Is there an easy way to filter my data frame so that any rows after and including a row that follows some condition are filtered out? The issue here is that I want it to be robust enough to handle a case where that condition is not met, in which the whole data frame will be returned. Check out my examples below if that sounds confusing:
library(dplyr)
## Works
mtcars %>%
as_tibble() %>%
filter(between(row_number(), 1, which(mpg == 17.8)))
#> # A tibble: 11 x 11
#> mpg cyl disp hp drat wt qsec vs am gear carb
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
#> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
#> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
#> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1
#> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
#> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
#> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
#> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
#> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
#> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
#> 11 17.8 6 168. 123 3.92 3.44 18.9 1 0 4 4
## Doesn't work
mtcars %>%
as_tibble() %>%
filter(between(row_number(), 1, which(mpg == 30.5)))
#> Error in filter_impl(.data, quo): Evaluation error: Expecting a single value: [extent=0]..
Created on 2018-08-12 by the reprex package (v0.2.0).
You could include an ifelse statement to check whether the value is present in the dataframe. Also, you need to select the first row where the condition is verified to account for cases where the value is present more than once (in your example 21.0)
library(dplyr)
mtcars %>%
as_tibble() %>%
filter(between(row_number(), 1,ifelse(!any(mpg == 30),n(),which(mpg == 30)[1]-1)))
## returns the whole tibble
mtcars %>%
as_tibble() %>%
filter(between(row_number(), 1,ifelse(!any(mpg == 21),n(),which(mpg == 21)[1]-1)))
## Returns a tibble with 0 rows
mtcars %>%
as_tibble() %>%
filter(between(row_number(), 1,ifelse(!any(mpg == 21.4),n(),which(mpg == 21.4)[1]-1)))
## returns:
# A tibble: 3 x 11
mpg cyl disp hp drat wt qsec vs am gear carb
<dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
2 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
3 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1