What tools does CV recommend or provide for users to share their data?

Question

My question is simply:

What is the preferred way for CV users to share data?

If there isn't one, I think there should be.

For example, some users provide a link to an external data source. Others dump it in code mode. Each has its pros and cons, but at least they are open ways of sharing the data.

Seeing "[...] send me the data through email" a couple of times on CV was the motivation for this question. I hope we – as a community – agree that such behavior should be discouraged.

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See also:

• https://pastebin.com/ (open code and data sharing tool)
• http://www.sharecsv.com/ (open csv sharing tool)
• place holder: some examples from around CV

Answer 1

I'm contributing this as an answer because it's rather hard to share an example in the comments field:

Data of 20 rows or fewer seem fine to share inline. One nice way to share R data (similar to datalines in SAS) is using textConnection. This blends the ease of copy-paste executable code and readable data formats. It also doesn't require any external links (many of which are blocked on more restricted computer networks like mine).

As an example:

mydf <- read.table(textConnection("
 Sepal.Length Sepal.Width Petal.Length Petal.Width Species
          5.1         3.5          1.4         0.2  setosa
          4.9         3.0          1.4         0.2  setosa
          4.7         3.2          1.3         0.2  setosa
          4.6         3.1          1.5         0.2  setosa
          5.0         3.6          1.4         0.2  setosa
          5.4         3.9          1.7         0.4  setosa
"), header=T)

Answer 2

clarinetist proposed dput() for R users. I also like it a lot. It has the advantage that it outputs all the information a data structure carries, down to the attributes. For instance, in questions about time series analysis, one of the (often) key attributes is the frequency, and this may get lost if a question only gives the time series values.

Specifically, someone may have a question about a dataset. Let's take the built-in AirPassengers dataset as an example. The questioner can simply type

> dput(AirPassengers)

and get the following output, which they simply paste into the question here at CV:

structure(c(112, 118, 132, 129, 121, 135, 148, 148, 136, 119, 
104, 118, 115, 126, 141, 135, 125, 149, 170, 170, 158, 133, 114, 
140, 145, 150, 178, 163, 172, 178, 199, 199, 184, 162, 146, 166, 
171, 180, 193, 181, 183, 218, 230, 242, 209, 191, 172, 194, 196, 
196, 236, 235, 229, 243, 264, 272, 237, 211, 180, 201, 204, 188, 
235, 227, 234, 264, 302, 293, 259, 229, 203, 229, 242, 233, 267, 
269, 270, 315, 364, 347, 312, 274, 237, 278, 284, 277, 317, 313, 
318, 374, 413, 405, 355, 306, 271, 306, 315, 301, 356, 348, 355, 
422, 465, 467, 404, 347, 305, 336, 340, 318, 362, 348, 363, 435, 
491, 505, 404, 359, 310, 337, 360, 342, 406, 396, 420, 472, 548, 
559, 463, 407, 362, 405, 417, 391, 419, 461, 472, 535, 622, 606, 
508, 461, 390, 432), .Tsp = c(1949, 1960.91666666667, 12), class = "ts")

(Note, as above, all the meta information being included at the end.) Then someone contemplating an answer can simply type

AirPassengers <- structure(c(112, 118, 132, 129, 121, 135, 148, 148, 136, 119, ...

and be guaranteed to get the exact data the OP was working on.

Of course the drawback of dput() is that its output is harder to work with for non-R users. However, I for one prefer this over having to read in a tabular structure and fiddling with field types and meta information.