docs: #84 adjusted type discussion

vignettes/deepdive.Rmd

@@ -245,7 +245,7 @@ datatable(
 
 ## `xportr_type()`
 
-We are going to explore the type column in the metadata object. A submission to a Health Authority should only have character and numeric types in the data. In the `ADSL` data we have several columns that are in the Date type: `TRTSDT`, `TRTEDT`, `DISONSDT`, `VISIT1DT` and `RFENDT`. We will change one variable type to a [factor variable](https://forcats.tidyverse.org/), which is a common data structure in R, to give us some educational opportunities. 
+We are going to explore the type column in the metadata object. A submission to a Health Authority should only have character and numeric types in the data. In the `ADSL` data we have several columns that are in the Date type: `TRTSDT`, `TRTEDT`, `DISONSDT`, `VISIT1DT` and `RFENDT` - under the hood these are actually numeric values and will be left as is. We will change one variable type to a [factor variable](https://forcats.tidyverse.org/), which is a common data structure in R, to give us some educational opportunities to see `xportr_type()` in action. 
 
 ```{r}
 adsl_fct <- adsl %>%
@@ -270,7 +270,7 @@ adsl_type_glimpse <- adsl_type %>%
  select(STUDYID, TRTSDT, TRTEDT, DISONSDT, VISIT1DT, RFENDT)
 ```
 
-Success! As we can see below, `xportr_type()` applied the types from the metadata object to the below columns converting them all to the proper type. The functions in `{xportr}` also display this coercion to the user in the console, which is seen above. 
+Success! As we can see below, `xportr_type()` applied the types from the metadata object to the `STUDYID` variables converting to the proper type. The functions in `{xportr}` also display this coercion to the user in the console, which is seen above. 
 
 ```{r, echo = TRUE}
 glimpse(adsl_type_glimpse)