Update 1-data-exploration.R

ML/1-data-exploration.R

@@ -77,7 +77,8 @@ ds_low_tsh <- ds_low_tsh_raw %>%
 
 #summary Table
 #use this instead of making myself
-high_table_summary <- ds_high_tsh %>%
+summary_table <- function(ds){
+  table <- ds %>%
     gtsummary$tbl_summary(
       by = ft4_dia
       ,missing = "no"
@@ -87,9 +88,9 @@ high_table_summary <- ds_high_tsh %>%
         ,anchor_age ~ "Age"
         )
       ,statistic = gtsummary$all_continuous() ~ c(
-      "{N_miss}",
+        "{N_miss}"
-      "{median} ({p25}, {p75})",
+        ,"{median} ({p25}, {p75})"
-      "{min}, {max}"
+        ,"{min}, {max}"
         )
       ) %>%
     gtsummary$bold_labels() %>%
@@ -99,12 +100,32 @@ high_table_summary <- ds_high_tsh %>%
     gtsummary$modify_header(label = "**Variable**") %>%
     gtsummary$modify_spanning_header(gtsummary$all_stat_cols() ~ "**Free T4 Diagnostic**")
 
-high_table_summary
+  return(table)
+
+  }
+
+# create both tables
+high_table_summary <- summary_table(ds_high_tsh)
+low_table_summary <- summary_table(ds_low_tsh)
+
+# merge tables
+merged_summary_table <- gtsummary$tbl_merge(
+  tbls = list(high_table_summary, low_table_summary)
+  ,tab_spanner = c(
+    "**Elevated TSH** \n Free T4 Diagnostic"
+    ,"**Decreased TSH** \n Free T4 Diagnostic"
+    )
+  ) %>%
+  gtsummary$as_flex_table()
+
+
+
+
 
 
 # correlation plot
-ds_corr <- cor(ds_high_tsh %>% dplyr$select(-subject_id, - charttime)
+ds_corr <- cor(ds_high_tsh %>%
-               %>% dplyr$mutate(dplyr$across(gender, ~dplyr$recode(.,M = 1, F = 2)))
+                 dplyr$mutate(dplyr$across(gender, ~dplyr$recode(.,M = 1, F = 2)))
                ,use = "complete.obs")
 
 
@@ -116,7 +137,6 @@ dev.off()
 
 #quick recode of gender, will still do recoding during feature engineering
 g1 <- ds_high_tsh %>%
-  dplyr$select(-subject_id, - charttime) %>%
   dplyr$mutate(dplyr$across(gender, ~dplyr$recode(.,M = 1, F = 2))) %>%
   tidyr$pivot_longer(cols = dplyr$everything()) %>%
   ggplot(aes(x = value)) +
@@ -127,7 +147,7 @@ g1
 
 # this takes a bit to load.  No discernable paterns in the data
 g2 <- ds_high_tsh %>%
-  dplyr$select(-gender, -subject_id, - charttime) %>%
+  dplyr$select(-gender) %>%
   tidyr$pivot_longer(cols = !ft4_dia) %>%
   ggplot(aes(x = factor(ft4_dia), y = value, fill = factor(ft4_dia))) +
   gp2$geom_boxplot(outlier.shape = NA, na.rm = TRUE) +