Eli Miller
Eli Miller
Hello, Thanks for the work on this! I was just wondering when the v1.1.8 version would be released with the changes that are currently in dev?
Hello, Really appreciate all of the work that has been done with getting R and Docker working together as well as it does. I'm trying to do a couple of...
## `set_numeric_where` This new function adds a filter step after the numeric_data is created to filter out rows that don't meet the cutoff. Columns, stat, and cutoffs can all be...
This would allow users to specify a cutoff for numeric amounts
``` adsl % set_missing_count(f_str("xx", n), missing = NA) ) build(t) ``` ``` Should result in # A tibble: 2 × 4 row_label1 var1_TRTA ord_layer_index ord_layer_1 1 An AE "1 (100.0%)"...
Idea is to take a JSON/YAML object, then be able to call an interface function and create a Tplyr table from the JSON data
DP control Rules: 0,+1,+2 [but not auto, still user supplied (vector in the source df, varies by PARAMCD)] ### Example ``` f_str_ % set_format_strings( f_str_ ) ) %>% build() ```
This is the functionality that allows dplyr to know the variables in the data you're working with when calling `select` or `filter`. Documentation is in `tidyselect::peek_data`
Allow user to conditionally format based on ranges(>99.9%,
Update count vignette where it says: The default indentation used will be 3 spaces, but as you can see here - you can set the indentation however you like using...