Programming with data.table
getting started with multiple bare variable names in data.table functions.
Flexible functions in data.table
I’m getting slightly more experienced with data.table, and I really like it.
My learning method was to get pretty deep for a month, reading everything I could and replicating my dplyr code in data.table.
I then stopped using it for a month, and carried on with dplyr.
Then I tried switching back to data.table again. Some of it stuck, some of it didn’t, but I persevered. I’m still struggling with joining tables, (for some reason the default right-joins really throw my mental model), but I really enjoy working with it, and I know there is a lot more for me to learn.
When in use interactively, there are some nice little shortcuts that allow you to explore a dataset reasonably quickly, and I have been able to create some little helper functions without too much effort.
However, I am passing in column names wrapped in quotes, which shouldn’t really be a big deal, but working with dplyr for so long has spoiled me.
So this post is a way to note some potential ways round it.
N.B. not a data.table expert, some of this is probably horrendous, use the comments below / reach out otherwise and educate me. It will be appreciated.
Let’s get set up with the flights dataset:
library(nycflights13)
library(data.table)
data(flights) # bring flights into the environment
setDT(flights)
Normal use and a brief .SD explainer
flights[,head(.SD,5), .SDcols = 'dep_delay']
## dep_delay
## 1: 2
## 2: 4
## 3: 2
## 4: -1
## 5: -6
This does nothing earth shattering, just grabbing the first few rows from the ‘dep_delay’ column. .SD means to take a subset of the data , and I specify the columns with .SDcols (note, not .SDCols as my brain seems to want to type)
You can of course pass in multiple column names like this:
flights[,head(.SD,5), .SDcols = c('dep_delay','carrier','sched_dep_time')]
## dep_delay carrier sched_dep_time
## 1: 2 UA 515
## 2: 4 UA 529
## 3: 2 AA 540
## 4: -1 B6 545
## 5: -6 DL 600
Or you can do this:
columns_of_interest <- c('dep_delay','carrier','sched_dep_time')
flights[,head(.SD,5), .SDcols = columns_of_interest]
## dep_delay carrier sched_dep_time
## 1: 2 UA 515
## 2: 4 UA 529
## 3: 2 AA 540
## 4: -1 B6 545
## 5: -6 DL 600
Single column functions - quoted column names
Of course we don’t want to have to do this repeatedly so we can create a function.
Here is a simple one, which will return unique values for a column of our choosing. There are a few ways we can do this by passing in a quoted column name:
unique_dots <- function(DT,target_col) {
vec <- unique(DT[,..target_col])
vec
}
See the two dots before ‘target_col’ in the function body. That’s the magic right there. Don’t believe me?
unique_dots(flights, 'dep_delay')
## dep_delay
## 1: 2
## 2: 4
## 3: -1
## 4: -6
## 5: -4
## ---
## 524: 358
## 525: 602
## 526: 593
## 527: 1014
## 528: 422
unique_dots(flights,'sched_dep_time')
## sched_dep_time
## 1: 515
## 2: 529
## 3: 540
## 4: 545
## 5: 600
## ---
## 1017: 1058
## 1018: 516
## 1019: 2153
## 1020: 2246
## 1021: 2208
unique_dots(flights,'carrier')
## carrier
## 1: UA
## 2: AA
## 3: B6
## 4: DL
## 5: EV
## 6: MQ
## 7: US
## 8: WN
## 9: VX
## 10: FL
## 11: AS
## 12: 9E
## 13: F9
## 14: HA
## 15: YV
## 16: OO
Cool, we have a function that works.
But wait, we can also do this:
# using with = FALSE
unique_with <- function(DT,target_col) {
vec <- unique(DT[,target_col, with = FALSE])
vec
}
unique_with(flights, 'dep_delay')
## dep_delay
## 1: 2
## 2: 4
## 3: -1
## 4: -6
## 5: -4
## ---
## 524: 358
## 525: 602
## 526: 593
## 527: 1014
## 528: 422
unique_with(flights,'sched_dep_time')
## sched_dep_time
## 1: 515
## 2: 529
## 3: 540
## 4: 545
## 5: 600
## ---
## 1017: 1058
## 1018: 516
## 1019: 2153
## 1020: 2246
## 1021: 2208
unique_with(flights,'carrier')
## carrier
## 1: UA
## 2: AA
## 3: B6
## 4: DL
## 5: EV
## 6: MQ
## 7: US
## 8: WN
## 9: VX
## 10: FL
## 11: AS
## 12: 9E
## 13: F9
## 14: HA
## 15: YV
## 16: OO
And a cursory check that the results are the same for both functions :
all.equal(unique_dots(flights, 'dep_delay'),
unique_with(flights,'dep_delay'))
## [1] TRUE
Well, that all seems marvellous.
