# ClinicoPath 0.0.2.0019

- rewrote summary of categorical values to decrease dependencies

DESCRIPTION

@@ -1,8 +1,8 @@
 Type: Package
 Package: ClinicoPath
 Title: Analysis for Clinicopathological Research
-Version: 0.0.2.0018
-Date: 2020-07-03
+Version: 0.0.2.0019
+Date: 2020-07-04
 Authors@R: 
     person(given = "Serdar",
            family = "Balci",
@@ -75,10 +75,8 @@ Suggests:
     rcrossref
 Remotes:
     ndphillips/FFTrees,
-    easystats/report,
     spgarbet/tangram,
     cran/rmngb,
-    mixOmicsTeam/mixOmics,
     mayoverse/arsenal
 VignetteBuilder:
     knitr

NEWS.md

@@ -1,3 +1,9 @@
+# ClinicoPath 0.0.2.0019
+
+- rewrote summary of categorical values to decrease dependencies
+
+
+
 # ClinicoPath 0.0.2.0018
 
 -   added cumulative events and cumulative hazard plots to survival

R/reportcat.b.R

@@ -89,28 +89,28 @@ reportcatClass <- if (requireNamespace('jmvcore')) R6::R6Class(
             myvars <- unlist(myvars)
 
 
-            myreport <- mydata %>%
-                select(myvars) %>%
-                report::report(.,
-                               median = FALSE,
-                               centrality = TRUE,
-                               dispersion = TRUE,
-                               range = TRUE,
-                               distribution = FALSE,
-                               levels_percentage = FALSE,
-                               n_entries = 3,
-                               missing_percentage = FALSE
-            #                    median = med,
-            #                    centrality = cent,
-            #                    dispersion = disp,
-            #                    range = ran,
-            #                    distribution = distr,
-            #                    levels_percentage = lev,
-            #                    n_characters = n_ch,
-            #                    missing_percentage = mis
-                               )
-
-            results1 <- myreport
+            # myreport <- mydata %>%
+            #     select(myvars) %>%
+            #     report::report(.,
+            #                    median = FALSE,
+            #                    centrality = TRUE,
+            #                    dispersion = TRUE,
+            #                    range = TRUE,
+            #                    distribution = FALSE,
+            #                    levels_percentage = FALSE,
+            #                    n_entries = 3,
+            #                    missing_percentage = FALSE
+            # #                    median = med,
+            # #                    centrality = cent,
+            # #                    dispersion = disp,
+            # #                    range = ran,
+            # #                    distribution = distr,
+            # #                    levels_percentage = lev,
+            # #                    n_characters = n_ch,
+            # #                    missing_percentage = mis
+            #                    )
+            #
+            # results1 <- myreport
 
 
 
@@ -119,6 +119,67 @@ reportcatClass <- if (requireNamespace('jmvcore')) R6::R6Class(
             #     dplyr::filter(na > 0)
 
 
+            # for (fac in facs)
+            #     data[[fac]] <- as.factor(data[[fac]])
+
+
+
+            # catsummary function
+            catsummary <- function(myvar) {
+
+
+
+
+                leng <- length(mydata[[myvar]])
+
+                miss <- sum(is.na(mydata[[myvar]]))
+
+                valid <- leng - miss
+
+                nlev <- nlevels(as.factor(mydata[[myvar]]))
+
+                summar <- summary(as.factor(mydata[[myvar]])) %>%
+                    as.table() %>%
+                    tibble::as_tibble(.name_repair = "unique") %>%
+                    dplyr::filter(.[[1]] != "NA's") %>%
+                    dplyr::arrange(dplyr::desc(n))
+
+                summar$validtotal <- valid
+
+                description <- summar %>%
+                    dplyr::mutate(
+                        percent = n/validtotal
+                    ) %>%
+                    dplyr::mutate(
+                        description = glue::glue(
+                            "{...1}: n = {n}, {scales::percent(percent)}. "
+                        )
+                    ) %>%
+                    dplyr::select(description) %>%
+                    dplyr::pull(.)
+
+
+                sentence1 <- paste0(
+                    myvar, " has ", leng, " observations and ", nlev, " levels. "
+                )
+
+                sentence3 <- paste0("There are ", miss, " missing values.")
+
+                sentence <- c(
+                    sentence1,
+                    unlist(description),
+                    sentence3
+                )
+
+                return(paste0(sentence, collapse = ""))
+
+            }
+
+
+
+            results <- purrr::map(.x = myvars, .f = catsummary)
+
+            results1 <- unlist(results)
 
