Counting characters of words in a series is useful in many data analysis projects, by knowing the individual count and frequency, we can gain a better understanding of the patterns and trends of a text. In this thread, different simple and efficient methods will be discussed for counting characters of words in a series. If you want to learn how to capitalize each word in a series, you can go through the thread of Capitalize first character of elements in a series.
1. Using "len()" function with list comprehension:
- The function
len()
is a built-in Python function that returns the length of an object. The object can be a string, list, tuple, dictionary, set, or any other iterable object. - List comprehension is used to apply
len()
to all values in the series and get a list which is then converted into a series again usingpd.Series()
before the final print.
2. Using "str.count()" method:
- In Python,
str.count()
is a string method that returns the number of occurrences of a substring in the given string. - The pattern provided to the function is
"\w"
which is a regular expression pattern that matches alphanumeric characters and in this way, we consider both letters and digits in the count.
3. Using "s.str.len()" method:
- The
str.len()
is a string method that returns the length of a string i.e., the number of characters in it and it can be directly applied to a series object.
4. Using lambda function with "apply()":
- In this technique, a simple lambda function is used which returns the length of an item passed to it.
- This lambda function is applied on the series object using the
apply()
method which is used to apply any function to a series or dataframe object.
Note: You can also create a different lambda function that performs the same task in another way.
5. Using "len()" function with "map()":
- The function
len()
is a built-in Python function that returns the length of an object. The object can be a string, list, tuple, dictionary, set, or any other iterable object. - In Pandas,
map()
is a method that can be applied to a Pandas series or dataframe column to transform each element of the column using a Python function. In this technique, Python’slen()
function is applied to each element usingmap()
.