[R] Can I use group_map to iteratively process a dataframe?
Rui Barradas
ru|pb@rr@d@@ @end|ng |rom @@po@pt
Sat Jun 5 21:34:42 CEST 2021
Hello,
You are absolutely right, I had misread the SO post date. Apologies for
my mistake. Besides, I even forgot the SO link [1] :(.
Now, for the question.
1. The code is giving errors, that it can't find functions
gwet.ac1.table
kappa2.table
and I have removed the calls to them and the corresponding kappa2 and
gwet values from the output data.frame.
2. In order to make the code more readable to me, I have written
auxiliary functions sensitivity, specificity, pfp and pfn. They extract
a sub-list member, like in the original code.
3. The main problem is that you need to pass epi_analysis its arguments.
But group_map and group_modify do not pass the grouping variable to the
function being called so I create a temp grouping variable by extracting
the assay number and grouping on it. The files are now created.
4.
Also, epi_analysis now returns the data.frames it creates.
I have included col_types in the call to read_csv.
And it gives a message with the output file name, remove it if you find
it useless. (It was meant for debugging so it probably is.)
library(tidyverse) # for cleaning and shaping data
library(epiR)
library(irrCAC)
all_epi_files <- list.files("congtables", pattern = "*.csv",
full.names = TRUE)
#Make export directory
check_create_dir <- function(the_dir) {
if (!dir.exists(the_dir)) {
dir.create(the_dir, recursive = TRUE) } #Creates a directory if it
doesn't already exist
}
# The auxiliary functions
sensitivity <- function(x) x$elements$sensitivity
specificity <- function(x) x$elements$specificity
pfp <- function(x) x$element$pfp
pfn <- function(x) x$element$pfn
#Make function for the series of analyses
epi_analysis <- function(x, the_dir){
# only the first of a vector of elements all equal to each other
# unique() could also be used
assay <- first(x[["TestAssay"]])
#Clean data
dat2 <- x %>%
select(c(Var1, Var2, Freq)) %>%
pivot_wider(Var1, names_from = Var2, values_from = Freq) %>%
remove_rownames %>%
column_to_rownames( var = "Var1") %>%
as.matrix()
#Run tests
rval <- epi.tests(dat2, conf.level = 0.95)
rkappa <- epi.kappa(dat2)
#gwet <- gwet.ac1.table(dat2)
#kappa2 <- kappa2.table(dat2)
#Export results
hd <- c('sensitivity', 'specificity', 'pfp', 'pfn',
#'kappa', 'gwet',
'pabak')
ests <- c(round(sensitivity(rval)$est, digits = 3),
round(specificity(rval)$est, digits = 3),
round(pfp(rval)$est, digits = 3),
round(pfn(rval)$est, digits = 3),
#round(kappa2$coeff.val, digits = 3),
#round(gwet$coeff.val, digits = 3),
round(rkappa$pabak$est, digits = 3))
cis <- c(paste(round(sensitivity(rval)$lower, digits = 3),
round(sensitivity(rval)$upper, digits = 3), sep = ","),
paste(round(specificity(rval)$lower, digits = 3),
round(specificity(rval)$upper, digits = 3), sep = ","),
paste(round(pfp(rval)$lower, digits = 3),
round(pfp(rval)$upper, digits = 3), sep = ","),
paste(round(pfn(rval)$lower, digits = 3),
round(pfn(rval)$upper, digits = 3), sep = ","),
#kappa2$coeff.ci,
#gwet$coeff.ci,
paste(round(rkappa$pabak$lower, digits = 3),
round(rkappa$pabak$lower, digits = 3), sep = ","))
df <- data.frame(hd, ests, cis)
outfile <- file.path(the_dir, paste0(assay, ".csv"))
msg <- sprintf("Output file: %s", outfile)
message(msg)
write.csv(df, file = outfile, na = "999.99", row.names = FALSE)
df
}
the_dir_ex <- "data_generated/epidata" #Name the new desired directory
check_create_dir(the_dir_ex) #Make the directory if it doesn't already exist
https://stackoverflow.com/questions/67811339/using-group-walk-to-iteratively-export-an-analysis-on-contingency-tables-after-g
data <- read_csv(
all_epi_files,
col_types = cols(
TestAssay = col_character(),
Var1 = col_character(),
Var2 = col_character(),
Freq = col_double()
)) %>%
mutate(AssayNum = str_extract(TestAssay, "\\d+")) %>%
group_by(AssayNum) %>%
group_map(~ epi_analysis(.x, the_dir_ex))
[1]
https://stackoverflow.com/questions/67811339/using-group-walk-to-iteratively-export-an-analysis-on-contingency-tables-after-g
Hope this helps,
Rui Barradas
Às 14:26 de 05/06/21, Madison Bell escreveu:
> This question had been posted on SO for a week with no response. I reached out to rhelp two days ago. I deleted the original question on SO and reposted an abbreviated version this morning.
