Update 1-data-exploration.R

ML/1-data-exploration.R

@@ -11,6 +11,7 @@ box::use(
   ,readr
   ,tidyr
   ,gp2 = ggplot2[ggplot, aes]
+  ,gtsummary
 )
 
 
@@ -54,64 +55,47 @@ ds_low_tsh_raw <- readr$read_rds(
 
 
 ds_high_tsh <- ds_high_tsh_raw %>%
-  dplyr$mutate(ft4_dia = dplyr$if_else(`50995` < 0.93, 1, 0)) %>%
+  dplyr$mutate(ft4_dia = dplyr$if_else(`50995` < 0.93, TRUE, FALSE)) %>%
   #can rename with a vector using either of these
   # dplyr$rename_with(~names(test_list_names), dplyr$all_of(test_list_names))
   dplyr$rename(!!!test_list_names) %>%
-  dplyr$select(-FT4)
+  dplyr$select(-FT4, -subject_id, -charttime) %>%
+  dplyr$relocate(gender, anchor_age)
 
 
 ds_low_tsh <- ds_low_tsh_raw %>%
-  dplyr$mutate(ft4_dia = dplyr$if_else(`50995` > 1.7, 1, 0)) %>%
+  dplyr$mutate(ft4_dia = dplyr$if_else(`50995` > 1.7, TRUE, FALSE)) %>%
   #can rename with a vector using either of these
   # dplyr$rename_with(~names(test_list_names), dplyr$all_of(test_list_names))
   dplyr$rename(!!!test_list_names) %>%
-  dplyr$select(-FT4)
+  dplyr$select(-FT4, -subject_id, -charttime) %>%
+  dplyr$relocate(gender, anchor_age)
 
 
 
 # basic visualization -----------------------------------------------------
 
-#graph and table of missing tests
-
-missing_count <- function(ds){
-
-  df <- dplyr$as_tibble(colSums(is.na(ds)), rownames = NA ) %>%
-    tibble::rownames_to_column()
-
-  graph <- df %>%
-    ggplot(aes(x = rowname, y = value)) +
-    gp2$geom_col() +
-    gp2$theme(
-      axis.text.x = gp2$element_text(angle = 90)
-    )
-
-  return(
-    list(
-      df = df
-      ,graph = graph
-      )
-    )
-
-}
-
-high_missing <- missing_count(ds_high_tsh)
-low_missing <- missing_count(ds_low_tsh)
-
-missing_table <- high_missing$df %>%
-  dplyr$left_join(low_missing$df, by = "rowname")
-
+#summary Table
 #use this instead of making myself
-ds_high_tsh %>% gtsummary::tbl_summary(by = ft4_dia)
+high_table_summary <- ds_high_tsh %>%
+  gtsummary$tbl_summary(
+    by = ft4_dia
+    ,missing = "no"
+    ,label = list(
+      gender ~ "Gender"
+      ,anchor_age ~ "Age"
+      )
+    ,statistic = list(
+      gtsummary$all_continuous() ~ "{median} ({min}-{max})
+      /n Missing: {N_miss} "
+      )
+    ) %>%
+  gtsummary$add_p() %>%
+  gtsummary$modify_header(label = "**Variable**") %>%
+  gtsummary$modify_spanning_header(gtsummary$all_stat_cols() ~ "**Free T4 Diagnostic**")
 
+high_table_summary
 
-# count of diagnostics ft4 and freq
-t1 <- ds_high_tsh %>%
-  dplyr$count(ft4_dia) %>%
-  dplyr$mutate(freq = n/sum(n)) %>%
-  knitr::kable()
-
-t1
 
 # correlation plot
 ds_corr <- cor(ds_high_tsh %>% dplyr$select(-subject_id, - charttime)