Pandas describe() function — Deep Dive

How important is the describe() function in Pandas library?

TL;DR: It is very important to know the nitty gritty of the describe function.

So, if you’re interested in Data Science topics and Python is your preferred programming language, you’ve probably came across the describe() method in Pandas’ library. When you obtain a new dataset, you usually run the describe command and then move on to cleaning it up, but do you truly dig into the findings produced by the describe function? If you don’t, this is the article for you. It will forever alter your approach to the describe function.

What is Pandas library?

Pandas is an open-source library developed by Wes McKinney, and instrumental to data analytics and data wrangling. Pandas is not included with any Python release and must be installed independently using the command:

pip install pandas

In addition to offering access to several data structures and methods for manipulating data, Pandas is well recognized for its Dataframe API. The Dataframe API may be compared to an interactive table that allows users to slice and dice different portions of interest or enable other types of operations like merge, join, broadcast, etc. In this article, we will just concentrate on the describe() function included in the Pandas library.

Describe()