I am trying to write a function in tidyverse/dplyr that I want to eventually use with lapply (or map). (I had been working on it to answer this question, but came upon an interesting result/dead-end. Please don't mark this as a duplicate - this question is an extension/departure from the answers that you see there.)
Is there
1) a way to get a list of quoted variables to work inside a dplyr function
(and not use the deprecated SE_ functions) or is there
2) some way to feed a list of unquoted strings through an lapply or map
I have used the Programming in Dplyr vignette to construct what I believe is a function most in line with the current standard
for working with the NSE.
sample_data <-
read.table(text = "REVENUEID AMOUNT YEAR REPORT_CODE PAYMENT_METHOD INBOUND_CHANNEL AMOUNT_CAT
1 rev-24985629 30 FY18 S Check Mail 25,50
2 rev-22812413 1 FY16 Q Other Canvassing 0.01,10
3 rev-23508794 100 FY17 Q Credit_card Web 100,250
4 rev-23506121 300 FY17 S Credit_card Mail 250,500
5 rev-23550444 100 FY17 S Credit_card Web 100,250
6 rev-21508672 25 FY14 J Check Mail 25,50
7 rev-24981769 500 FY18 S Credit_card Web 500,1e+03
8 rev-23503684 50 FY17 R Check Mail 50,75
9 rev-24982087 25 FY18 R Check Mail 25,50
10 rev-24979834 50 FY18 R Credit_card Web 50,75
", header = TRUE, stringsAsFactors = FALSE)
report <- function(report_cat){
report_cat <- enquo(report_cat)
sample_data %>%
group_by(!!report_cat, YEAR) %>%
summarize(num=n(),total=sum(AMOUNT)) %>%
rename(REPORT_VALUE = !!report_cat) %>%
mutate(REPORT_CATEGORY := as.character(quote(!!report_cat))[2])
}
Which works fine for generating a single report:
> report(REPORT_CODE) # A tibble: 7 x 5 # Groups: REPORT_VALUE [4] REPORT_VALUE YEAR num total REPORT_CATEGORY <chr> <chr> <int> <int> <chr> 1 J FY14 1 25 REPORT_CODE 2 Q FY16 1 1 REPORT_CODE 3 Q FY17 1 100 REPORT_CODE 4 R FY17 1 50 REPORT_CODE 5 R FY18 2 75 REPORT_CODE 6 S FY17 2 400 REPORT_CODE 7 S FY18 2 530 REPORT_CODE
It is when I try and set up a list of all 4 of the reports to generate, that everything breaks down. (Though admittedly the code required in that last line of the function - to return a string with which to then fill the column - should be clue enough that I have wandered off in the wrong direction.)
#the other reports
cat.list <- c("REPORT_CODE","PAYMENT_METHOD","INBOUND_CHANNEL","AMOUNT_CAT")
# Applying and Mapping attempts
lapply(cat.list, report)
map_df(cat.list, report)
Which results in:
> lapply(cat.list, report) Error in (function (x, strict = TRUE) : the argument has already been evaluated > map_df(cat.list, report) Error in (function (x, strict = TRUE) : the argument has already been evaluated
I have also tried to convert the list of strings to names before handing it over to apply and map:
library(rlang)
cat.names <- lapply(cat.list, sym)
lapply(cat.names, report)
map_df(cat.names, report)
> lapply(cat.names, report) Error in (function (x, strict = TRUE) : the argument has already been evaluated > map_df(cat.names, report) Error in (function (x, strict = TRUE) : the argument has already been evaluated
In any case, the reason I am asking this question is that I think that I have written the function to the currently documented standards, but ultimately I can then see no way to utilize a member of the apply or even of the purrr::map family with such a function. Short of rewriting the function to use names like useR has done here https://stackoverflow.com/a/47316151/5088194 is there a way to get this function to work with apply or map?
I am hoping to see this as a result:
# A tibble: 27 x 5 # Groups: REPORT_VALUE [16] REPORT_VALUE YEAR num total REPORT_CATEGORY <chr> <chr> <int> <int> <chr> 1 J FY14 1 25 REPORT_CODE 2 Q FY16 1 1 REPORT_CODE 3 Q FY17 1 100 REPORT_CODE 4 R FY17 1 50 REPORT_CODE 5 R FY18 2 75 REPORT_CODE 6 S FY17 2 400 REPORT_CODE 7 S FY18 2 530 REPORT_CODE 8 Check FY14 1 25 PAYMENT_METHOD 9 Check FY17 1 50 PAYMENT_METHOD 10 Check FY18 2 55 PAYMENT_METHOD # ... with 17 more rows
as.name will convert a string to a name and that can be passed to report:
lapply(cat.list, function(x) do.call("report", list(as.name(x))))
character argument An alternative is to rewrite report so that it accepts a character string argument:
report_ch <- function(colname) {
report_cat <- rlang::sym(colname) # as.name(colname) would also work here
sample_data %>%
group_by(!!report_cat, YEAR) %>%
summarize(num = n(), total = sum(AMOUNT)) %>%
rename(REPORT_VALUE = !!report_cat) %>%
mutate(REPORT_CATEGORY = colname)
}
lapply(cat.list, report_ch)
wrapr An alternate approach is to rewrite report using the wrapr package which is an alternative to rlang/tidyeval:
library(dplyr)
library(wrapr)
report_wrapr <- function(colname)
let(c(COLNAME = colname),
sample_data %>%
group_by(COLNAME, YEAR) %>%
summarize(num = n(), total = sum(AMOUNT)) %>%
rename(REPORT_VALUE = COLNAME) %>%
mutate(REPORT_CATEGORY = colname)
)
lapply(cat.list, report_wrapr)
Of course, this whole problem would go away if you used a different framework, e.g.
plyr
library(plyr)
report_plyr <- function(colname)
ddply(sample_data, c(REPORT_VALUE = colname, "YEAR"), function(x)
data.frame(num = nrow(x), total = sum(x$AMOUNT), REPORT_CATEOGRY = colname))
lapply(cat.list, report_plyr)
sqldf
library(sqldf)
report_sql <- function(colname, envir = parent.frame(), ...)
fn$sqldf("select [$colname] REPORT_VALUE,
YEAR,
count(*) num,
sum(AMOUNT) total,
'$colname' REPORT_CATEGORY
from sample_data
group by [$colname], YEAR", envir = envir, ...)
lapply(cat.list, report_sql)
base - by
report_base_by <- function(colname)
do.call("rbind",
by(sample_data, sample_data[c(colname, "YEAR")], function(x)
data.frame(REPORT_VALUE = x[1, colname],
YEAR = x$YEAR[1],
num = nrow(x),
total = sum(x$AMOUNT),
REPORT_CATEGORY = colname)
)
)
lapply(cat.list, report_base_by)
data.table The data.table package provides another alternative but that has already been covered by another answer.
Update: Added additional alternatives.