Confirms the columns types match the template, the values follow the allowed ranges of the template and tables can be joined appropriately.
Usage
bpt_check_data(
event = NULL,
location = NULL,
census = NULL,
proportion_calf = NULL,
complete = FALSE,
join = FALSE,
check_study_years = FALSE
)Arguments
- event
A data frame of event data.
- location
A data frame of location data.
- census
A data frame of census data.
- proportion_calf
A data frame of calf proportion data.
- complete
A flag indicating if all data frames need to be supplied.
- join
A flag indicating if joins should be checked.
- check_study_years
A flag indicating if study years should be checked (census and calf proportion data must be within the same study years as the event data)
Examples
if (FALSE) { # \dontrun{
# When all data sets are present
data <- bpt_check_data(
event = event_data,
location = location_data,
census = census_data,
proportion_calf = proportion_calf_data,
complete = TRUE,
join = TRUE,
check_study_years = TRUE
)
event_data <- data$event
location_data <- data$location
# To check only a single data set
data_1 <- bpt_check_data(location = location_data)
data_2 <- bpt_check_data(event = event_data)
data_3 <- bpt_check_data(census = census_data)
data_4 <- bpt_check_data(proportion_calf = proportion_calf_data)
# Should error, as `complete = TRUE` requires all 4 data sets be provided
try(event <- bpt_check_data(event = event_data, complete = TRUE))
} # }