data.table
is a fantastic R package and I am using it in a library I am developing. So far all is going very well, except for one complication. It seems to be much more difficult (compared to the conventional data frames) to refer to data.table
columns using names saved in variables (as for data frames would be, for example: colname="col"; df[df[,colname]<5,colname]=0
).
Perhaps what complicates the things most is the apparent lack of consistency of syntax on this in data.table
. In some cases, eval(colname)
and get(colname)
, or even c(colname)
seem to work. In others, DT[,colname, with=F]
is the solution. Yet in others, such as, for example, the set()
and subset()
functions, I haven't found a solution at all. Finally, an extreme, albeit also quite common use case was discussed earlier (passing column names to data.table programmatically) and the proposed solutions, albeit apparently doing their job, did not seem particularly readable...
Perhaps I am complicating things too much? If anyone could jot down a quick cheatsheet for referring to data.table
column names using variables for different common scenarios, I would be very grateful.
UPDATE:
Some specific examples that work provided I can hard code column names:
x.short = subset(x, abs(dist)<=100) set(x, which(x$val<10), "val", 0)
Now assume distcol="dist"
, valcol="val"
. What is the best way to do the above using distcol
and valcol
, but not dist
and val
?
The term “field” is usually used interchangeably with “column,” but database purists prefer to use the word “field” to denote a particular value or single item of a column.
Typically, the independent variable will be shown on the X axis and the dependent variable will be shown on the Y axis (just like you learned in math class!).
By using the Column name or Column index we can identify a column in a data table.
Title the table; make sure the title relates to the data you will put in your table. The data table title is NOT a repeat of the research question; the title SHOULD be descriptive of the data contained in the table.
If you are going to be doing complicated operations inside your j
expressions, you should probably use eval
and quote
. One problem with that in current version of data.table
is that the environment of eval
is not always correctly processed - eval and quote in data.table (Note: There has been an update to that answer based on an update to the package.) - and the current fix for that is to add .SD
to eval
. As far as I can tell from a few tests that I've run this doesn't affect speed (the way e.g. having .SD[1]
in j
would).
Interestingly this issue only plagues the j
and you'll be fine using eval
normally in i
(where .SD
is not available anyway).
The other problem is assignment, and there you have to have strings. I know one way to extract the string name from a quoted expression - it's not pretty, but it works. Here's an example combining everything together:
x = data.table(dist = c(1:10), val = c(1:10)) distcol = quote(dist) valcol = quote(val) x[eval(valcol) < 5, capture.output(str(distcol, give.head = F)) := eval(distcol)*sum(eval(distcol, .SD))]
Note how I was ok not adding .SD
in one eval(distcol)
, but won't be if I take it out of the other eval
.
Another option is to use get
:
diststr = "dist" valstr = "val" x[get(valstr) < 5, c(diststr) := get(diststr)*sum(get(diststr))]
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