# Python | Average String length in list

Sometimes, while working with data, we can have a problem in which we need to gather information of average length of String data in list. This kind of information might be useful in Data Science domain. Let’s discuss certain ways in which this task can be performed.

Method #1 : Using list comprehension + sum() + len() The combination of above functions can be used to perform this task. In this we compute lengths of all Strings using list comprehension and then divide the sum by length of list using len() and sum().

## Python3

 `# Python3 code to demonstrate working of``# Average String lengths in list``# using list comprehension + sum() + len()` `# initialize list``test_list ``=` `[``'gfg'``, ``'is'``, ``'best'``, ``'for'``, ``'geeks'``]` `# printing original list``print``(``"The original list : "` `+` `str``(test_list))` `# Average String lengths in list``# using list comprehension + sum() + len()``temp ``=` `[``len``(ele) ``for` `ele ``in` `test_list]``res ``=` `0` `if` `len``(temp) ``=``=` `0` `else` `(``float``(``sum``(temp)) ``/` `len``(temp))` `# printing result``print``(``"The Average length of String in list is : "` `+` `str``(res))`

Output :
```The original list : ['gfg', 'is', 'best', 'for', 'geeks']
The Average length of String in list is : 3.4```

Time Complexity: O(n), where n is length of list.
Auxiliary Space: O(1)

Method #2 : Using map() + sum() + len() The combination of above functions can also be used to perform this task. In this, we compute lengths using map(). Rest all the logic is similar to above method.

## Python3

 `# Python3 code to demonstrate working of``# Average String lengths in list``# using map() + sum() + len()` `# initialize list``test_list ``=` `[``'gfg'``, ``'is'``, ``'best'``, ``'for'``, ``'geeks'``]` `# printing original list``print``(``"The original list : "` `+` `str``(test_list))` `# Average String lengths in list``# using map() + sum() + len()``res ``=` `sum``(``map``(``len``, test_list))``/``float``(``len``(test_list))` `# printing result``print``(``"The Average length of String in list is : "` `+` `str``(res))`

Output :
```The original list : ['gfg', 'is', 'best', 'for', 'geeks']
The Average length of String in list is : 3.4```

Time Complexity: O(n), where n is the length of the input list. This is because weâ€™re using map() + sum() + len() which has a time complexity of O(n) in the worst case.
Auxiliary Space: O(1), as weâ€™re using constant additional space.

Method #3 : Using len() and mean() method of statistics module

## Python3

 `# Python3 code to demonstrate working of``# Average String lengths in list``import` `statistics``# initialize list``test_list ``=` `[``'gfg'``, ``'is'``, ``'best'``, ``'for'``, ``'geeks'``]` `# printing original list``print``(``"The original list : "` `+` `str``(test_list))` `# Average String lengths in list``x``=``[]``for` `i ``in` `test_list:``    ``x.append(``len``(i))``res``=``statistics.mean(x)``# printing result``print``(``"The Average length of String in list is : "` `+` `str``(res))`

Output
```The original list : ['gfg', 'is', 'best', 'for', 'geeks']
The Average length of String in list is : 3.4```

Time complexity: O(n*n), where n is the length of the numbers list. The len() and mean() method of statistics module have a time complexity of O(n)
Auxiliary Space: O(1), constant space is required

Method #4 : Using reduce()

## Python3

 `from` `functools ``import` `reduce` `# Python3 code to demonstrate working of``# Average String lengths in list``# using reduce()`` ` `# initialize list``test_list ``=` `[``'gfg'``, ``'is'``, ``'best'``, ``'for'``, ``'geeks'``]`` ` `# printing original list``print``(``"The original list : "` `+` `str``(test_list))`` ` `# Average String lengths in list``# using reduce()``res ``=` `reduce``(``lambda` `x, y: x ``+` `y, ``map``(``len``, test_list))``/``len``(test_list)`` ` `# printing result``print``(``"The Average length of String in list is : "` `+` `str``(res))` `#this code is contributed by edula vinay kumar reddy`

Output
```The original list : ['gfg', 'is', 'best', 'for', 'geeks']
The Average length of String in list is : 3.4```

In this method, we first use map() to calculate the length of each string in the list. Then, we use reduce() function to get the sum of all lengths. Finally, we divide the sum by the length of the list to get the average length.

