Python – Cumulative Mean of Dictionary keys
Given the dictionary list, our task is to write a Python Program to extract the mean of all keys.
Input : test_list = [{‘gfg’ : 34, ‘is’ : 8, ‘best’ : 10},
{‘gfg’ : 1, ‘for’ : 10, ‘geeks’ : 9, ‘and’ : 5, ‘best’ : 12},
{‘geeks’ : 8, ‘find’ : 3, ‘gfg’ : 3, ‘best’ : 8}]
Output : {‘gfg’: 12.666666666666666, ‘is’: 8, ‘best’: 10, ‘for’: 10, ‘geeks’: 8.5, ‘and’: 5, ‘find’: 3}
Explanation : best has 3 values, 10, 8 and 12, their mean computed to 10, hence in result.
Input : test_list = [{‘gfg’ : 34, ‘is’ : 8, ‘best’ : 10},
{‘gfg’ : 1, ‘for’ : 10, ‘and’ : 5, ‘best’ : 12},
{ ‘find’ : 3, ‘gfg’ : 3, ‘best’ : 8}]
Output : {‘gfg’: 12.666666666666666, ‘is’: 8, ‘best’: 10, ‘for’: 10, ‘and’: 5, ‘find’: 3}
Explanation : best has 3 values, 10, 8 and 12, their mean computed to 10, hence in result.
Method #1 : Using mean() + loop
In this, for extracting each list loop is used and all the values are summed and memorized using a dictionary. Mean is extracted later by div
g by the occurrence of each key.Python3
# Python3 code to demonstrate working of# Cumulative Keys Mean in Dictionary List# Using loop + mean()from statistics import mean # initializing listtest_list = [{'gfg' : 34, 'is' : 8, 'best' : 10}, {'gfg' : 1, 'for' : 10, 'geeks' : 9, 'and' : 5, 'best' : 12}, {'geeks' : 8, 'find' : 3, 'gfg' : 3, 'best' : 8}] # printing original listprint("The original list is : " + str(test_list)) res = dict()for sub in test_list: for key, val in sub.items(): if key in res: # combining each key to all values in # all dictionaries res[key].append(val) else: res[key] = [val] for key, num_l in res.items(): res[key] = mean(num_l) # printing resultprint("The Extracted average : " + str(res)) |
Output:
The original list is : [{‘gfg’: 34, ‘is’: 8, ‘best’: 10}, {‘gfg’: 1, ‘for’: 10, ‘geeks’: 9, ‘and’: 5, ‘best’: 12}, {‘geeks’: 8, ‘find’: 3, ‘gfg’: 3, ‘best’: 8}]
The Extracted average : {‘gfg’: 12.666666666666666, ‘is’: 8, ‘best’: 10, ‘for’: 10, ‘geeks’: 8.5, ‘and’: 5, ‘find’: 3}
Method #2 : Using defaultdict() + mean()
In this, the task of memorizing is done using defaultdict(). This reduces one conditional check and makes the code more concise.
Python3
# Python3 code to demonstrate working of# Cumulative Keys Mean in Dictionary List# Using defaultdict() + mean()from statistics import meanfrom collections import defaultdict # initializing listtest_list = [{'gfg' : 34, 'is' : 8, 'best' : 10}, {'gfg' : 1, 'for' : 10, 'geeks' : 9, 'and' : 5, 'best' : 12}, {'geeks' : 8, 'find' : 3, 'gfg' : 3, 'best' : 8}] # printing original listprint("The original list is : " + str(test_list)) # defaultdict reduces step to memoize.res = defaultdict(list)for sub in test_list: for key, val in sub.items(): res[key].append(val) res = dict(res)for key, num_l in res.items(): # computing mean res[key] = mean(num_l) # printing resultprint("The Extracted average : " + str(res)) |
Output:
The original list is : [{‘gfg’: 34, ‘is’: 8, ‘best’: 10}, {‘gfg’: 1, ‘for’: 10, ‘geeks’: 9, ‘and’: 5, ‘best’: 12}, {‘geeks’: 8, ‘find’: 3, ‘gfg’: 3, ‘best’: 8}]
The Extracted average : {‘gfg’: 12.666666666666666, ‘is’: 8, ‘best’: 10, ‘for’: 10, ‘geeks’: 8.5, ‘and’: 5, ‘find’: 3}
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