>
> Sorry for the cross posting, but I am urgently trying to get some ideas on how approach this problem.
>
> Sent from my iPhone
>
>> On Jun 5, 2021, at 09:07, Rui Barradas <ruipbarradas using sapo.pt> wrote:
>>
>> Hello,
>>
>> This is cross-posted from StackOverflow [1]. Cross posting is not well seen on R-help and the SO post is better explained (at least the data seem to be more complete). You should have waited for an answer there.
>>
>>
>> Hope this helps,
>>
>> Rui Barradas
>>
>> Às 15:03 de 04/06/21, Madison Bell escreveu:
>>> I want to iteratively process a master list of comparisons using
>>> group_walk() as an alternative method to import batches of .csv files.
>>> I have the code for iteratively importing batch csvs here:
>>> #Import list of csv files from directory, formatted as:
>>> |rownm | neg | pos |
>>> |------|-----|-----|
>>> |neg |19 |18 |
>>> |pos |5 |141 |
>>> ```
>>> library(tidyverse) # for cleaning and shaping data
>>> library(epiR)
>>> library(irrCAC)
>>> all_epi_files <- list.files("congtables", pattern = "*.csv",
>>> full.names = TRUE)
>>> #Make export directory
>>> check_create_dir <- function(the_dir) {
>>> if (!dir.exists(the_dir)) {
>>> dir.create(the_dir, recursive = TRUE) } #Creates a directory if it
>>> doesn't already exist
>>> }
>>> the_dir_ex <- "data_generated/epidata" #Name the new desired directory
>>> check_create_dir(the_dir_ex) #Make the directory if it doesn't already exist
>>> #Make function for the series of analyses
>>> epi_analysis <- function(a_csv, the_dir){
>>> #Import data as inserted variables
>>> dat2 <- read_csv(a_csv)%>%
>>> remove_rownames %>%
>>> column_to_rownames(var="rownm") %>%
>>> as.matrix()
>>> #Run tests
>>> rval <- epi.tests(dat2, conf.level = 0.95)
>>> rkappa<-epi.kappa(dat2)
>>> gwet <- gwet.ac1.table(dat2)
>>> kappa2 <- kappa2.table(dat2)
>>> #Export results
>>> hd <- c('sensitivity', 'specificity', 'pfp', 'pfn', 'kappa', 'gwet', 'pabak')
>>> ests <- c(round(rval$elements$sensitivity$est, digits = 3),
>>> round(rval$elements$specificity$est, digits = 3),
>>> round(rval$element$pfp$est, digits = 3),
>>> round(rval$element$pfn$est, digits = 3),
>>> round(kappa2$coeff.val, digits = 3),
>>> round(gwet$coeff.val, digits = 3),
>>> round(rkappa$pabak$est, digits = 3))
>>> cis <- c(paste(round(rval$elements$sensitivity$lower, digits = 3),
>>> round(rval$elements$sensitivity$upper, digits = 3), sep = ","),
>>> paste(round(rval$elements$specificity$lower, digits = 3),
>>> round(rval$elements$specificity$upper, digits = 3), sep = ","),
>>> paste(round(rval$element$pfp$lower, digits = 3),
>>> round(rval$element$pfp$upper, digits = 3), sep = ","),
>>> paste(round(rval$element$pfn$lower, digits = 3),
>>> round(rval$element$pfn$upper, digits = 3), sep = ","),
>>> kappa2$coeff.ci,
>>> gwet$coeff.ci,
>>> paste(round(rkappa$pabak$lower, digits = 3),
>>> round(rkappa$pabak$lower, digits = 3), sep = ","))
>>> df <- data.frame(hd, ests, cis)
>>> write.csv(df,
>>> file = paste0(the_dir, "/", basename(a_csv)),
>>> na = "999.99",
>>> row.names = FALSE)
>>> }
>>> #Execute functions
>>> lapply(all_epi_files,
>>> FUN = epi_analysis,
>>> the_dir = the_dir_ex)
>>> ```
