In the previous article, I wrote about some introductory stuff and basic Pandas capabilities. In this part, the main focus will be on DateTime values. I am also going to introduce you to some grouping and merging possibilities in Pandas. For this purpose here is another dataset downloaded from UCI Repository, which contains date and time columns. This time my data comes from Excel file, so the way I read it is a slightly different than in the previous post. After importing pandas library (see the previous blog post) I’m going to use read_excel() function and display data sample with head() …
Data Exploration with Pandas (part 1)
If you ever decide to become someone who is into big data, surely you can do it without having a clue about pandas. But that’s not the brightest solution, because why would you leave aside something that’s gonna make you a lot better. Pandas as well know library for manipulating datasets that contains numerical and table structures, which makes it pretty good-to-know library for data engineers and data scientists. In part 1 we’re gonna go through some of the basic stuff to introduce you to the Pandas capabilities.. For the purpose of this article, as an example dataset I’ve used …