# Python | Summation of dictionary list values

Last Updated : 13 Apr, 2023

Sometimes, while working with Python dictionaries, we can have its values as lists. In this can, we can have a problem in that we just require the count of elements in those lists as a whole. This can be a problem in Data Science in which we need to get total records in observations. Let’s discuss certain ways in which this task can be performed.

Method #1: Using sum() + list comprehension
This task can be performed using sum function which can be used to get the summation and internal list comprehension can provide a mechanism to iterate this logic to all the keys of the dictionary.

## Python3

 `# Python3 code to demonstrate working of` `# Summation of dictionary list values` `# using sum() + list comprehension`   `# initialize dictionary` `test_dict ``=` `{``'gfg'``: [``5``, ``6``, ``7``], ``'is'``: [``10``, ``11``], ``'best'``: [``19``, ``31``, ``22``]}`   `# printing original dictionary` `print``(``"The original dictionary is : "` `+` `str``(test_dict))`   `# Summation of dictionary list values` `# using sum() + list comprehension` `res ``=` `sum``(``len``(sub) ``for` `sub ``in` `test_dict.values())`   `# printing result` `print``(``"Summation of dictionary list values are : "` `+` `str``(res))`

Output

```The original dictionary is : {'gfg': [5, 6, 7], 'is': [10, 11], 'best': [19, 31, 22]}
Summation of dictionary list values are : 8```

Time complexity: O(N), where N is the total number of elements in all the lists contained within the dictionary.
Auxiliary space: O(1), as it only uses a constant amount of auxiliary space to store the input dictionary and the result variable.

Method #2: Using sum() + map()
This task can also be performed using map function in place of list comprehension to extend the logic of finding the length, rest all the functionality remaining same as the above method.

## Python3

 `# Python3 code to demonstrate working of ` `# Summation of dictionary list values ` `# using sum() + map() `   `# initialize dictionary ` `test_dict ``=` `{``'gfg'` `: [``5``, ``6``, ``7``], ``'is'` `: [``10``, ``11``], ``'best'` `: [``19``, ``31``, ``22``]} `   `# printing original dictionary ` `print``(``"The original dictionary is : "` `+` `str``(test_dict)) `   `# Summation of dictionary list values ` `# using sum() + map() ` `res ``=` `sum``(``map``(``len``, test_dict.values())) `   `# printing result ` `print``(``"Summation of dictionary list values are : "` `+` `str``(res)) `

Output

```The original dictionary is : {'gfg': [5, 6, 7], 'is': [10, 11], 'best': [19, 31, 22]}
Summation of dictionary list values are : 8```

Method #3: Using values(), extend() and len() methods

## Python3

 `# Python3 code to demonstrate working of` `# Summation of dictionary list values`   `# initialize dictionary` `test_dict ``=` `{``'gfg'` `: [``5``, ``6``, ``7``], ``'is'` `: [``10``, ``11``], ``'best'` `: [``19``, ``31``, ``22``]}`   `# printing original dictionary` `print``(``"The original dictionary is : "` `+` `str``(test_dict))`   `# Summation of dictionary list values` `x``=``list``(test_dict.values())` `a``=``[]` `for` `i ``in` `x:` `    ``a.extend(i)` `res``=``len``(a)` `    `  `# printing result` `print``(``"Summation of dictionary list values are : "` `+` `str``(res))`

