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A book to learn R and Python in parallel for Data Science

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Re: A book to learn R and Python in parallel for Data Science

#41

Post by eoinmurray92 »

mh12345 wrote: post #32

R has a nice web development framework called Shiny. While it is not comparable to say Django or Flask, Shiny does make it incredibly easy to share data analysis. If one wants to share statistical analysis or create a data oriented dashboard, then there is definitely a reason to consider R and Shiny. Note that Python has Dash, which is comparable to Shiny, but it is less mature as far as I know. While previously Shin…

Dash by plotly is also amazing its like shiny but for python! - we were able to whip together an app that would let you drag and drop xyyy data and get a scatter plot instantly - you can try it here (first load takes 1-2s):

https://dash-app-dx9g2r0la6-8000.cloud.kyso.io

It was also really easy to make it, maybe 250 lines of python in total

(guide to making this app is here: https://kyso.io/KyleOS/creating-an-interactive-application-u...)

Re: A book to learn R and Python in parallel for Data Science

#42

Post by Annatar »

mh12345 wrote: post #32

R has a nice web development framework called Shiny. While it is not comparable to say Django or Flask, Shiny does make it incredibly easy to share data analysis. If one wants to share statistical analysis or create a data oriented dashboard, then there is definitely a reason to consider R and Shiny. Note that Python has Dash, which is comparable to Shiny, but it is less mature as far as I know. While previously Shin…

I maintain R and Shiny where I work. With Shiny, one can now build any web application imaginable, even a completely generic one.

R has such a huge library of software now, that it has gone far and wide outside of statistics and analytics - any kind of application can be built in R now.

In fact I see no point in using Python for mathematics or number crunching any more as R has it all and performance critical parts can be rewritten in modern Fortran for very high speed and made available inside of R transparently.

Re: A book to learn R and Python in parallel for Data Science

#43

Post by conjectures »

cwyers wrote: post #3

Nobody would write R code the way this book is teaching. For that matter, nobody looking to do linear regression for data science in Python is doing their own matrix math, either.

Linear regression should be regarded as the statistical equivalent of stripping down a rifle, reassembling it and checking its function. If you develop any statistical software, you're going to end up doing it at some point.

Re: A book to learn R and Python in parallel for Data Science

#44

Post by Annatar »

arendtio wrote: post #27
billfruit wrote: post #13

I sometimes wonder is there any reason to learn R at all, since python eco system has absorbed most of its advanced statistical functionality, coupled with the factor that python environment is much more general, with capabilities to fetch, decode/encoded data,work with binary data databases, web frameworks for presenting etc.

I don't know if it is still a thing, but if you are working with SAP HANA (in-memory database) there is a good chance you would like to learn R as they integrated it into their database.

Vertica did as well.

Re: A book to learn R and Python in parallel for Data Science

#45

Post by mikorym »

mh12345 wrote: post #38
mikorym wrote: post #26

Earlier quoted context omitted.

I use both python and R almost every day. Although I like R and often use R to quickly order tabulated data, there are a few things to take into account that in recent times are building a strong case for me not to use R habitually. Development in R is frustrating. If you don't need to do dev, then on this point you are home free. Testing things that you deploy in R is not simple. Scripting in R can be frustrating. I…

Interesting, why do you advise people to stay away from Shiny?

It tries to do html, but it is limited. So I'd rather use Javascript to manipulate the frontend directly.

It tries to do functional programming, but the documentation is not satisfying. The responses and behaviour is perplexing.

I spent around 5—10 hours trying to get a Shiny GUI to work and eventually got to the conclusion that 1) if you want a big project do all the frontend stuff in something else, like JS and 2) if you want a small project try something established (I am not advocating, it's just an example) like Power BI.

Re: A book to learn R and Python in parallel for Data Science

#46

Post by Annatar »

kuzehanka wrote: post #22
billfruit wrote: post #13

I sometimes wonder is there any reason to learn R at all, since python eco system has absorbed most of its advanced statistical functionality, coupled with the factor that python environment is much more general, with capabilities to fetch, decode/encoded data,work with binary data databases, web frameworks for presenting etc.

I don't think there's any reason to learn R for anyone who is already proficient at programming. Despite being proficient with R, the only times I used it in the last two years were for ggplot. And even for data vis, I'm increasingly using Python and JS. There's a bunch of comments below which can be summed up with 'use R because doesn't have a direct python equivalent' but they're all missing the point that the Pyth…

I cannot understand why I would use Python over R. R is designed from the ground up for massive amounts of data processing at speed and with ease. Even if Python continues accreting computational functionality, it will never be as fast or as efficient as R. Improving Python for something R is designed to do seems to me to be a huge waste of time: familiarity should not be the driving force behind replicating R's functionality. That's just so wrong.