>>> But instead I would like to input a dataset that looks like this:
>>> |Test Assay | Var1 | Var2 |Freq|
>>> |-----------|------|------|----|
>>> |Assay1 |neg |neg |19 |
>>> |Assay1 |neg |pos |5 |
>>> |Assay1 |pos |neg |8 |
>>> |Assay1 |pos |pos |141 |
>>> |Assay2 |neg |neg |25 |
>>> |Assay2 |neg |pos |6 |
>>> |Assay2 |pos |neg |17 |
>>> |Assay2 |pos |pos |33 |
>>> |Assay3 |neg |neg |99 |
>>> |Assay3 |neg |pos |20 |
>>> |Assay3 |pos |neg |5 |
>>> |Assay3 |pos |pos |105 |
>>> I want to use the same function epi_analysis and export a csv for each
>>> Test Assay (in this example Assay1, Assay2, and Assay3). So far I
>>> have:
>>> ```
>>> #Make export directory
>>> check_create_dir <- function(the_dir) {
>>> if (!dir.exists(the_dir)) {
>>> dir.create(the_dir, recursive = TRUE) } #Creates a directory if it
>>> doesn't already exist
>>> }
>>> the_dir_ex <- "data_generated/epidata" #Name the new desired directory
>>> check_create_dir(the_dir_ex) #Make the directory if it doesn't already exist
>>> #Make function for the series of analyses
>>> epi_analysis <- function(.x, the_dir){
>>> #Clean data
>>> dat2 <- .x %>%
>>> select(c(Var1, Var2, Freq)) %>%
>>> pivot_wider(Var1, names_from = Var2, values_from = Freq) %>%
>>> remove_rownames %>%
>>> column_to_rownames( var = "Var1") %>%
>>> as.matrix()
>>> #Run tests
>>> rval <- epi.tests(dat2, conf.level = 0.95)
>>> rkappa<-epi.kappa(dat2)
>>> gwet <- gwet.ac1.table(dat2)
>>> kappa2 <- kappa2.table(dat2)
>>> #Export results
>>> hd <- c('sensitivity', 'specificity', 'pfp', 'pfn', 'kappa', 'gwet', 'pabak')
>>> ests <- c(round(rval$elements$sensitivity$est, digits = 3),
>>> round(rval$elements$specificity$est, digits = 3),
>>> round(rval$element$pfp$est, digits = 3),
>>> round(rval$element$pfn$est, digits = 3),
>>> round(kappa2$coeff.val, digits = 3),
>>> round(gwet$coeff.val, digits = 3),
>>> round(rkappa$pabak$est, digits = 3))
>>> cis <- c(paste(round(rval$elements$sensitivity$lower, digits = 3),
>>> round(rval$elements$sensitivity$upper, digits = 3), sep = ","),
>>> paste(round(rval$elements$specificity$lower, digits = 3),
>>> round(rval$elements$specificity$upper, digits = 3), sep = ","),
>>> paste(round(rval$element$pfp$lower, digits = 3),
>>> round(rval$element$pfp$upper, digits = 3), sep = ","),
>>> paste(round(rval$element$pfn$lower, digits = 3),
>>> round(rval$element$pfn$upper, digits = 3), sep = ","),
>>> kappa2$coeff.ci,
>>> gwet$coeff.ci,
>>> paste(round(rkappa$pabak$lower, digits = 3),
>>> round(rkappa$pabak$lower, digits = 3), sep = ","))
>>> df <- data.frame(hd, ests, cis)
>>> write.csv(df,
>>> file = paste0(the_dir, "/", basename(.x$TestAssay)),
>>> na = "999.99",
>>> row.names = FALSE)
>>> }
>>> data <- read_csv("data_raw/EpiTest.csv") %>%
>>> group_by(TestAssay)%>%
>>> group_map(~ epi_analysis)
>>> ```
>>> But the only output I see is:
>>> ```
>>> [[1]]
>>> function(.x, the_dir){
>>> #Clean data
>>> dat2 <- .x %>%
>>> select(c(Var1, Var2, Freq)) %>%
>>> pivot_wider(Var1, names_from = Var2, values_from = Freq) %>%
>>> remove_rownames %>%
>>> column_to_rownames( var = "Var1") %>%
>>> as.matrix()
>>> #Run tests
>>> rval <- epi.tests(dat2, conf.level = 0.95)
>>> rkappa<-epi.kappa(dat2)
>>> gwet <- gwet.ac1.table(dat2)