Output

```The original dictionary is : {'gfg': [5, 6, 7], 'is': [10, 11], 'best': [19, 31, 22]}
Summation of dictionary list values are : 8```

Method #4: Using reduce()

Using reduce() and len(): This approach uses the reduce() function from the functools module to iteratively combine the values of the dictionary into a single iterable, and then uses the len() function to get the count of elements in the iterable. Time complexity is O(n) where n is the total number of elements in the lists, and auxiliary space is O(n) where n is the total number of elements in the lists.

## Python3

 `from` `functools ``import` `reduce`   `# initialize dictionary` `test_dict ``=` `{``'gfg'``: [``5``, ``6``, ``7``], ``'is'``: [``10``, ``11``], ``'best'``: [``19``, ``31``, ``22``]}`   `# printing original dictionary` `print``(``"The original dictionary is : "` `+` `str``(test_dict))`   `# Summation of dictionary list values` `# Using reduce() and len()` `# reduce() method applies a given function to all elements in an iterable and returns a single value` `# len() method returns the length of the passed iterable` `res ``=` `len``(``reduce``(``lambda` `x, y: x ``+` `y, test_dict.values()))`   `# printing result` `print``(``"Summation of dictionary list values are : "` `+` `str``(res))` `# This code is contributed by Edula Vinay Kumar Reddy`

Output

```The original dictionary is : {'gfg': [5, 6, 7], 'is': [10, 11], 'best': [19, 31, 22]}
Summation of dictionary list values are : 8```

The time complexity of this code is O(N*M), where N is the number of keys in the dictionary and M is the length of the longest list in the dictionary.

The space complexity of this code is O(M), where M is the length of the longest list in the dictionary.

Method#5 Using Numpy library

## Python3

 `import` `numpy as np`   `# initialize dictionary` `test_dict ``=` `{``'gfg'``: [``5``, ``6``, ``7``], ``'is'``: [``10``, ``11``], ``'best'``: [``19``, ``31``, ``22``]}` `# printing original dictionary` `print``(``"The original dictionary is : "` `+` `str``(test_dict))`   `# convert dictionary values to numpy array` `values_array ``=` `np.array(``list``(test_dict.values()))`   `# flatten array to 1D` `values_array ``=` `values_array.flatten()`   `# sum the values in the array` `result ``=` `np.``sum``(values_array)`   `print``(``len``(result))` `#This code is contributed by Vinay Pinjala.`

Output:

```The original dictionary is : {'gfg': [5, 6, 7], 'is': [10, 11], 'best': [19, 31, 22]}
Summation of dictionary list values are : 8```

Time complexity: O(n)
Auxiliary Space: O(n)

Method#6: Using a for loop:

• The function is defined with a single parameter called test_dict, which represents the dictionary that will be input to the function.
• A variable called result is initialized to 0. This variable will be used to keep track of the sum of the lengths of all the sub-lists in the dictionary.
• The function uses a for loop to iterate through all the values of the input dictionary. The values() method of a dictionary returns a view object that contains the values of the dictionary.
• For each sub-list in the dictionary, the length of the sub-list is calculated using the len() function, and the result is added to the result variable.
• Once all the sub-lists have been processed, the final value of result is returned from the function.
• Finally, the function is tested with a sample dictionary called test_dict, and the result is printed to the console using the print() function.

## Python3

 `def` `sum_dict_values(test_dict):` `    ``# Initialize a variable to store the result` `    ``result ``=` `0` `    ``# Iterate through all the values of the dictionary` `    ``for` `sub_list ``in` `test_dict.values():` `        ``# Add the length of each sub-list to the result` `        ``result ``+``=` `len``(sub_list)` `    ``# Return the result` `    ``return` `result` `# Test the function with a sample dictionary` `test_dict ``=` `{``'gfg'``: [``5``, ``6``, ``7``], ``'is'``: [``10``, ``11``], ``'best'``: [``19``, ``31``, ``22``]}` `# printing original dictionary` `print``(``"The original dictionary is : "` `+` `str``(test_dict))` `result ``=` `sum_dict_values(test_dict)` `print``(``"Summation of dictionary list values are : "` `+` `str``(result))` `#This is code is contributed by Jyothi pinjala`

Output

```The original dictionary is : {'gfg': [5, 6, 7], 'is': [10, 11], 'best': [19, 31, 22]}
Summation of dictionary list values are : 8```

Time complexity: O(n)
Auxiliary Space: O(1)