             self$results$text$setContent(results1)
 

codemeta.json

@@ -14,7 +14,7 @@
   ],
   "issueTracker": "\n    https://github.com/sbalci/ClinicoPathJamoviModule/issues/",
   "license": "https://spdx.org/licenses/GPL-3.0",
-  "version": "0.0.2.17",
+  "version": "0.0.2.19",
   "programmingLanguage": {
     "@type": "ComputerLanguage",
     "name": "R",
@@ -657,6 +657,6 @@
     "survival-analysis",
     "natural-language-summaries"
   ],
-  "fileSize": "302.535KB",
+  "fileSize": "304.534KB",
   "readme": "https://github.com/sbalci/ClinicoPathJamoviModule/blob/master/README.md"
 }

jamovi/0000.yaml

@@ -1,12 +1,12 @@
 ---
 title: Common Analysis for Clinicopathological Research
 name: ClinicoPath
-version: 0.0.2.0018
+version: 0.0.2.0019
 jms: '1.0'
 authors:
   - Serdar Balci
 maintainer: Serdar Balci <drserdarbalci@gmail.com>
-date: '2020-07-03'
+date: '2020-07-04'
 type: R
 description: >-
   ClinicoPath help researchers to generate natural language summaries of their

tododata/todo.Rmd

@@ -1196,6 +1196,82 @@ deneme <- readxl::read_xlsx(path = here::here("tododata", "histopathology-templa
 ```
 
 
+```{r}
+library(magrittr)
+
+myvar <- deneme$LVI
+
+
+# The data contains 250 observations of the following variables:
+#   - Group: 2 levels: Control (n = 120, 48.00%); Treatment (n = 129, 51.60%) and missing (n = 1, 0.40%)
+#   - Sex: 2 levels: Male (n = 128, 51.20%); Female (n = 121, 48.40%) and missing (n = 1, 0.40%)
+
+
+
+
+
+unique(deneme$LVI)
+
+leng <- length(deneme$LVI)
+
+for (fac in facs)
+            data[[fac]] <- as.factor(data[[fac]])
+
+miss <- sum(is.na(deneme$LVI))
+
+valid <- leng - miss
+
+nlev <- nlevels(as.factor(deneme$LVI))
+
+unique(as.factor(deneme$LVI))
+
+
+
+summar <- summary(as.factor(deneme$LVI)) %>% 
+as.table() %>%
+  tibble::as_tibble(.name_repair = "unique") %>% 
+    dplyr::filter(.[[1]] != "NA's") 
+
+summar$validtotal <- valid
+
+
+description <- summar %>% 
+    dplyr::mutate(
+        percent = n/validtotal
+        ) %>% 
+    dplyr::mutate(
+        description = glue::glue(
+            "{...1}: n = {n}, {scales::percent(percent)}"
+                            )
+                    ) %>%
+                    dplyr::select(description) %>%
+                    dplyr::pull()
+
+
+
+paste0(
+    myvar, " has ", leng, " observations and ", nlev, " levels.",
+    unlist(description),
+    "There are ", miss, "missing values."
+       )
+
+
+# catsummary function
+catsummary <- function(myvar) {
+
+    
+    
+
+
+
+            }
+```
+
+
+
+
+
+
 ```{r report}
 deneme <- readxl::read_xlsx(path = here::here("tododata", "histopathology-template2019-11-25.xlsx"))
 
@@ -3487,3 +3563,11 @@ ids[["records"]]
 ```
 
 
+
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+