CODEWITHSUNDEEP
rpipereadability
Stupid_Intern
Stupid_Intern

Reputation: 3450

How to pass two inputs to %>% operator in R

Originally I have this code which I am trying to simplify and improve readability using %>% operator.

#Get Sunday's from 2018-01-01 till today
d = seq(as.Date("2018-01-01"),Sys.Date()+365,by='day')
HolidayList = data.frame(Holidays=d[weekdays(d)=='Sunday'])

#Get Alternate saturdays 2nd and 4th
d = seq(as.Date("2018-01-01"),Sys.Date()+365,by='day')
saturdayList = d[weekdays(d)=='Saturday']
altSaturdayList = lapply(split(saturdayList, format(saturdayList, "%Y-%m")), function(x)
  na.omit(x[c(2,4)]))
altSaturdayList = as.data.frame(altSaturdayList)
altSaturdayList = gather(altSaturdayList)
altSaturdayList = subset(altSaturdayList,select = c(value))
HolidayList = rbind(HolidayList, setNames(altSaturdayList, "Holidays"))
HolidayList = rbind(HolidayList, setNames(as.data.frame(as.Date("2018-11-06")), "Holidays"))
HolidayList = unique(HolidayList)
HolidayList = arrange(HolidayList,Holidays)
rm(d)
rm(saturdayList)
rm(altSaturdayList)

I don't want to store the intermediate variables that's why I thought pipe operator would be a good choice but I am not able to reproduce the result.

Here's what I tried

HolidayList = saturdayList %>% 
    data.frame(lapply(split(saturdayList, format(saturdayList, "%Y-%m")), function(x)
    na.omit(x[c(2,4)]))) %>% 
    subset(gather(altSaturdayList),select = c(value)) %>% 
    rbind(HolidayList, setNames(altSaturdayList, "Holidays")) %>% 
    rbind(HolidayList, setNames(as.data.frame(as.Date("2018-11-06")), "Holidays")) %>% 
    arrange(unique(HolidayList),Holidays)

Holidays dataframe has dates to which I am trying to bind and add new dates.

How do I take output of each step and put as input in next line without creating new variables?

Please explain the steps so that I can understand the process to simplify above code.

Upvotes: 0

Views: 323

Answers (1)

Ronak Shah
Ronak Shah

Reputation: 388862

There are functions which are specially designed for pipe operators in tidyverse. Those functions are well suited for using pipe operators instead of using base R operators and trying to fit them in pipe. You can still use base R functions in pipe but it is more convenient to use them using tidyverse tools.

library(tidyverse)

temp <- map_dfr(split(saturdayList,format(saturdayList, "%Y-%m")), ~ .[c(2, 4)]) %>%
    gather(key, Holidays) %>%
    select(Holidays) %>%
    bind_rows(HolidayList) %>%
    add_row(Holidays = as.Date("2018-11-06")) %>%
    unique() %>%
    na.omit() %>%
    arrange(Holidays) 

temp

#   Holidays  
#   <date>    
# 1 2018-01-07
# 2 2018-01-13
# 3 2018-01-14
# 4 2018-01-21
# 5 2018-01-27
# 6 2018-01-28
# 7 2018-02-04
# 8 2018-02-10
# 9 2018-02-11
#10 2018-02-18
# … with 160 more rows

To confirm if output from both of them is the same we can convert temp to data frame and then compare to HolidayList in your final step.

identical(data.frame(temp), HolidayList)
#[1] TRUE

Upvotes: 2

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