PYTHON PROGRAMMING
The title of this text stresses the strengths and limitations of chaining Pandas operations — but to be honest, I’ll write about fun.
Why fun? Is it in any respect necessary when we have now data to research?
I don’t know what works for you, but for me fun in work is significant. During my 20+ years of experience in data science, I’ve found that the more enjoyment I derive from coding, the more satisfied I’m from completing the duty. And I do mean the technique of pursuing the duty, not only just completing it. In fact, achieving results matters, probably probably the most. But trust me, for those who dislike the tools you’re using, all you’ll want is to complete the job as quickly as possible. This may result in mistakes, as you may work rapidly and overlook necessary details in the information. And that’s something you wish to avoid.
I transitioned to Python from R, and analyzing data with R is loads of fun — due to the dplyr syntax. I’ve at all times enjoyed it, and I still do. Nevertheless, once I switched to Python, I discovered myself preferring it over R. I’ve never really enjoyed programming in R (note the excellence between analyzing data and programming), while…
