R/logbook_measure_control.R
logbook_measure_control.RdThe purpose of the logbook_measure_control function is to provide a table of data that contains an inconsistency between the total number of individuals measured per sample and the sum of individuals per sample, species and size class
logbook_measure_control(dataframe1, dataframe2, output)data.frame expected. Csv or output of the function data_extraction, which must be done before using the logbook_measure_control () function.
data.frame expected. Csv or output of the function data_extraction, which must be done before using the logbook_measure_control () function.
character expected.Kind of expected output. You can choose between "message", "report" or "logical".
The function returns a character with output is "message", a data.frame with output is "report", a logical with output is "logical"
The input dataframe must contain all these columns for the function to work :
samplespecies_id
samplespecies_measuredcount
sample_id
samplespeciesmeasure_id
samplespeciesmeasure_count
samplespecies_id
#Sample 1 and 2 are ok,
#Sample 3 has different count,
#Sample 4 has sample species measure count is missing in dataframe2,
#Sample 5 has sample species measured count is missing in dataframe1
dataframe1 <- data.frame(samplespecies_id = c("1", "2", "3", "4", "5", "6"),
samplespecies_measuredcount = c(4, 6, 15, 6, 7, NA),
sample_id = c("1", "1", "2", "3", "4", "5"))
dataframe2 <- data.frame(samplespeciesmeasure_id = c("1", "2", "3", "4", "5", "6"),
samplespeciesmeasure_count = c(10, 10, 5, 3, 2, 8),
samplespecies_id = c("1", "3", "3", "4", "4", "6"))
logbook_measure_control(dataframe1, dataframe2, output = "report")
#> sample_id logical sum_measuredcount sum_count
#> 1 1 TRUE 10 10
#> 2 2 TRUE 15 15
#> 3 3 FALSE 6 5
#> 4 4 FALSE 7 NA
#> 5 5 FALSE NA 8