The goal of genero is to ease data cleaning when it comes to augment
data with “gender” or sex assigned at birth. It uses lists of common
names in Spanish and Portuguese with frequent gender assignments.
Therefore it has many limitations and should be used with care. This
package is provided to study large populations and not individual
records.
For better methods for estimating gender in English and other languages please use the gender package
This package does not take into account non-binary gender identification as of this moment. We apologize for that, we expect to have more sensical approaches in the near future. Any ideas or feedback on how to make it more inclusive are more than welcome.
Use this package with care and make sure it is not used for any type of discrimination.
Make sure to check the results provided by genero by other means, like
manual inspection.
You can install the released version of genero from CRAN (SOOOOOON) with:
install.packages("genero")And the development version with
devtools::install_github("datasketch/genero")This is a basic example which shows you how to estimate gender from names:
library(genero)
names <- c("Juan", "Pablo", "Camila", "Mariana")
genero(names)
#> [1] "male" "male" "female" "female"For Portuguese use the lang = "pt" parameter. Don’t like the results
English? Me neither, simply provide a named vector to rename results.
names <- c("Gabriela", "Ina","Luiz", "Edson")
genero(names, lang = "pt", result_as = c(male = "Homem", female = "Mulher"))
#> [1] "Mulher" "Mulher" "Homem" "Homem"It also works with data frames and composed names, and even last names.
The genero tries to guess whats the column with the names, if it finds
two columns with names, the first one will be
used.
names <- c("Juan Álvarez", "Juan Maria García", "Maria José", "José María", "María Rodríguez")
age <- c(23, 43, 56, 67, 24)
d <- data.frame(names = names, age = age, stringsAsFactors = FALSE)
genero(d)
#> Guessed names column: names
#> names names_gender_guess age
#> 1 Juan Álvarez male 23
#> 2 Juan Maria García male 43
#> 3 Maria José female 56
#> 4 José María male 67
#> 5 María Rodríguez female 24