Learning R and Python

[TravisCraven]

As someone who is still on newer side of data science I am not trying to add on to the R vs Python debate. Rather I wonder how many members here use both? Was it difficult to reconcile syntax. I have split resources for learning and tools I use such as Alteryx default to R but offer objects to throw in raw Python code.

My organization is in the crawling phase of data science so I am just trying to navigate if it is possible to learn both at once or if I need to prioritize.

Thanks

Travis

[jdlong]

So I do both and I'm not sure the best way to learn both, to be honest. I know what worked for me but that's a pretty small sample size. So take my input with a grain of salt.

I have found that building a workflow in one language and then building it in another is helpful. I would not try to simultaneously build a workflow in two languages at once. The problem is one of abstraction level. You need to focus on solving the problem at hand using the tools of the language. So really focusing at one at a time helps with that.

This is akin to learning a song in one spoken language then learning it in another. It's much more "sticky" than just learning all the words in one language then learning those same words in another.

[dlsweet]

I've been working in R for a few years not but I'm far from being an expert in it and have used Python a handful of times. I would completely agree with jdlong's advice of building up one at a time is definitely the way to go.

One thing that I have found extremely helpful for both languages is a DataCamp subscription. They have Data Scientist Career Tracks using both R and Python.

[radmuzom]

I am an intermediate R and a beginner Python programmer.

In my experience, the amount of effort you need to spend before you are able to analyze & explore data and create some basic statistical models is lower for R. I suspect this is because R was primarily developed by statisticians who wanted to use the language versus Python which was built to be a general purpose programming language but became popular in data science.

Since you are relatively new to data science, I would advise you to learn R first to get the positive reinforcement which comes with building things quickly and allows you to stay motivated.