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0 pointsJakeColtman9y ago0 comments

For straight up data analysis R over python every time but the flip is python is a better gateway to more mainstream programming (IMO).

At the end of the day motivation is the most important thing though. It seems likely that R will better fit your current interests and hence make you more likely to continue the journey so I'd go that way

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7 comments · 1 top-level

boniface3169y ago· 6 in thread

I really appreciate your advice Jake. I will stick to R. Do you have experience with R?

JakeColtmanOP9y ago

We used it at uni a lot but these days I tend to use it as a last mile language. Get the data, format it etc in python/f# then bring in the big R guns.

Things like BMA or survival analysis barely exist in python.

I have a great R stats book that I'll post when I get home (can't remember the name off the top of my head)

Edit: to be clear I wouldn't recommend that pipeline! Most of my professional work has been in the above so I'm just more comfortable with it

boniface3169y ago

omg! I would really appreciate that! I have been looking for data science books.

If you don't mind, could you give me your opinion on this course?

https://academy.microsoft.com/en-US/professional-degree/data...

1 more reply

minimaxir9y ago

You should not stick to any one language. Both R and Python have their perks and definiciencies, and using both is powerful.

boniface3169y ago

Hey, I love to work with different languages and expand my knowledge. I wanted to know where should I start and focus initially. I will be interested in learning Python so I can do cool web applications.

PS: I love your blog! I have saved and bookmarked it!

curiousgal9y ago

Listen to this guy, he's done wonders with both R and Python. Great blog dude!

3 more replies

JakeColtmanOP9y ago

FWIW I wasn't suggesting sticking to one language exclusively, some of the biggest jumps I've made have been caused by exposure to different paradigms. But for beginners I think it can be helpful to keep focus in one place. There's a lot of overhead involved in a language (tooling, IDEs, best practices, quirks etc.) that can get in the way of seeing the important stuff.

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