list of items as input, returns mode
'''
dictofcounts = {}
listofcounts = []
for i in inplist:
countofi = inplist.count(i) # count items for each item in list
listofcounts.append(countofi) # add counts to list
dictofcounts[i]=countofi # add counts and item in dict to get later
maxcount = max(listofcounts) # get max count of items
if maxcount ==1:
print "There is no mode for this dataset, values occur only once"
else:
modelist = [] # if more than one mode, add to list to print out
for key, item in dictofcounts.iteritems():
if item ==maxcount: # get item from original list with most counts
modelist.append(str(key))
print "The mode(s) are:",' and '.join(modelist)
return modelist
Why not just
def print_mode (thelist):
counts = {}
for item in thelist:
counts [item] = counts.get (item, 0) + 1
maxcount = 0
maxitem = None
for k, v in counts.items ():
if v > maxcount:
maxitem = k
maxcount = v
if maxcount == 1:
print "All values only appear once"
elif counts.values().count (maxcount) > 1:
print "List has multiple modes"
else:
print "Mode of list:", maxitem
This doesn't have a few error checks that it should have, but it will find the mode without importing any functions and will print a message if all values appear only once. It will also detect multiple items sharing the same maximum count, although it wasn't clear if you wanted that.
This function returns the mode or modes of a function no matter how many, as well as the frequency of the mode or modes in the dataset. If there is no mode (ie. all items occur only once), the function returns an error string. This is similar to A_nagpal's function above but is, in my humble opinion, more complete, and I think it's easier to understand for any Python novices (such as yours truly) reading this question to understand.
def l_mode(list_in):
count_dict = {}
for e in (list_in):
count = list_in.count(e)
if e not in count_dict.keys():
count_dict[e] = count
max_count = 0
for key in count_dict:
if count_dict[key] >= max_count:
max_count = count_dict[key]
corr_keys = []
for corr_key, count_value in count_dict.items():
if count_dict[corr_key] == max_count:
corr_keys.append(corr_key)
if max_count == 1 and len(count_dict) != 1:
return 'There is no mode for this data set. All values occur only once.'
else:
corr_keys = sorted(corr_keys)
return corr_keys, max_count
For a number to be a mode, it must occur more number of times than at least one other number in the list, and it must not be the only number in the list. So, I refactored @mathwizurd's answer (to use the difference method) as follows:
def mode(array):
'''
returns a set containing valid modes
returns a message if no valid mode exists
- when all numbers occur the same number of times
- when only one number occurs in the list
- when no number occurs in the list
'''
most = max(map(array.count, array)) if array else None
mset = set(filter(lambda x: array.count(x) == most, array))
return mset if set(array) - mset else "list does not have a mode!"
These tests pass successfully:
mode([]) == None
mode([1]) == None
mode([1, 1]) == None
mode([1, 1, 2, 2]) == None
Here is how you can find mean,median and mode of a list:
import numpy as np
from scipy import stats
#to take input
size = int(input())
numbers = list(map(int, input().split()))
print(np.mean(numbers))
print(np.median(numbers))
print(int(stats.mode(numbers)[0]))
def mode(inp_list):
sort_list = sorted(inp_list)
dict1 = {}
for i in sort_list:
count = sort_list.count(i)
if i not in dict1.keys():
dict1[i] = count
maximum = 0 #no. of occurences
max_key = -1 #element having the most occurences
for key in dict1:
if(dict1[key]>maximum):
maximum = dict1[key]
max_key = key
elif(dict1[key]==maximum):
if(key<max_key):
maximum = dict1[key]
max_key = key
return max_key
def mode(data):
lst =[]
hgh=0
for i in range(len(data)):
lst.append(data.count(data[i]))
m= max(lst)
ml = [x for x in data if data.count(x)==m ] #to find most frequent values
mode = []
for x in ml: #to remove duplicates of mode
if x not in mode:
mode.append(x)
return mode
print mode([1,2,2,2,2,7,7,5,5,5,5])
Here is a simple function that gets the first mode that occurs in a list. It makes a dictionary with the list elements as keys and number of occurrences and then reads the dict values to get the mode.
def findMode(readList):
numCount={}
highestNum=0
for i in readList:
if i in numCount.keys(): numCount[i] += 1
else: numCount[i] = 1
for i in numCount.keys():
if numCount[i] > highestNum:
highestNum=numCount[i]
mode=i
if highestNum != 1: print(mode)
elif highestNum == 1: print("All elements of list appear once.")
This will return all modes:
def mode(numbers)
largestCount = 0
modes = []
for x in numbers:
if x in modes:
continue
count = numbers.count(x)
if count > largestCount:
del modes[:]
modes.append(x)
largestCount = count
elif count == largestCount:
modes.append(x)
return modes
If you want a clear approach, useful for classroom and only using lists and dictionaries by comprehension, you can do:
def mode(my_list):
# Form a new list with the unique elements
unique_list = sorted(list(set(my_list)))
# Create a comprehensive dictionary with the uniques and their count
appearance = {a:my_list.count(a) for a in unique_list}
# Calculate max number of appearances
max_app = max(appearance.values())
# Return the elements of the dictionary that appear that # of times
return {k: v for k, v in appearance.items() if v == max_app}
#function to find mode
def mode(data):
modecnt=0
#for count of number appearing
for i in range(len(data)):
icount=data.count(data[i])
#for storing count of each number in list will be stored
if icount>modecnt:
#the loop activates if current count if greater than the previous count
mode=data[i]
#here the mode of number is stored
modecnt=icount
#count of the appearance of number is stored
return mode
print mode(data1)
来源：https://stackoverflow.com/questions/10797819/finding-the-mode-of-a-list