gender 0.6.0

• Fixes installation problems with the move away from rOpenSci
• Removes the gender_df() function, which did not work properly.

gender 0.5.4

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

gender 0.5.3

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

gender 0.5.2

• bugfix for change in the genderize.io API (#50)

gender 0.5.1

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

gender 0.5.0

• 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 Genderize.io 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

• updates to README.md as requested by CRAN

gender 0.4.2

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

gender 0.4.1

• 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

• 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

• 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

• 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

• 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