发布于 2020-01-21 23:06:17
您可以通过对location.id进行分组并对Fruit_total的总和进行过滤来完成此操作
library(tidyverse)
df %>%
  group_by(location.ID) %>%
  filter(sum(Fruit_total) != 0)收益率:
# A tibble: 22 x 5
# Groups:   location.ID [11]
   location.ID  Year plant                 treatment Fruit_total
         <dbl> <dbl> <chr>                 <chr>           <dbl>
 1           7  2019 Anaheim.Peppers.Count Control            23
 2           9  2019 Anaheim.Peppers.Count Control             3
 3          15  2019 Anaheim.Peppers.Count Control             0
 4          23  2019 Anaheim.Peppers.Count Control             1
 5          38  2019 Anaheim.Peppers.Count Control             8
 6          41  2019 Anaheim.Peppers.Count Control             1
 7          42  2019 Anaheim.Peppers.Count Control            12
 8          43  2019 Anaheim.Peppers.Count Control             7
 9          45  2019 Anaheim.Peppers.Count Control             5
10          49  2019 Anaheim.Peppers.Count Control            13
# ... with 12 more rowshttps://stackoverflow.com/questions/59843627
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