Re: A book to learn R and Python in parallel for Data Science

#47

Post by Annatar »

kuzehanka wrote: post #33
anthony_doan wrote: post #25

Earlier quoted context omitted.

> There's a bunch of comments below which can be summed up with 'use R because doesn't have a direct python equivalent' but they're all missing the point that the Python data science ecosystem is evolving at a much faster pace than R and will completely supersede it in a few years. The point is R is a very good language for statistic because of the packages not data science. Data science can do their own thing it's o…

Everything you said sums up with 'R is a very good language for statistic because of the packages' which is pretty much in agreement with the GP comment. R has nothing going for it except a rapidly dwindling number of packages that don't yet have a direct python equivalent. It doesn't make sense to invest time into R if one already knows python unless one specifically focusing on academia pure stats type stuff. Even…

"It doesn't make sense to invest time into R if one already knows python unless one specifically focusing on academia pure stats type stuff."

Ha! I knew it! So it is familiarity with Python then!

R does have something else going for it: phenomenal documentation and consistency. Replicating R's thousands of available libraries will be a gargantuan effort. It is cheaper and more efficient to master R.

Re: A book to learn R and Python in parallel for Data Science

#48

Post by knbknb »

eoinmurray92 wrote: post #41
mh12345 wrote: post #32

R has a nice web development framework called Shiny. While it is not comparable to say Django or Flask, Shiny does make it incredibly easy to share data analysis. If one wants to share statistical analysis or create a data oriented dashboard, then there is definitely a reason to consider R and Shiny. Note that Python has Dash, which is comparable to Shiny, but it is less mature as far as I know. While previously Shin…

Dash by plotly is also amazing its like shiny but for python! - we were able to whip together an app that would let you drag and drop xyyy data and get a scatter plot instantly - you can try it here (first load takes 1-2s): https://dash-app-dx9g2r0la6-8000.cloud.kyso.io It was also really easy to make it, maybe 250 lines of python in total (guide to making this app is here: https://kyso.io/KyleOS/creating-an-interact…

I thought the Python equivalent to Shiny is Bokeh, see https://bokeh.pydata.org/en/latest/docs/gallery.html#gallery) ?

Re: A book to learn R and Python in parallel for Data Science

#49

Post by roenxi »

minimaxir wrote: post #16
billfruit wrote: post #13

I sometimes wonder is there any reason to learn R at all, since python eco system has absorbed most of its advanced statistical functionality, coupled with the factor that python environment is much more general, with capabilities to fetch, decode/encoded data,work with binary data databases, web frameworks for presenting etc.

I use both Python and R. tidyverse/ggplot2 alone are enough reason to use R, and are substantially faster for tasks that utilize those packages than the equivalent in Python (in my opinion). Although I haven't had as much reason to use base R. For more ML-related tasks I do go back to Python.

Here here. Tidyverse also provides a centralised 'this is how you do X' nexus really helps discover-ability. World class stuff, on tap.

For example, I know the recommended pipe in R is magrittr's %>%. I have no idea what the respectable pipe library in Python is, or even if there is one.

I wouldn't even know where to start finding all the tidyverse equivalents in Python. It isn't as organised and obvious as the R statistics community.

On the other hand Base R is the worst. Disgusting language.

Re: A book to learn R and Python in parallel for Data Science

#50

Post by kuzehanka »

Annatar wrote: post #46
kuzehanka wrote: post #22

Earlier quoted context omitted.

I don't think there's any reason to learn R for anyone who is already proficient at programming. Despite being proficient with R, the only times I used it in the last two years were for ggplot. And even for data vis, I'm increasingly using Python and JS. There's a bunch of comments below which can be summed up with 'use R because doesn't have a direct python equivalent' but they're all missing the point that the Pyth…

I cannot understand why I would use Python over R. R is designed from the ground up for massive amounts of data processing at speed and with ease. Even if Python continues accreting computational functionality, it will never be as fast or as efficient as R. Improving Python for something R is designed to do seems to me to be a huge waste of time: familiarity should not be the driving force behind replicating R's func…

> R is designed from the ground up for massive amounts of data processing at speed

What? The R ecosystem doesn't provide meaningful out of core capabilities, nevermind the ability to handle anything approaching 'massive amounts of data'.

-- Would sure love to know why an agenda-less factual comment is getting downvoted.

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