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I have this data frame:

df <- data.frame (ID  = c(1:20),
                  Ethnicity = c(rep(c("White", "Asian", "Black", "Hispanic", "Other"), times=20/5)),
                  Age = c(1:20),
                  Set = rep(c(1,2,3,4), times=20/4)
)

Is there a way to filter out all the rows where Ethnicity is NOT Asian using the filter function in R? Maybe something similar to -filter?

Thanks!

jo_
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    Try: `dplyr::filter(df, Ethnicity != "Asian")` – PaulS May 13 '22 at 18:08
  • Clarity: *"`filter` function in R"* might be interpreted as `base::filter`, which is far different from `dplyr::filter`; that particular name-collision is a source of problem for many new to R who are learning primarily/solely dplyr syntax. – r2evans May 13 '22 at 18:11
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    From this question it seems it would be useful for you to go through some R tutorials to include "conditionals" (`==`, `!=`, `<`, `<=`, etc), as what you're asking is common to everywhere any conditional can be used (regardless of base/dplyr/data.table). While not a tutorial, simply [`?Comparison`](https://stat.ethz.ch/R-manual/R-devel/library/base/html/Comparison.html) (also `?==`, `?!=`, etc) as well as [`?Ops`](https://stat.ethz.ch/R-manual/R-devel/library/base/html/groupGeneric.html) might be informative. – r2evans May 13 '22 at 18:15

1 Answers1

1

In addition to PaulS's tidyverse/dplyr solution, here's how you can filter out rows using base R.

df[df$Ethnicity != "Asian",]

#>    ID Ethnicity Age Set
#> 1   1     White   1   1
#> 3   3     Black   3   3
#> 4   4  Hispanic   4   4
#> 5   5     Other   5   1
#> 6   6     White   6   2
#> 8   8     Black   8   4
#> 9   9  Hispanic   9   1
#> 10 10     Other  10   2
#> 11 11     White  11   3
#> 13 13     Black  13   1
#> 14 14  Hispanic  14   2
#> 15 15     Other  15   3
#> 16 16     White  16   4
#> 18 18     Black  18   2
#> 19 19  Hispanic  19   3
#> 20 20     Other  20   4
Aron Strandberg
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