>>> kappa2 <- kappa2.table(dat2)
>>> #Export results
>>> hd <- c('sensitivity', 'specificity', 'pfp', 'pfn', 'kappa', 'gwet', 'pabak')
>>> ests <- c(round(rval$elements$sensitivity$est, digits = 3),
>>> round(rval$elements$specificity$est, digits = 3),
>>> round(rval$element$pfp$est, digits = 3),
>>> round(rval$element$pfn$est, digits = 3),
>>> round(kappa2$coeff.val, digits = 3),
>>> round(gwet$coeff.val, digits = 3),
>>> round(rkappa$pabak$est, digits = 3))
>>> cis <- c(paste(round(rval$elements$sensitivity$lower, digits = 3),
>>> round(rval$elements$sensitivity$upper, digits = 3), sep = ","),
>>> paste(round(rval$elements$specificity$lower, digits = 3),
>>> round(rval$elements$specificity$upper, digits = 3), sep = ","),
>>> paste(round(rval$element$pfp$lower, digits = 3),
>>> round(rval$element$pfp$upper, digits = 3), sep = ","),
>>> paste(round(rval$element$pfn$lower, digits = 3),
>>> round(rval$element$pfn$upper, digits = 3), sep = ","),
>>> kappa2$coeff.ci,
>>> gwet$coeff.ci,
>>> paste(round(rkappa$pabak$lower, digits = 3),
>>> round(rkappa$pabak$lower, digits = 3), sep = ","))
>>> df <- data.frame(hd, ests, cis)
>>> write.csv(df,
>>> file = paste0(the_dir, "/", basename(.x$TestAssay)),
>>> na = "999.99",
>>> row.names = FALSE)
>>> }
>>> [[2]]
>>> function(.x, the_dir){
>>> #Clean data
>>> dat2 <- .x %>%
>>> select(c(Var1, Var2, Freq)) %>%
>>> pivot_wider(Var1, names_from = Var2, values_from = Freq) %>%
>>> remove_rownames %>%
>>> column_to_rownames( var = "Var1") %>%
>>> as.matrix()
>>> #Run tests
>>> rval <- epi.tests(dat2, conf.level = 0.95)
>>> rkappa<-epi.kappa(dat2)
>>> gwet <- gwet.ac1.table(dat2)
>>> kappa2 <- kappa2.table(dat2)
>>> #Export results
>>> hd <- c('sensitivity', 'specificity', 'pfp', 'pfn', 'kappa', 'gwet', 'pabak')
>>> ests <- c(round(rval$elements$sensitivity$est, digits = 3),
>>> round(rval$elements$specificity$est, digits = 3),
>>> round(rval$element$pfp$est, digits = 3),
>>> round(rval$element$pfn$est, digits = 3),
>>> round(kappa2$coeff.val, digits = 3),
>>> round(gwet$coeff.val, digits = 3),
>>> round(rkappa$pabak$est, digits = 3))
>>> cis <- c(paste(round(rval$elements$sensitivity$lower, digits = 3),
>>> round(rval$elements$sensitivity$upper, digits = 3), sep = ","),
>>> paste(round(rval$elements$specificity$lower, digits = 3),
>>> round(rval$elements$specificity$upper, digits = 3), sep = ","),
>>> paste(round(rval$element$pfp$lower, digits = 3),
>>> round(rval$element$pfp$upper, digits = 3), sep = ","),
>>> paste(round(rval$element$pfn$lower, digits = 3),
>>> round(rval$element$pfn$upper, digits = 3), sep = ","),
>>> kappa2$coeff.ci,
>>> gwet$coeff.ci,
>>> paste(round(rkappa$pabak$lower, digits = 3),
>>> round(rkappa$pabak$lower, digits = 3), sep = ","))
>>> df <- data.frame(hd, ests, cis)
>>> write.csv(df,
>>> file = paste0(the_dir, "/", basename(.x$TestAssay)),
>>> na = "999.99",
>>> row.names = FALSE)
>>> }
>>> [[3]]
>>> function(.x, the_dir){
>>> #Clean data
>>> dat2 <- .x %>%
>>> select(c(Var1, Var2, Freq)) %>%
>>> pivot_wider(Var1, names_from = Var2, values_from = Freq) %>%
>>> remove_rownames %>%
>>> column_to_rownames( var = "Var1") %>%
>>> as.matrix()
>>> #Run tests
>>> rval <- epi.tests(dat2, conf.level = 0.95)
