#Defining the new labels
c.label<-c('loan.date', 'mat.date', 'term',
'repay.date', 'district', 'borrower', 'city',
'state', 'ABA', 'type.credit', 'i.rate',
'comm.real', 'consumer', 'treasury',
'municipal', 'corp', 'mbs.cmo',
#Changing the column names
I also like to add a few additional variables when I see a potential need when I can. At this point the files are individual, and adding the quarter variable might be helpful. Sure I could write a loop to create the new column based on the month of the date, but I like to keep things as simple as possible. Why add complexity when there is no reason. I used the ABA to define the length of the data set because it did not have any missing values, while others did. The new column name is qtr, and the function rep() is used to repeat the quarter number the length of the column ABA.