I'm going to give you a small example of how to do this task, as long as you are able to read your data as a data frame, you can do something like this.
library(tidyverse)
# Sample data / you have to replace this by your actual dataset
sample <- data.frame(stringsAsFactors = FALSE,
ethnicity = c("[African]", "[African] & [Latino/Hispanic] & [Mexican]",
"[African] & [Middle Eastern/North African]",
"[American Indian/Alaska Native]",
"[American Indian/Alaska Native] & [Black or African American]"))
sample %>%
separate_rows(ethnicity, sep = "\\s&\\s") %>%
mutate(ethnicity = str_remove_all(ethnicity, "[\\[\\]]")) %>%
count(ethnicity)
#> # A tibble: 6 x 2
#> ethnicity n
#> <chr> <int>
#> 1 African 3
#> 2 American Indian/Alaska Native 2
#> 3 Black or African American 1
#> 4 Latino/Hispanic 1
#> 5 Mexican 1
#> 6 Middle Eastern/North African 1
Created on 2019-10-08 by the reprex package (v0.3.0.9000)