Data overview

First, we are going to analyze the types of variables that we have in the dataset. For that, we can use the class function, which tells us whether a variable is a number, a character, or a matrix. For example, the class of the identifying number of a bank ID_RSSD can be obtained as follows:

class(Model_database$ID_RSSD)

 ## [1] "integer"

This function indicates that this variable is a number without decimals.

We can calculate the same information for all the variables and store it using the following code:

 classes<-as.data.frame(sapply(Model_database, class))
 classes<-cbind(colnames(Model_database),classes)
 colnames(classes)<-c("variable","class")

With sapply, calculate iteratively the class function on the dataset. Then, combine the name of variables with the class in only a data frame, and, finally, rename the resulting dataset...