The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
library(predictrace)
#> Thank you for using predictrace!
#> To acknowledge our work, please cite the package:
#> Kaplan, J (2023). predictrace: Predict the Race and Gender of a Given Name Using Census and Social Security Administration Data. Version 2.0.1. URL: https://github.com/jacobkap/predictrace, https://jacobkap.github.io/predictrace/.The goal of predictrace is to predict the race of a
surname or first name and the gender of a first name. This package uses
U.S. Census data which says how many people of each race has a certain
surname. For first name data, this package uses data from Tzioumis
(2018). From this we can predict which race is mostly likely to have
that surname or first name. The possible races are American Indian,
Asian, Black, Hispanic, White, or two or more races. For the gender of
first names, this package uses data from the United States Social
Security Administration (SSA) that tells how many people of a given name
are female and how many are male (no other genders are included). I use
this to determine the proportion of each gender a name is, and use the
gender with the higher proportion as the most likely gender for that
name. Please note that the Census data on the race of first names is far
smaller than the SSA data on the gender of first names, so you will
match far fewer first names to race than to gender.
Full citation for the Tzioumis data: Tzioumis, Konstantinos (2018) Demographic aspects of first names, Scientific Data, 5:180025 [dx.doi.org/10.1038/sdata.2018.25].
To get the race of a surname, the only required parameter in
predict_race() is name which is the surname
you want to find the race of. Please note that this parameter only
accepts surnames, including both first and last name will result in not
finding a match in the Census data. This function returns the name you
input, the named matched through Census data, and likely race of that
name, and the probability that the name is of each race.
predict_race("Washington")
#> name match_name likely_race probability_american_indian
#> 1 Washington washington black 0.0066
#> probability_asian probability_black probability_hispanic probability_white
#> 1 0.0028 0.8865 0.0202 0.0517
#> probability_2races
#> 1 0.0323This function accepts a single string or a vector of strings.
predict_race(c("Washington", "Franklin", "Lincoln"))
#> name match_name likely_race probability_american_indian
#> 1 Washington washington black 0.0066
#> 2 Franklin franklin white 0.0085
#> 3 Lincoln lincoln white 0.0373
#> probability_asian probability_black probability_hispanic probability_white
#> 1 0.0028 0.8865 0.0202 0.0517
#> 2 0.0050 0.3828 0.0222 0.5577
#> 3 0.0125 0.1421 0.0215 0.7615
#> probability_2races
#> 1 0.0323
#> 2 0.0238
#> 3 0.0250If you only want the most likely race and not the individual
probabilities of each race, set the parameter probability
to FALSE.
To get the race of a first name, you again use
predict_race() but now set the parameter
surname to FALSE. This returns the exact same results as
above, but now only works for first names (you may still get a match of
a name if you don’t set the parameter to FALSE but that is simply
because some first names are also last names. The race results will
likely be incorrect.).
predict_race("sarah", surname = FALSE)
#> name match_name likely_race probability_american_indian probability_asian
#> 1 sarah sarah white 0.0014 0.0208
#> probability_black probability_hispanic probability_white probability_2races
#> 1 0.0175 0.0189 0.9397 0.0017This function accepts a single string or a vector of strings.
predict_race(c("sarah", "jaime", "jon", "bao"), surname = FALSE)
#> name match_name likely_race probability_american_indian probability_asian
#> 1 sarah sarah white 0.0014 0.0208
#> 2 jaime jaime hispanic 0.0013 0.0493
#> 3 jon jon white 0.0014 0.0190
#> 4 bao bao asian 0.0090 0.9640
#> probability_black probability_hispanic probability_white probability_2races
#> 1 0.0175 0.0189 0.9397 0.0017
#> 2 0.0045 0.4933 0.4497 0.0019
#> 3 0.0073 0.0100 0.9616 0.0007
#> 4 0.0000 0.0000 0.0180 0.0090If you only want the most likely race and not the individual
probabilities of each race, set the parameter probability
to FALSE.
To get the gender of a first name you use the
predict_gender() function and the only required parameter
in predict_gender() is name which is the first
name you want to find the gender of. This function returns the name you
input, the named matched through SSA data, and likely gender of that
name, and the probability that the name is female or male.
predict_gender("tyrion")
#> name match_name likely_gender probability_female probability_male
#> 1 tyrion tyrion male 0.0115894 0.9884106predict_gender(c("tyrion", "jaime", "jon", "sansa", "arya", "cersei"))
#> name match_name likely_gender probability_female probability_male
#> 1 tyrion tyrion male 0.011589404 0.9884106
#> 2 jaime jaime male 0.420397758 0.5796022
#> 3 jon jon male 0.007450144 0.9925499
#> 4 sansa sansa female 1.000000000 0.0000000
#> 5 arya arya female 0.892700886 0.1072991
#> 6 cersei cersei female 1.000000000 0.0000000If you only want the most likely gender and not the individual
probabilities of each gender, set the parameter probability
to FALSE.
predict_gender(c("tyrion", "jaime", "jon", "sansa", "arya", "cersei"), probability = FALSE)
#> name match_name likely_gender
#> 1 tyrion tyrion male
#> 2 jaime jaime male
#> 3 jon jon male
#> 4 sansa sansa female
#> 5 arya arya female
#> 6 cersei cersei femaleIn cases where there is no match in the data, it will return NA.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.