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

Method#5:Using list comprehension

## Python3

 `# initialize list``test_list ``=` `[``'gfg'``, ``'is'``, ``'best'``, ``'for'``, ``'geeks'``]``# calculate total length of all strings in the list``total_length ``=` `sum``([``len``(string) ``for` `string ``in` `test_list])` `# calculate average``average ``=` `total_length``/``len``(test_list)` `# print result``print``(``"The Average length of String in list is : "` `+` `str``(average))`

Output
`The Average length of String in list is : 3.4`

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

Method#6: Using For loop.

## Python3

 `# initialize list``test_list ``=` `[``'gfg'``, ``'is'``, ``'best'``, ``'for'``, ``'geeks'``]``total_length ``=` `0``# calculate total length of all strings in the list using for loop``for` `string ``in` `test_list:``    ``total_length ``+``=` `len``(string)``    ` `# calculate average``average ``=` `total_length``/``len``(test_list)` `# print result``print``(``"The Average length of String in list is : "` `+` `str``(average))``#this code contributed by tvsk`

Output
`The Average length of String in list is : 3.4`

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

Method#7: Using numpy:

1. Import the numpy library as np.
2. Define a function named “avg_str_len” that takes a list of strings as input.
3. Within the function, use a list comprehension to create a list of the lengths of the strings in the input list.
4. Use the np.mean() function to compute the average of the list of string lengths.
5. Return the result of step 4 from the function.
6. Define a list of strings to test the function.
7. Call the avg_str_len function with the test list as an argument and store the result in a variable named “result”.
8. Print the original list of strings and the computed average length of the strings.

## Python3

 `import` `numpy as np``def` `avg_str_len(lst):``    ``return` `np.mean([``len``(s) ``for` `s ``in` `lst])``test_list ``=` `[``'gfg'``, ``'is'``, ``'best'``, ``'for'``, ``'geeks'``]``result ``=` `avg_str_len(test_list)``print``(``"The original list:"``, test_list)``print``(``"The average length of strings in the list:"``, result)``#This code is contributed by Jyothi pinjala.`

Output:

The original list: [‘gfg’, ‘is’, ‘best’, ‘for’, ‘geeks’]
The average length of strings in the list: 3.4

The time complexity :O(n), where n is the length of the input list of strings. This is because the code iterates through each string in the list exactly once to calculate its length, and then computes the average of these lengths using the numpy mean() function, which has a time complexity of O(n).

The space complexity :O(n), where n is the length of the input list of strings. This is because the list comprehension creates a new list of the same length as the input list to store the lengths of the strings, and this list is stored in memory until the numpy mean() function is called. The numpy mean() function creates a new scalar object to store the average length of the strings, which is returned by the function. Thus, the overall space complexity is also O(n).

Method#8:Using enumerate()

Algorithm:

1. Initialize the input list test_list.
2. Calculate the total length of all strings in the list using list comprehension and sum() function, and store the result in total_length.
3. Calculate the average by dividing total_length by the length of test_list.
4. Print the result using the print() function.

## Python3

 `# initialize list``test_list ``=` `[``'gfg'``, ``'is'``, ``'best'``, ``'for'``, ``'geeks'``]``total_length ``=` `0` `# calculate total length of all strings in the list``for` `i, string ``in` `enumerate``(test_list):``    ``total_length ``+``=` `len``(string)` `# calculate average``average ``=` `total_length ``/` `len``(test_list)` `# print result``print``(``"The Average length of String in list is : "` `+` `str``(average))``#This code is contributed by Vinay Pinjala.`

Output
`The Average length of String in list is : 3.4`

Time Complexity:
The time complexity of this algorithm is O(n), where n is the number of strings in the input list. This is because the list comprehension and sum() functions iterate over each string in the list once, giving us a linear time complexity.

Auxiliary Space:
The space complexity of this algorithm is O(1), as we are only storing a constant number of variables (test_list, total_length, and average) in memory regardless of the size of the input list.

Method#8: Using pandas package

Note: first install the pandas package by using: pip install pandas

• Convert the list of strings to a pandas Series.
• Apply the str.len() method to get the length of each string.
• Calculate the average using the mean() method.

## Python3

 `import` `pandas as pd` `# initialize list``test_list ``=` `[``'gfg'``, ``'is'``, ``'best'``, ``'for'``, ``'geeks'``]` `# calculating the average using pandas package``aver ``=` `pd.Series(test_list).``apply``(``len``).mean()` `# print result``print``(``"The Average length of String in list is : "` `+` `str``(aver))`

Output

`The Average length of String in list is : 3.4`

Time Complexity: O(N) where N is the number of strings in the list.
Auxiliary Space: O(N) where N is the number of strings in the list.

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