>>> rkappa<-epi.kappa(dat2)
>>> gwet <- gwet.ac1.table(dat2)
>>> kappa2 <- kappa2.table(dat2)
>>> #Export results
>>> hd <- c('sensitivity', 'specificity', 'pfp', 'pfn', 'kappa', 'gwet', 'pabak')
>>> ests <- c(round(rval$elements$sensitivity$est, digits = 3),
>>> round(rval$elements$specificity$est, digits = 3),
>>> round(rval$element$pfp$est, digits = 3),
>>> round(rval$element$pfn$est, digits = 3),
>>> round(kappa2$coeff.val, digits = 3),
>>> round(gwet$coeff.val, digits = 3),
>>> round(rkappa$pabak$est, digits = 3))
>>> cis <- c(paste(round(rval$elements$sensitivity$lower, digits = 3),
>>> round(rval$elements$sensitivity$upper, digits = 3), sep = ","),
>>> paste(round(rval$elements$specificity$lower, digits = 3),
>>> round(rval$elements$specificity$upper, digits = 3), sep = ","),
>>> paste(round(rval$element$pfp$lower, digits = 3),
>>> round(rval$element$pfp$upper, digits = 3), sep = ","),
>>> paste(round(rval$element$pfn$lower, digits = 3),
>>> round(rval$element$pfn$upper, digits = 3), sep = ","),
>>> kappa2$coeff.ci,
>>> gwet$coeff.ci,
>>> paste(round(rkappa$pabak$lower, digits = 3),
>>> round(rkappa$pabak$lower, digits = 3), sep = ","))
>>> df <- data.frame(hd, ests, cis)
>>> write.csv(df,
>>> file = paste0(the_dir, "/", basename(.x$TestAssay)),
>>> na = "999.99",
>>> row.names = FALSE)
>>> }
>>> [[4]]
>>> function(.x, the_dir){
>>> #Clean data
>>> dat2 <- .x %>%
>>> select(c(Var1, Var2, Freq)) %>%
>>> pivot_wider(Var1, names_from = Var2, values_from = Freq) %>%
>>> remove_rownames %>%
>>> column_to_rownames( var = "Var1") %>%
>>> as.matrix()
>>> #Run tests
>>> rval <- epi.tests(dat2, conf.level = 0.95)
>>> rkappa<-epi.kappa(dat2)
>>> gwet <- gwet.ac1.table(dat2)
>>> kappa2 <- kappa2.table(dat2)
>>> #Export results
>>> hd <- c('sensitivity', 'specificity', 'pfp', 'pfn', 'kappa', 'gwet', 'pabak')
>>> ests <- c(round(rval$elements$sensitivity$est, digits = 3),
>>> round(rval$elements$specificity$est, digits = 3),
>>> round(rval$element$pfp$est, digits = 3),
>>> round(rval$element$pfn$est, digits = 3),
>>> round(kappa2$coeff.val, digits = 3),
>>> round(gwet$coeff.val, digits = 3),
>>> round(rkappa$pabak$est, digits = 3))
>>> cis <- c(paste(round(rval$elements$sensitivity$lower, digits = 3),
>>> round(rval$elements$sensitivity$upper, digits = 3), sep = ","),
>>> paste(round(rval$elements$specificity$lower, digits = 3),
>>> round(rval$elements$specificity$upper, digits = 3), sep = ","),
>>> paste(round(rval$element$pfp$lower, digits = 3),
>>> round(rval$element$pfp$upper, digits = 3), sep = ","),
>>> paste(round(rval$element$pfn$lower, digits = 3),
>>> round(rval$element$pfn$upper, digits = 3), sep = ","),
>>> kappa2$coeff.ci,
>>> gwet$coeff.ci,
>>> paste(round(rkappa$pabak$lower, digits = 3),
>>> round(rkappa$pabak$lower, digits = 3), sep = ","))
>>> df <- data.frame(hd, ests, cis)
>>> write.csv(df,
>>> file = paste0(the_dir, "/", basename(.x$TestAssay)),
>>> na = "999.99",
>>> row.names = FALSE)
>>> }
>>> ```
>>> and there are no csvs in my epidata folder. Any
>>> suggestions/corrections welcomed. I haven't used group_map() before,
>>> but I am keen to use it.
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