How to summarize a unique value of a numeric variable within dplyr

January 30, 2022

Data:

structure(list(Month_Name = c("September", "September", "September", 
"September", "September", "September", "September", "September", 
"September", "September", "September", "September", "September", 
"September", "September", "September", "September", "September", 
"September", "September", "September", "September", "September", 
"September", "September", "September", "September", "September", 
"September", "September", "October", "October", "October", "October", 
"October", "October", "October", "October", "October", "October", 
"October", "October", "October", "October", "October", "October", 
"October", "October", "October", "October", "October", "October", 
"October", "October", "October", "October", "October", "October", 
"October", "October", "October", "November", "November", "November", 
"November", "November", "November", "November", "November", "November", 
"November", "November", "November", "November", "November", "November", 
"November", "November", "November", "November", "November", "November", 
"November", "November", "November", "November", "November", "November", 
"November", "November", "November", "December", "December", "December", 
"December", "December", "December", "December", "December", "December", 
"December", "December", "December", "December", "December", "December", 
"December", "December", "December", "December", "December", "December", 
"December", "December", "December", "December", "December", "December", 
"December", "December", "December", "December", "January", "January", 
"January", "January", "January", "January", "January", "January", 
"January", "January", "January", "January", "January", "January", 
"January", "January", "January", "January", "January", "January", 
"January", "January", "January", "January", "January", "January", 
"January", "January", "January", "January"), Mins_Work = c(435L, 
350L, 145L, 135L, 15L, 60L, 60L, 390L, 395L, 395L, 315L, 80L, 
580L, 175L, 545L, 230L, 435L, 370L, 255L, 515L, 330L, 65L, 115L, 
550L, 420L, 45L, 266L, 196L, 198L, 220L, 17L, 382L, 0L, 180L, 
343L, 207L, 263L, 332L, 0L, 0L, 259L, 417L, 282L, 685L, 517L, 
111L, 64L, 466L, 499L, 460L, 269L, 300L, 427L, 301L, 436L, 342L, 
229L, 379L, 102L, 146L, NA, 94L, 345L, 73L, 204L, 512L, 113L, 
135L, 458L, 493L, 552L, 108L, 335L, 395L, 508L, 546L, 396L, 159L, 
325L, 747L, 650L, 377L, 461L, 669L, 186L, 220L, 410L, 708L, 409L, 
515L, 413L, 166L, 451L, 660L, 177L, 192L, 191L, 461L, 637L, 297L, 
601L, 586L, 270L, 479L, 0L, 480L, 397L, 174L, 111L, 0L, 610L, 
332L, 345L, 423L, 160L, 611L, 0L, 345L, 550L, 324L, 427L, 505L, 
632L, 560L, 230L, 495L, 235L, 522L, 654L, 465L, 377L, 260L, 572L, 
612L, 594L, 624L, 237L, 0L, 38L, 409L, 634L, 292L, 706L, 399L, 
568L, 0L, 694L, 298L, 616L, 553L, 581L, 423L)), row.names = c(NA, 
-152L), class = "data.frame")

Problem:

Not sure why, but I’m having difficulties figuring out how to use dplyr right now to get what I want out of summarize this time. Basically, I have a grouped sum, mean, and per week table for minutes of work:

library(tidyverse)

work_slack %>% 
  group_by(Month_Name) %>% 
  summarize(Sum_Work = round((sum(Mins_Work,na.rm = T))/60),
            Mean_Work_Day = round(mean(Mins_Work,na.rm = T)/60),
            Per_Week_Sum = round((sum(Mins_Work,na.rm = T))/60/4))%>% 
  arrange(desc(Sum_Work))

Which gives me these values so far when I add them into a gt table:

However, I wanna find a way to summarize how many times there was no work done. I’m having trouble trying to figure out which command within dplyr can get me this. The best idea ive had so far is this, which doesnt work:

work_slack %>% 
  group_by(Month_Name) %>% 
  summarize(Sum_Work = round((sum(Mins_Work,na.rm = T))/60),
            Mean_Work_Day = round(mean(Mins_Work,na.rm = T)/60),
            Per_Week_Sum = round((sum(Mins_Work,na.rm = T))/60/4),
            Breaks = count(Mins_Work = 0))%>% 
  arrange(desc(Sum_Work))

Basically, what I need is a way to summarize the number of unique times per month Mins_Work equaled zero. Hopefully that makes sense.

>Solution :

Is this what you need:

df %>% 
  group_by(Month_Name) %>% 
  summarize(Sum_Work_0 = sum(Mins_Work==0,na.rm = T))
# A tibble: 5 × 2
  Month_Name Sum_Work_0
  <chr>           <int>
1 December            3
2 January             2
3 November            0
4 October             3
5 September           0