Investigating the wrapr let function

wrapr let.R

##### set up#######

library(dplyr)
library(wrapr)


data<-structure(list(Location = c("AreaZ", "AreaZ", "AreaZ", "AreaZ", 
                                  "AreaZ", "AreaZ", "AreaZ", "AreaZ", "AreaZ", "AreaZ", "AreaZ", 
                                  "AreaZ", "AreaZ", "AreaZ", "AreaZ", "AreaZ", "AreaZ", "AreaZ", 
                                  "AreaZ", "AreaZ", "AreaZ", "AreaZ", "AreaZ", "AreaZ", "AreaZ", 
                                  "AreaZ", "AreaZ", "AreaZ", "AreaZ", "AreaZ", "AreaZ", "AreaZ", 
                                  "AreaZ", "AreaZ", "AreaZ", "AreaZ", "AreaZ", "AreaZ", "AreaZ", 
                                  "AreaZ", "AreaZ", "AreaZ", "AreaZ", "AreaZ", "AreaZ", "AreaZ", 
                                  "AreaZ", "AreaZ", "AreaZ", "AreaZ", "AreaZ", "AreaZ", "AreaZ", 
                                  "AreaZ", "AreaZ", "AreaZ", "AreaZ", "AreaZ", "AreaZ", "AreaZ", 
                                  "AreaZ", "AreaZ", "AreaZ", "AreaZ"), Date = structure(c(14761, 
                                                                                          14791, 14822, 14853, 14883, 14914, 14944, 14975, 15006, 15034, 
                                                                                          15065, 15095, 15126, 15156, 15187, 15218, 15248, 15279, 15309, 
                                                                                          15340, 15371, 15400, 15431, 15461, 15492, 15522, 15553, 15584, 
                                                                                          15614, 15645, 15675, 15706, 15737, 15765, 15796, 15826, 15857, 
                                                                                          15887, 15918, 15949, 15979, 16010, 16040, 16071, 16102, 16130, 
                                                                                          16161, 16191, 16222, 16283, 16314, 16344, 16375, 16436, 16467, 
                                                                                          16495, 16526, 16556, 16587, 16617, 16648, 16679, 16709, 16770
                                  ), class = "Date"), y = c(6, 3, 8, 18, 18, 2, 15, 11, 24, 11, 
                                                            13, 13, 11, 10, 19, 5, 12, 14, 20, 3, 22, 15, 16, 24, 10, 18, 
                                                            18, 38, 15, 23, 24, 23, 27, 27, 31, 18, 20, 20, 26, 22, 19, 21, 
                                                            26, 25, 19, 19, 31, 23, 23, 21, 28, 23, 28, 35, 23, 29, 38, 22, 
                                                            25, 23, 28, 33, 31, 20)), class = "data.frame", row.names = c(NA, -64L), .Names = c("Location", "Date", "y"))

####### end of setup#############


## define functions:

NSE_median_rows <- function(df, groupvar,x,nrows=NULL) {
  #get the first rows for median calculations
  MedianRows<- df %>%
    dplyr::arrange_(.dots = lazyeval::lazy(x)) %>% 
    dplyr::group_by_(.dots = lazyeval::lazy(groupvar)) %>% 
    
    dplyr::slice_(~1:nrows)
  return(MedianRows)
}




wrapr_median_rows <- function (dframe,datecol,groupvar=NULL,colname,nrows=9) {
  
  mapping = list(COL=colname,DATES=datecol)
  if(!is.null(groupvar)) {
    wrapr::let(list(GROUPVAR= groupvar),
               dframe %>%
                 dplyr::group_by(GROUPVAR)-> dframe
    )
  }
  
  wrapr::let(mapping,
             {
               dframe %>%
                 dplyr::arrange(DATES)%>%
                 dplyr::filter(row_number(DATES) %in% c(1:nrows)) %>%
                 #dplyr::mutate(baseline = median(COL))%>%
                 dplyr::ungroup()
             })
}



  
 


####compare use####

#interactive dplyr:
interactive_data <- data %>%
  arrange(Date) %>%
  group_by(Location) %>%
  filter(row_number(Location) %in% c(1:9)) %>%
  ungroup() 



#NSE/lazyeval:
NSE_data <- NSE_median_rows(data,Location,Date,9)


##wrapr let :
wrapr_let_data <- wrapr_median_rows(data,'Date','Location','y',9)



#compare
interactive_data
NSE_data
wrapr_let_data