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An opinionated view of the Tidyverse “dialect” of the R language

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Re: An opinionated view of the Tidyverse “dialect” of the R language

#111

Post by roenxi »

kgwgk wrote: post #87
minimaxir wrote: post #86

Earlier quoted context omitted.

That's an interesting caveat with pipes/magrittr (I didn't know of it), although it's out of scope of this debate since this discussion is just about how tidyverse uses pipes. In my experience if there's a package that's required in a script/R Notebook outside of tidyverse, I just import the entire library at the start of the file Python-style (to make the dependency obvious), which would avoid this issue.

If you claim that something like the_data x) the_data is a pain to read compared to the_data % subset(variable_a > x) %>% transform(variable_c = variable_a/variable_b) %>% head(100) I thinks it’s fair to mention how by making things more complicated by using pipes you expose yourself to other issues. (In my opinion the first variant is not less readable, and it has the advantage of allowing any of the operations to b…

They are roughly equivalent to read; but the reason for that is that the first code sample is clearly someone unwinding something that they are conceptualising as a piped statement. If you aren't conceptualising the code as an unwound pipe, you'd have to actually inspect the code and think about what each function argument means rather than being confident it is a set of chained transforms as you can be by glancing and seeing a %>%.

I'm a bit suspicious about that coincidence - after I met the pipe operator, a lot of my code looks like that. Before I met the pipe operator, not very much of my code looked like that.

As long as people are thinking in pipes then they can choose if they value making commenting code cheap vs making reading/typing code cheap. But it is quite important that beginners are introduced to pipes as a concept as they learn R. The semantics are critical, using the syntax is optional.

Re: An opinionated view of the Tidyverse “dialect” of the R language

#112

Post by [deleted] »

RosanaAnaDana wrote: post #107
hadley wrote: post #101

Earlier quoted context omitted.

You are of course free to dispute what is in the tidyverse, but I pretty strongly believe that it is part of the tidyverse

Seeing as the tidyverse is pretty much your invention, its well within your purvue to define what is in and what is out. I do think, respectfully, that both the op and the general sentiment article have the right of it. Data.table and data.table-esque notation represent such an improvement of tibble/dplyr, that within my company, we're making a concerted effort to purge all tidyverse packages from general use (less g…

[deleted]

Re: An opinionated view of the Tidyverse “dialect” of the R language

#113

Post by hooloovoo_zoo »

RosanaAnaDana wrote: post #107
hadley wrote: post #101

Earlier quoted context omitted.

You are of course free to dispute what is in the tidyverse, but I pretty strongly believe that it is part of the tidyverse

Seeing as the tidyverse is pretty much your invention, its well within your purvue to define what is in and what is out. I do think, respectfully, that both the op and the general sentiment article have the right of it. Data.table and data.table-esque notation represent such an improvement of tibble/dplyr, that within my company, we're making a concerted effort to purge all tidyverse packages from general use (less g…

"Tidyverse was fine in school. It doesn't pass muster in production...."

This is a bit disrespectful.

"Data.table syntax is simpler, easier to read, easier to teach..."

This is rather arbitrary, and I don't think it's the majority view of the community, whatever the advantages of data.table.

"...orders of magnitude faster"

This is an exaggeration in most real cases, even according to the benchmarks pointed to by data.table.[1]

[1] https://h2oai.github.io/db-benchmark/

Re: An opinionated view of the Tidyverse “dialect” of the R language

#114

Post by cosinequanon »

cwyers wrote: post #94
ellisv wrote: post #91

As an R user of some 10+ years, I think some of this is spot on and some of it is just silly. Pretty much everyone knows the Tidyverse is slow to run, but many of us find it faster to write and very readable because it avoids one-time-use assignments (i.e. in `a need the Tidyverse and it doesn't run faster. Fair criticism. > The "star" of the Tidyverse, dplyr, consists of 263 functions. While a user initially need no…

> Mostly I think Prof. Matloff is forgetting that base R is kinda terrible and no one else has done much about it aside from RStudio. I think he'd disagree with the contention that base R is kinda terrible. Like, I'm pretty sure he's wrong. But this isn't something he's forgotten, it's something he's never believed. The point about the Tidyverse and RStudio is that RStudio doesn't make any of its revenue from the Tid…

If you don't think base R is kinda terrible then I recommend you read R Inferno. It's truly a crazy language with enough footguns for a centipede. A lot of the attraction to the tidyverse is having sane defaults and consistent APIs that help you do the right thing quickly.

