hi this may be a basic filter question, but my goal is to essentially remove rows that meet BOTH of the following two conditions:
dataframe %>%
filter(animal != "cat & !is.na(animal_numbers))
unfortunately, with that statement rows where animal != cat OR rows where !is.na(animal_numbers) are being removed. I want to only remove rows if both meet this condition. does this make sense? thank you!!
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
mtcars %>% filter(cyl != 8 & !is.na(drat))
#> mpg cyl disp hp drat wt qsec vs am gear carb
#> Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
#> Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
#> Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
#> Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
#> Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
#> Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
#> Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
#> Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
#> Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
#> Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
#> Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
#> Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
#> Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
#> Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
#> Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
#> Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
#> Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
#> Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2
Created on 2022-09-23 by the reprex package (v2.0.1)
I am looking for ways to keep "cat" in a row if the "animal_numbers" has a value and not NA though
thank you
thank u sir.
structure(list(animal = c("dog", "dog", "mouse", "cat", "dog",
"cat"), animal_numbers = c(4, 3, 21, 32, NA, 21)), row.names = c(NA,
-6L), class = c("tbl_df", "tbl", "data.frame"))
in that example I copy and paste, only row 5 and 9 should be removed, since it meets both condition. animal is not "cat". and animal_numbers is NA
There is no row 9, but it appears you want to remove all animal_number rows with NA except for cats.
DF <- structure(list(animal = c(
"dog", "dog", "mouse", "cat", "dog",
"cat"
), animal_numbers = c(4, 3, 21, 32, NA, 21)), row.names = c(
NA,
-6L
), class = c("tbl_df", "tbl", "data.frame"))
# introduce a case in which cat is NA
DF[6,2] <- NA
DF[-which(DF[1] != "cat" & is.na(DF[2])),]
#> # A tibble: 5 × 2
#> animal animal_numbers
#> <chr> <dbl>
#> 1 dog 4
#> 2 dog 3
#> 3 mouse 21
#> 4 cat 32
#> 5 cat NA
The logic is easier in {base} in this case.
Keep rows where animal_numbers is not NA or animal is "cat"? As usual, cats get a free pass.
library(tidyverse)
DF <- structure(list(animal = c(
"dog", "dog", "mouse", "cat", "dog",
"cat"
), animal_numbers = c(4, 3, 21, 32, NA, 21)), row.names = c(
NA,
-6L
), class = c("tbl_df", "tbl", "data.frame"))
# introduce a case in which cat is NA
DF[6,2] <- NA
DF |> filter(animal == "cat" | !is.na(animal_numbers))
#> # A tibble: 5 × 2
#> animal animal_numbers
#> <chr> <dbl>
#> 1 dog 4
#> 2 dog 3
#> 3 mouse 21
#> 4 cat 32
#> 5 cat NA
Created on 2022-09-23 with reprex v2.0.2
I want to remove any instance where animal is "cat" and animal_numbers" is " NA" for a given row
I just want the filter to include both conditions must be a thing for a given row to be removed
DF |> filter(animal == "cat" | !is.na(animal_numbers))
#> # A tibble: 5 × 2
#> animal animal_numbers
#> <chr> <dbl>
#> 1 dog 4
#> 2 dog 3
#> 3 mouse 21
#> 4 cat 32
#> 5 cat NA
#> 6 dog NA
#> 7 dog NA
in the example above.. I only want row 5 gone. sorry I have not been clear.
I want a row with "cat' in animals gone if it also has "NA" in animal numbers.
what I want:
#> animal animal_numbers
#> <chr> <dbl>
#> 1 dog 4
#> 2 dog 3
#> 3 mouse 21
#> 4 cat 32
#> 5 dog NA
#> 6 dog NA
thank you all so much!!
Is this what you want?
library(tidyverse)
DF <- structure(list(animal = c(
"dog", "dog", "mouse", "cat", "dog",
"cat"
), animal_numbers = c(4, 3, 21, 32, NA, 21)), row.names = c(
NA,
-6L
), class = c("tbl_df", "tbl", "data.frame"))
# introduce a case in which cat is NA
DF[6,2] <- NA
DF
#> # A tibble: 6 × 2
#> animal animal_numbers
#> <chr> <dbl>
#> 1 dog 4
#> 2 dog 3
#> 3 mouse 21
#> 4 cat 32
#> 5 dog NA
#> 6 cat NA
DF |> filter(animal != "cat" | !is.na(animal_numbers))
#> # A tibble: 5 × 2
#> animal animal_numbers
#> <chr> <dbl>
#> 1 dog 4
#> 2 dog 3
#> 3 mouse 21
#> 4 cat 32
#> 5 dog NA
Created on 2022-09-23 with reprex v2.0.2
it is. I am so dumb. I made that way more complicated./ thank you.
The logic of "and" and "or" when filtering is not easy. Using "or" instead of "and" it takes just one TRUE to be kept. All animals other than cat have at least one TRUE and will be kept. Cats will get a FALSE for the first part and those with an NA for the second get another FALSE and will be dropped.
See section 5.2.2 of R for Data Science for logical operators and filtering:
Of course, in hindsight the clearest solution would have been to just drop any row with animal = cat AND animal_numbers that is NA. From R for Data Science, De Morgan's Law is !(x & y) is the same as (!x | !y). A useful thing to remember.
library(tidyverse)
DF <- structure(list(animal = c(
"dog", "dog", "mouse", "cat", "dog",
"cat"
), animal_numbers = c(4, 3, 21, 32, NA, 21)), row.names = c(
NA,
-6L
), class = c("tbl_df", "tbl", "data.frame"))
# introduce a case in which cat is NA
DF[6,2] <- NA
DF |> filter(!(animal == "cat" & is.na(animal_numbers)))
#> # A tibble: 5 × 2
#> animal animal_numbers
#> <chr> <dbl>
#> 1 dog 4
#> 2 dog 3
#> 3 mouse 21
#> 4 cat 32
#> 5 dog NA
Created on 2022-09-23 with reprex v2.0.2
This topic was automatically closed 21 days after the last reply. New replies are no longer allowed.
If you have a query related to it or one of the replies, start a new topic and refer back with a link.