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Madison Bell

2021-Jun-04 14:03 UTC

[R] Can I use group_map to iteratively process a dataframe?

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.

Greg Minshall

2021-Jun-05 06:37 UTC

head link

[R] Can I use group_map to iteratively process a dataframe?

Madison,

by the way, it's sort of hard to follow your example.  there's some
concept of MWE ==? Minimum Working Example.  duckduckgo, or others on
the list, can probably point the way.

and, by the way :), i'm no expert.  in particular, not on magrittr
pipes, or on group_*, though i use both in some of my code.
> data <- read_csv("data_raw/EpiTest.csv") %>%
>   group_by(TestAssay)%>%
>   group_map(~ epi_analysis)
sans-pipe, i would have had

: group_map(df, epi_analysis, the_dir)

or some such.  in magrittr pipes, maybe that would be

: ... %>% group_map, epi_analysis, the_dir)

or some such?

hth.

cheers, Greg

Rui Barradas

2021-Jun-05 13:07 UTC

head link

[R] Can I use group_map to iteratively process a dataframe?

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

?s 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.
> 
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

R help - Jun 2021 - Can I use group_map to iteratively process a dataframe?

[R] Can I use group_map to iteratively process a dataframe?

[R] Can I use group_map to iteratively process a dataframe?

[R] Can I use group_map to iteratively process a dataframe?