Data + Science

9/27/2014
Using the Gender Package in R: Part 1 - Getting Started

There is a package in R called gender and it can be used to determine the gender of a first name. The package is very easy to use and is really powerful. I am planning a few posts related to this package, so I wanted to begin the series of posts with some basic R code to get things started. Below is the basic setup.


# install the gender package if you need to
install.packages('gender')
# NOTE - if asked to install GenderData click 1 for yes.

# load the gender package
library(gender)

# Examples

# this example returns all of the fields using Social Security Administration database from 1900 to 1990. You can adjust the dates or choose a different database.
gender("Jeff" , method = "ssa", years = c(1900, 1990))

# The "ssa" method looks up names based from the U.S. Social Security Administration baby name data. (This method is based on an implementation by Cameron Blevins.)
# The "ipums" method looks up names from the U.S. Census data in the Integrated Public Use Microdata Series. (This method was contributed by Ben Schmidt.)
# The "kantrowitz" method uses the Kantrowitz corpus of male and female names.
# The "genderize" method uses the Genderize.io <http://genderize.io/> API, which is based on "user profiles across major social networks.

# this example returns a single field of Gender, which is what we will use in the code below.
gender("Jeff" , method = "ssa", years = c(1900, 1990))$gender

Try a few different look ups. For example, search "Morgan" using 1860 to 1950 and then run it again using 1960 to 1990. You will find that the name used to be a man's name, but in the last 50 years it has become a woman's name.

Using the code above we can import a CSV file of first names and append the gender.


# load the gender package
library(gender)

# Create Function to lookup gender using first name
workerFunc <- function(n){
  return
  cbind(n, gender(as.character(n) , method = "ssa", years = c(1900, 1990))$gender)
}

# import CSV File of first names - replace with file path of CSV file with first names
importDF <- read.csv("D:\\Dropbox\\Data Mining\\R\\Top 100 names.csv") 
firstname <- as.vector(unlist(importDF))

# if you have a short list or don't have a CSV to try then you can build your own list - simply uncomment
# firstname <- c("Elizabeth", "Mary", "Jeff", "John", "Morgan", "Helen", "Tim", "Diane", "Patricia")

# Run gender lookup and append to list of first names and report processing time
Sys.time()
results <- lapply(firstname, workerFunc)
Sys.time()

# Put final results together in data frame
indx <- sapply(res, length)
results <- as.data.frame(do.call(rbind,lapply(res, `length<-`, max(indx))))
colnames(results) <- c("name", "gender")

# Save results as a CSV file - Replace with file path to save file
write.csv(results,"D:/Dropbox/Data Mining/R/Top 100 names with Gender.csv")

# NOTE - The file path uses / and not \ for Windows. \\ also works as an alternative.

I hope you find this information useful. If you have any questions feel free to email me at Jeff@DataPlusScience.com

Jeffrey A. Shaffer

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