
Last chance! 50% off unlimited learning
Sale ends in
data.frame
to anticipate problems before writing to a REDCap project.data.frame
to anticipate problems before writing with REDCap's API.
validate_for_write( d )
validate_no_logical( d )
validate_no_uppercase( d )
data.frame
containing the dataset used to update the REDCap project. Required.data.frame
, where each potential violation is a row. The two columns are:
field_name
: The name of the data.frame
that might cause problems during the upload.
field_index
: The position of the field. (For example, a value of '1' indicates the first column, while a '3' indicates the third column.)
concern
: A description of the problem potentially caused by the field
.
suggestion
: A potential solution to the concern.
validate_for_read()
function executes all
these individual validation checks. It allows the client to check everything with one call.
d <- data.frame(
record_id = 1:4,
flag_logical = c(TRUE, TRUE, FALSE, TRUE),
flag_Uppercase = c(4, 6, 8, 2)
)
validate_for_write(d = d)
Run the code above in your browser using DataLab