But wait, there’s even more. We can pass in a quoted column name and use ‘get’. Note, I wrapped the call to get in brackets to return a data.table, rather than a vector.
unique_get <- function(DT, target_col){
vec <- unique(DT[,.(get(target_col))]) # ugly but returns a DT
vec
}
A marginally less horrible way would be this, which returns a vector:
unique_get2 <- function(DT, target_col){
vec <- unique(DT[,get(target_col)])
vec
}
Anyway, despite the hideousness, it still works
unique_get(flights, 'dep_delay')
## V1
## 1: 2
## 2: 4
## 3: -1
## 4: -6
## 5: -4
## ---
## 524: 358
## 525: 602
## 526: 593
## 527: 1014
## 528: 422
unique_get(flights,'sched_dep_time')
## V1
## 1: 515
## 2: 529
## 3: 540
## 4: 545
## 5: 600
## ---
## 1017: 1058
## 1018: 516
## 1019: 2153
## 1020: 2246
## 1021: 2208
unique_get(flights,'carrier')
## V1
## 1: UA
## 2: AA
## 3: B6
## 4: DL
## 5: EV
## 6: MQ
## 7: US
## 8: WN
## 9: VX
## 10: FL
## 11: AS
## 12: 9E
## 13: F9
## 14: HA
## 15: YV
## 16: OO
Enough of this. Give me multiple unquoted column names
No, I will not do that. Instead, have a function that takes a single unquoted column name
bare_col <- function(dt,n,target_col) {
target_col <- deparse(substitute(target_col))
dt[,head(.SD,n), .SDcols = target_col]
}
If you are thinking, “Dude, this is standard base R stuff” then yes, you are correct. Which is kind of the point.. Does it work? Oh yes..
bare_col(flights,5, dep_delay)
## dep_delay
## 1: 2
## 2: 4
## 3: 2
## 4: -1
## 5: -6
bare_col(flights, 20, origin)
## origin
## 1: EWR
## 2: LGA
## 3: JFK
## 4: JFK
## 5: LGA
## 6: EWR
## 7: EWR
## 8: LGA
## 9: JFK
## 10: LGA
## 11: JFK
## 12: JFK
## 13: JFK
## 14: EWR
## 15: LGA
## 16: JFK
## 17: EWR
## 18: LGA
## 19: LGA
## 20: EWR
I literally hate you. Give me multiple unquoted columns now..
Well, seeing as you asked nicely.. As a reminder, we can do this kind of thing with quotes
flights[,head(.SD,10), .SDcols = c('origin','distance','tailnum')]
## origin distance tailnum
## 1: EWR 1400 N14228
## 2: LGA 1416 N24211
## 3: JFK 1089 N619AA
## 4: JFK 1576 N804JB
## 5: LGA 762 N668DN
## 6: EWR 719 N39463
## 7: EWR 1065 N516JB
## 8: LGA 229 N829AS
## 9: JFK 944 N593JB
## 10: LGA 733 N3ALAA
And we can do this..
getcols <- function(dt,n, ...) {
sdcols <- eval(substitute(alist(...)))
sdcols <- sapply(as.list(sdcols), deparse)
dt[,head(.SD,n),.SDcols = sdcols]
}
And look - no quotes necessary :
getcols(flights, 10, origin, distance , tailnum)
## origin distance tailnum
## 1: EWR 1400 N14228
## 2: LGA 1416 N24211
## 3: JFK 1089 N619AA
## 4: JFK 1576 N804JB
## 5: LGA 762 N668DN
## 6: EWR 719 N39463
## 7: EWR 1065 N516JB
## 8: LGA 229 N829AS
## 9: JFK 944 N593JB
## 10: LGA 733 N3ALAA
getcols(flights, 20, dep_time, sched_dep_time, carrier)
## dep_time sched_dep_time carrier
## 1: 517 515 UA
## 2: 533 529 UA
## 3: 542 540 AA
## 4: 544 545 B6
## 5: 554 600 DL
## 6: 554 558 UA
## 7: 555 600 B6
## 8: 557 600 EV
## 9: 557 600 B6
## 10: 558 600 AA
## 11: 558 600 B6
## 12: 558 600 B6
## 13: 558 600 UA
## 14: 558 600 UA
## 15: 559 600 AA
## 16: 559 559 B6
## 17: 559 600 UA
## 18: 600 600 B6
## 19: 600 600 MQ
## 20: 601 600 B6
This also works :
getcols2 <- function(dt,n, ...) {
sdcols <- eval(substitute(alist(...)))
sdcols <- sapply(sdcols, deparse)
dt[,head(.SD,n),.SDcols = sdcols]
}
getcols2(flights, 10, origin, distance , tailnum)
## origin distance tailnum
## 1: EWR 1400 N14228
## 2: LGA 1416 N24211
## 3: JFK 1089 N619AA
## 4: JFK 1576 N804JB
## 5: LGA 762 N668DN
## 6: EWR 719 N39463
## 7: EWR 1065 N516JB
## 8: LGA 229 N829AS
## 9: JFK 944 N593JB
## 10: LGA 733 N3ALAA
Again, usual disclaimers apply - mainly that I’m not a data.table expert.
There are no doubt a load of better ways of doing this, but this will hopefully serve as a starter.. if you have better ways of creating a flexible function that will accept multiple unknown columns, don’t be shy in sharing them
Thanks :)
Until then, I’ll be getting down with my new found flexi function ability:
