CODEWITHSUNDEEP
r
seungwoolee
seungwoolee

Reputation: 3

how i can conditional sum in R

I want conditional sum in R. I have dataframe with 6 column.

I want sum breeding count about equal condition(same [year, month, kind, gender, type]) and age <= 20 and changed row's age is 20.

My hope : age = 3,4,5, ...., 20 --> age = 20 (18 row to 1 row) group by other column and sum breeding count. So data(have age = 20)'s breeding count column contain age=3~20 breeding count

 year  month kind  gender   age breeding_count type    
  <chr> <dbl> <chr> <chr>  <dbl>          <dbl> <chr>   
1 2022     12 한우  암         3          65043 breeding
2 2022     12 한우  암         4          31740 breeding
3 2022     12 한우  암         5          36680 breeding
4 2022     12 한우  암         6          42295 breeding
5 2022     12 한우  암         7          49243 breeding
6 2022     12 한우  암         8          58414 breeding

'''

I expect all age<= 20 to age == 20 group by year, month, kind, gender, type Like this,

 A tibble: 22 × 8
   year  month kind  gender   age breeding_count slaughter_count   rate
   <chr> <dbl> <chr> <chr>  <dbl>          <dbl>           <dbl>  <dbl>
 1 2014      1 젖소  젖소      20           7249               9 0.124 
 2 2014      1 젖소  젖소      21           5416               5 0.0922
 3 2014      1 젖소  젖소      22           5498               5 0.0909
 4 2014      1 젖소  젖소      23           7431               9 0.121 
 5 2014      1 젖소  젖소      24           6979              20 0.286 
 6 2014      1 젖소  젖소      25           7372              25 0.338 
 7 2014      1 젖소  젖소      26           7457              22 0.294 
 8 2014      1 젖소  젖소      27           4823              18 0.372 
 9 2014      1 젖소  젖소      28           4471              23 0.512 
10 2014      1 젖소  젖소      29           6312              22 0.347

Upvotes: 0

Views: 51

Answers (1)

Kra.P
Kra.P

Reputation: 15123

You may try

library(dplyr)

df
  year month kind gender age breeding_count     type
1 2022    12 한우     암   3          65043 breeding
2 2022    12 한우     암   4          31740 breeding
3 2022    12 한우     암   5          36680 breeding
4 2022    12 한우     암   6          42295 breeding
5 2022    12 한우     암   7          49243 breeding
6 2022    12 한우     암   8          58414 breeding

df %>%
  mutate(age = ifelse(age <= 20, 20, age)) %>%
  group_by(year, month, kind, gender, age, type) %>%
  summarise(breeding_count = sum(breeding_count))

  year month kind  gender   age type     breeding_count
  <int> <int> <chr> <chr>  <dbl> <chr>             <int>
1  2022    12 한우  암        20 breeding         283415

Upvotes: 1

Related Questions