I have a list of different types of masks and I would like to categorise them into those that are N95, surgical, cloth or other.
df<-data.frame(mask_type=
c("Surgical Mask (3M 1800)",
"N95 FFR (Wilson 1105N) (2x 3mm leaks)",
"N95 FFR (San Huei United Company 1895N) (2x 3mm leaks)",
"Surgical Mask (Primed PG4-1073) (2x 3mm leaks)",
"Surgical Mask (3M 1800) (2x 3mm leaks)",
"N95 FFR (Wilson 1105N) (4x 3mm leaks)",
"Cloth FFR (San Huei United Company 1895N) (4x 3mm leaks)",
"Cloth Mask (Primed PG4-1073) (4x 3mm leaks)")
This works that filters the masks but doesn't create an "other" column. Am I far away do you think?
require(dplyr) require(tidyr)
df %>%
mutate(TYPE=stringr::str_detect(mask_type,"N95 | surgical | cloth")) %>%
filter(TYPE=TRUE) %>%
select(mask_type)
Read more here: https://stackoverflow.com/questions/66275681/r-cut-equivalent-for-strings
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