Mutate multiple split variable columns

Usage

mmc(data, lib_name_list, list_cut, openright = FALSE, digits = 0)

Arguments

data: a dataframe contain continuous type data column.
lib_name_list: a series of continuous variables for classification, concatenated using character methods.
list_cut: data split points used for grouping in multiple continuous variables,these split points need to be packed into a list.Warning：The order of checking lib_name_list and list_cut before starting analysis is the same.
openright: default openright= FALSE,the data interval is in the form of left opening and right closing,such as [1,2).When openright= TRUE, the data interval is in the form of left closing and right opening.
digits: defines the number of decimal places for the return label.

Value

adds multiple user-specified classified data columns to the data frame.

Examples

if (FALSE) {
data(data_med)

lab_wider = data_med$lab  %>%
  tr(.,c("test_date"),"dat") %>%
  group_by(patient_id,lab_name) %>%
  arrange(test_date) %>%  slice_tail(n =1) %>%  ungroup() %>%
  select(patient_id,lab_name ,lab_va) %>%
  tr(.,c("lab_va"),"num") %>%
  spread(lab_name,lab_va) %>%  distinct()

names(lab_wider)

HbA1c <- c(0,6.5,7.0,8.0,9.0,Inf)
TC <- c(0,5.2,6.2,Inf)
LDL <- c(0,3.4,4.1,Inf)
HDL <- c(0,1.0,Inf)
TG <- c(0,1.7,2.3,Inf)
WBC <- c(0,4,10,Inf)

## keep only the columns related to the analysis
lib_name_list <- names(lab_wider)[-1]
## this step need to adjust the order of list subsets in name_list order
list_cut <- list(HbA1c,HDL,LDL,TC,TG,WBC)

cut_dataframe = mmc(lab_wider,lib_name_list,list_cut,digits=2)
}