rfilterdplyrtidyverseremove-if

Two condition filtering and removing Zero Values

I have a simple dataframe of counts in a growing pepper experiment. I want to remove observations where both treatment's[(Control and Covered) Fruit_total are equal to zero. I tried filter but I can only handle one variable at a time. Any advice?

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Solution

  • You can accomplish this by grouping on location.id and filtering for the sum of Fruit_total:

    library(tidyverse)

df %>%
  group_by(location.ID) %>%
  filter(sum(Fruit_total) != 0)

    Yields:

    # 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 rows