If you have been using the pandas library in python you may have noticed that a lot of data comes in textual form instead of pure numbers as some people may imagine.

This means there is a need to clean and preprocess string so it can be analyzed, consumed by algorithms, or shown to the public. Luckily pandas library has its own part that deals with string processing.

In this article, we will walk you through this part of the pandas’ library and show you the most useful pandas string processing functions. You will learn how to use:

• upper()
• lower()
• isupper()
• slower()
• isnumeric()
• replace()
• split()
• contains()
• find()
• findall()

Ready?

Let’s get started.

#machine-learning #data-science #programming #pandas #python