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My DF has two columns, start_time and member_casual. I am looking to see what percent of members and casuals started within each hour in R.

I do not have any idea where to start.

This is my first time using dput; please let me know if there is too much data.

structure(list(start_time = structure(c(55320, 86160, 71340, 
68760, 38340, 59580, 43080, 60480, 39600, 65100, 56640, 65100, 
32880, 83160, 64740, 75420, 62340, 61620, 20160, 37260, 64980, 
62820, 69420, 54540, 43200, 57300, 58560, 44460, 65820, 48240, 
29160, 41100, 83640, 69840, 44100, 29460, 62700, 71100, 27780, 
48240, 35280, 840, 39480, 27000, 64140, 48300, 28080, 61800, 
59880, 45420, 49860, 39180, 38580, 31320, 72660, 20100, 30480, 
64140, 62280, 56280, 29700, 56820, 30180, 64260, 33780, 37920, 
69780, 27240, 40440, 72180, 34800, 72780, 28080, 52500, 82200, 
28500, 60120, 60780, 54780, 58560, 62220, 59700, 68220, 50580, 
63060, 59220, 56580, 39720, 52800, 52080, 63960, 63540, 70500, 
69420, 82560, 58500, 53880, 48120, 29700, 62760), class = c("hms", 
"difftime"), units = "secs"), member_casual = c("member", "member", 
"casual", "casual", "member", "casual", "member", "member", "member", 
"member", "member", "member", "member", "casual", "member", "member", 
"casual", "member", "member", "casual", "casual", "member", "member", 
"casual", "casual", "member", "casual", "member", "member", "casual", 
"casual", "casual", "casual", "member", "casual", "member", "casual", 
"casual", "casual", "casual", "casual", "casual", "casual", "casual", 
"casual", "member", "casual", "member", "member", "casual", "casual", 
"casual", "member", "member", "member", "casual", "member", "casual", 
"member", "casual", "member", "casual", "member", "casual", "member", 
"member", "casual", "member", "member", "member", "member", "member", 
"member", "member", "member", "casual", "member", "member", "member", 
"member", "member", "member", "member", "member", "member", "member", 
"member", "member", "member", "member", "member", "member", "member", 
"casual", "casual", "casual", "casual", "casual", "member", "member"
)), row.names = c(NA, -100L), class = c("tbl_df", "tbl", "data.frame"
))
Vinícius Félix
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Joshua Rowsom
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  • You might get an idea of where to start here: https://datacornering.com/calculate-the-percentage-by-a-group-in-r-dplyr/ and https://stackoverflow.com/questions/29549731/finding-percentage-in-a-sub-group-using-group-by-and-summarise – Skaqqs Sep 27 '21 at 20:04
  • Thank you for the links. I have read both, and know I know. – Joshua Rowsom Sep 28 '21 at 18:08

1 Answers1

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library(dplyr)
library(lubridate)

df %>% 
  count(hour = hour(start_time), member_casual) %>% 
  group_by(hour) %>% 
  mutate(p = 100*n/sum(n))

# A tibble: 34 x 4
# Groups:   hour [18]
    hour member_casual     n     p
   <int> <chr>         <int> <dbl>
 1     0 casual            1 100  
 2     5 casual            1  50  
 3     5 member            1  50  
 4     7 casual            4  66.7
 5     7 member            2  33.3
 6     8 casual            1  14.3
 7     8 member            6  85.7
 8     9 casual            1  25  
 9     9 member            3  75  
10    10 casual            3  50  
# ... with 24 more rows
Vinícius Félix
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  • Thank you so much for showing me. Between your showing me and the links provided by @Skaqqs, I have a clear understanding of how this works. – Joshua Rowsom Sep 28 '21 at 18:12