gender 0.5.4 2020-05-15

  • update dependencies, and fix for dplyr 1.0.0
  • update URL for rOpenSci CRAN-like repository

gender 0.5.3 2019-11-09

  • improvements to documentation
  • improvements to testing when genderdata is available

gender 0.5.2 2018-03-07

  • bugfix for change in the API (#50)

gender 0.5.1 2015-09-04

  • bugfix for some users who cannot install the genderdata package as binary

gender 0.5.0 2015-08-22

  • genderdata package is installed using install.packages() from the rOpenSci package repository instead of using install_github().
  • all functions always return data frames
  • general performance improvements
  • calls to API no longer fail if the name does not exist
  • new function gender_df() efficiently applies gender() to data frames
  • add North Atlantic Population Project dataset for six European countries

gender 0.4.3 2014-12-24

  • updates to as requested by CRAN

gender 0.4.2 2014-12-03

  • bugfix: Kantrowitz method is now case-insensitive
  • updates to title and descriptions according to CRAN policy

gender 0.4.1 2014-09-29

  • tests and vignettes run without depending on the genderdata package
  • users will be prompted to install the genderdata package from GitHub the first time that it is necessary
  • added a demo mode with a minimal dataset

gender 0.4 Unreleased

  • data is now external to the gender package and is available in the genderdata package.
  • genderdata package can be installed with a new function

gender 0.3 Unreleased

  • rewrote all functions to take only character vectors, not data frames, but provided instructions on how to use with data frames
  • wrote a vignette describing the data sources and explaining the historical methodology behind this package

gender 0.2 Unreleased

  • implemented an ipums method that predicts gender before 1930 using U.S. Census data from IPUMS (contributed by Benjamin Schmidt).
  • upgraded dependency on dplyr to 0.2.

gender 0.1 Unreleased

  • function gender implements gender lookup for names and data frames
  • implemented finding gender by using the Kantrowitz names corpus
  • implemented finding gender by using the national Social Security Administration data for names and dates of birth