Re: An opinionated view of the Tidyverse “dialect” of the R language

#115

Post by malshe »

stilley2 wrote: post #74

I recently tried to do some stuff in R with tidyverse, and was not a fan. I'm no expert, but the tidyverse's frequent use of nonstandard evaluation drove me crazy. It makes it so much more difficult to write functions encapsulating tidy functions. However, I never see people complain about this, so maybe I'm doing something wrong or not grokking something...

No, you are not doing anything wrong. It's a real pain.

Re: An opinionated view of the Tidyverse “dialect” of the R language

#116

Post by finebalance »

wodenokoto wrote: post #104
bsg75 wrote: post #103

Earlier quoted context omitted.

There are nuances that to me make R data frames, especially with Magrittr, simpler to work with over Pandas. Pandas indexing always seems to get in the way. I have been using Python a lot longer than R, but the Pandas syntax is taking longer to internalize. Maybe it's just me?

No. Pandas is a powerful tool, but a poor api / user interface.

Pandas grouping and slicing is, imo, significantly worse than R. And I so despise those multiindexes.

Re: An opinionated view of the Tidyverse “dialect” of the R language

#117

Post by ACow_Adonis »

nonbel wrote: post #102
roenxi wrote: post #44

He is glossing over the major issue with base R, which is its tendancy to switch data types in a way that appears random to new users. As an undergrad I spent nights literally on the verge of tears debugging R code where the types had been mucked up by R's bizarre semantics. Claiming that data[foo] is the same as filter(data, foo) is not correct - the [] and [[]] operators have a lot of strange side effects depending…

> "Dr. Matloff is grossly underestimating how painful it is for beginners to, eg, figure out when they are dealing with a column of strings vs a column of factors." This is just sapply(df, class)... Is this not found in R 101 material that beginners are likely to find?

Pay no attention to the myriad of other apply functions hiding behind the curtain and the difficulty in remembering what each of them does and why you can't just use map, eh? :)

So to answer your question, no, its not just simply that.

Re: An opinionated view of the Tidyverse “dialect” of the R language

#118

Post by robust »

notafraudster wrote: post #83
robust wrote: post #80

Earlier quoted context omitted.

Can you provide an example of a problem that requires multiple tidyverse operations, but could be solved equally well using only lapply?

I run a large scale national survey. We download the data from our survey platform. Survey respondents are asked 100+ questions. The questions change week to week and so the column names are not consistent. We exclude respondents who appear to be cheating the system (rushing through questions, straight-lining, skipping almost every question, etc.) As part of our completion check, we want to do a row-wise map of the d…

Thank you for providing this example! I share your experience that rowwise operations seem more difficult to program using the tidyverse than using apply.

Re: An opinionated view of the Tidyverse “dialect” of the R language

#119

Post by GlennS »

Bootvis wrote: post #5
kickout wrote: post #3

Decent critiques in my opinion. I was trained on/learned base-R myself ~10 years ago and love the "tidyverse" (although the author is correct, data.table is superior for big data and its not particularly close). Can't imagine people that only know tidyr/dplyr/etc without knowing base-R, seems like those people would get exposed quickly. I enjoy base-R solutions where I can. I use data.table when my data sets are medi…

I don’t even understand the not a real language critique, R: - is based on scheme, a HN favourite; - integrates very well with C++ through RCpp allowing you to do whatever you want. 9/10 times someone already went through the trouble for you.

There's really not much Lisp/Scheme left in R these days.

Function arguments/environments are still pairlists: a type of cons cell.

You can manipulate the parameters to a function as symbols before you evaluate them. This is useful — many very good R libraries all make heavy use of it — and certainly very interesting. Lispers probably know it as quote/antiquote.

I suppose we could also point that, much like most Lisps, R gives you plenty of object systems to choose from...

And that's about it for R-as-a-Lisp.

It's also a really bad language for working with tree-structured data, something Lisps normally excel at.

Re: An opinionated view of the Tidyverse “dialect” of the R language

#120

Post by Bootvis »

hadley wrote: post #101
Bootvis wrote: post #49

Earlier quoted context omitted.

The claim that ggplot2 is tidyverse can be disputed. It existed before and works fine outside of it.

You are of course free to dispute what is in the tidyverse, but I pretty strongly believe that it is part of the tidyverse

Thank you for your reply and all your work.

I probably should have phrased my comment better. My point was that it’s perfectly possible to use ggplot without explicit knowledge of tidy principles or tibbles. This is great! And for example, I’m reading through your ggplot book and it doesn’t make reference to it.[1] In my work, we use data.tables (we believe we need the raw performance) with ggplot for visualization and are not using the rest of tidyverse and it works fine.

[1]: In recent versions this seems to be slowly changing.

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