For example, I have this tibble:
nationality Other
[1,] White 1 ------> I want to add
[2,] Mexican 0
[3,] American 0
[4,] Asian 1 -------> I want to add
[5,] af 1 -------> I want to add
[6,] American 0
I want to somehow sum up the values in Other and create it's own tibble:
Other
[1,] 3
I tried using sum(), but it gives me
Error in FUN(X[[i]], ...) :
only defined on a data frame with all numeric variables
In addition to that, tally() gives me this, it counts the number of rows in the column:
n
1 88
Here is the code:
natgroups3 <- ibtclean %>% select(nationality) %>%mutate(Other = ifelse(str_detect(nationality, "af|White|Asian|white|Middle-Eastern"), yes = 1, no = 0)) %>% drop_na()
Try to use the tidyverse library. I prepared a sample code that recreates a tibble d with your structure and calculates the target tibble c with the count of rows with the column other equals to 1.
library(tidyverse)
d <- tribble(~nationality, ~other, 'White', 0, 'Mexican', 1, 'Amrican', 0, 'Asian', 1, 'af', 1)
d
c <- d %>% count(other) %>% filter(other == 1) %>% select('Other' = n)
c
You can also select the column other and calculate its sum with the following code (according to your business need)
library(tidyverse)
d <- tribble(~nationality, ~other, 'White', 0, 'Mexican', 1, 'Amrican', 0, 'Asian', 1, 'af', 1)
d
c <- d %>% select(other) %>% summarise('Other'=sum(other))
c
Both of the code snippets produce the following result
# A tibble: 5 x 2
nationality other
<chr> <dbl>
1 White 0
2 Mexican 1
3 Amrican 0
4 Asian 1
5 af 1
# A tibble: 1 x 1
Other
<dbl>
1 3
I hope these snippets solve your issue
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