Databases
StackOverflow2013
Postsdbo
PO
 

Note that there are some explanatory texts on larger screens.

plurals
  1. PO
    primarykey
    data
    text
    <p><strong>Completely rewritten on 2015-11-24, to fix an error in previous versions.</strong></p> <p>You have a few options.</p> <ol> <li><p>Process all of the target columns with an embedded call to <code>lapply()</code>, using <code>:=</code> to assign the modified values in place. This relies on <code>:=</code>'s very handy support for simultaneous assignment to several column named on its LHS.</p></li> <li><p>Use a <code>for</code> loop to run through the target columns one at a time, using <code>set()</code> to modify the value of each one in turn.</p></li> <li><p>Use a <code>for</code> loop to iterate over multiple "naive" calls to <code>[.data.table()</code>, each one of which modifies a single column.</p></li> </ol> <p>These methods all seem about equally fast, so which one you use will be mostly a matter of taste. (1) is nicely compact and expressive. It's what I most often use, though you may find (2) easier to read. Because they process and modify the columns one at a time, (2) or (3) will have an advantage in the rare situation in which your data.table is so large that you are in danger of running up against limits imposed by your R session's available memory.</p> <pre><code>library(data.table) ## Create three identical 1000000-by-20 data.tables DT1 &lt;- data.table(1:1e6, as.data.table(replicate(1e6, paste(sample(letters, nr, TRUE), sample(letters, nr, TRUE))))) cnames &lt;- c("ID", paste0("X", 1:19)) setnames(DT1, cnames) DT2 &lt;- copy(DT1); DT3 &lt;- copy(DT1) ## Method 1 system.time({ DT1[, cnames[-1] := lapply(DT1[,cnames[-1],with=FALSE], function(x) gsub(" ", "_", x))] }) ## user system elapsed ## 10.90 0.11 11.06 ## Method 2 system.time({ for(cname in cnames[-1]) { set(DT2, j=cname, value=gsub(" ", "_", DT2[[cname]])) } }) ## user system elapsed ## 10.65 0.05 10.70 ## Method 3 system.time({ for(cname in cnames[-1]) { DT3[ , cname := gsub(" ", "_", DT3[[cname]]), with=FALSE] } }) ## user system elapsed ## 10.33 0.03 10.37 </code></pre> <p>For more details on <code>set()</code> and <code>:=</code>, read their help page, gotten by typing <code>?set</code> or <code>?":="</code>.</p>
    singulars
    1. This table or related slice is empty.
    1. POHow do I run apply on a data.table?
      singulars
      1. PTQuestion
    1. PTAnswer
    1. USJosh O'Brien
    1. USJosh O'Brien
    plurals
    1. This table or related slice is empty.
    1. This table or related slice is empty.
    1. POHow do I run apply on a data.table?
      singulars
      1. PTQuestion
    1. This table or related slice is empty.
    1. VO
      singulars
      1. PO
      1. This table or related slice is empty.
      1. VTUpMod
    2. VO
      singulars
      1. PO
      1. This table or related slice is empty.
      1. VTUpMod
    3. VO
      singulars
      1. PO
      1. This table or related slice is empty.
      1. VTUpMod
    1. COThis is an interesting case. Here, 19 columns out of 20 are being replaced; the RHS of `:=` is almost all the table. The advantage of `:=` is greater when, say, one or two columns are added to 20, or one or two columns of 20 are modified. In those cases most of the columns are left in place and `:=` is much faster than copying the whole table.
      singulars
      1. PO
      1. USMatt Dowle
    2. COAlso, `set()` is a new function in v1.8.0 (not yet on CRAN) which provides `:=` functionality directly. `set()` can be much faster than `:=` when assigning within a loop (for easier more natural programming). There's an example in latest NEWS on homepage.
      singulars
      1. PO
      1. USMatt Dowle
    3. CO@MatthewDowle -- Thanks for your comments. They reminded me that, over the weekend, I'd had a nagging feeling about the answer I'd given here, and spurred me to revisit this. Obviously I had good reason to feel nagged. Please have a look at my revised answer. Also **please add any of the suggestions you've got in your comments to the text of my answer**, where you think they might help. I'll have a look at `set()`, but don't yet feel qualified to discuss it. And, once again, thanks for all of the work you put into continuing development of the data.table package!
      singulars
      1. PO
      1. USJosh O'Brien
 

Querying!

 
Guidance
A row detail

Detail views are divided into sections. All the information in the data section comes from columns in the selected row. The other sections display data from other, related rows.

Related data can be related in a to-one or a to-many fashion. Captions of data related in a to-many fashion link to a list view showing a filtered view of the table.

Try moving around until you find a non-empty to-many entry and click on the label to get to one. You can move back to the root by clicking on the database name in the header.

SQuiL has stopped working due to an internal error.

If you are curious you may find further information in the browser console, which is accessible through the devtools (F12).

Reload