Update 0-data_prep.R

ML/0-data_prep.R

@@ -12,6 +12,7 @@ box::use(
   ,dplyr
   ,dbplyr
   ,tidyr
+  ,readr
 )
 
 # globals -----------------------------------------------------------------
@@ -65,12 +66,6 @@ patients <- dplyr$tbl(db, "patients") %>%
   dplyr$select(-anchor_year, -anchor_year_group, -dod) %>%
   dplyr$collect()
 
-#this function is failing if run as part of the DB query
-# Recoding Male = 1, Female = 2
-
-patients <- patients %>%
-  dplyr$mutate(dplyr$across(gender, ~dplyr$recode(gender, "M" = 1, "F" = 2)))
-
 # most likely will not use this as there are not as many complete rows.  However
 # gathering it just in case.
 # first is using specimen id, usable data set is using chart time as it appears
@@ -123,6 +118,20 @@ ds_bmp <- patients %>%
   dplyr$filter(dplyr$if_all(.fns = ~!is.na(.)))
 
 
+# save data ---------------------------------------------------------------
+
+
+ds_high_tsh <- ds_bmp %>%
+  dplyr$filter(`50993` > 4.2) %>%
+  readr$write_rds(
+    here("ML","data-unshared","ds_high_tsh.RDS")
+  )
+
+ds_low_tsh <- ds_bmp %>%
+  dplyr$filter(`50993` < 0.27) %>%
+  readr$write_rds(
+    here("ML","data-unshared","ds_low_tsh.RDS")
+  )
 
 
 

ML/0-greeter-dbcreation.R

@@ -39,7 +39,7 @@ readr$read_csv_chunked(
     dbWriteTable(mimicDB, "labevents", chunk, append = TRUE)
     }
   ,chunk_size = 10000
-  ,col_types = "_d_ddTT_d______"
+  ,col_types = "_d_dd_TT_d______"
   )