Fix to ensure that ordered factors can be used as grouping variables or as inputs to survey_count and survey_tally (#92, thanks for reporting @szimmer & @walkerke & for fixing @bschneidr).
Fix to ensure that numeric values can be used in grouping variables (#78 & #74, thanks for reporting @tzoltak & fix @bschneidr)
Some improvements for dplyr 1.0 (#79) transmute() now works (thanks for reporting @caayala), summarise()’s .groups argument is respected, and multi-row returns to summarise() work. (Unfortunately the new across() function isn’t quite supported in summarise() yet, it will hopefully come soon)
unweighted now evaluates in the right context and so will provide correct error when an incorrectly interpolated function is used (#70, thanks for reporting @tlmcmurry)
filter_at works now, (#57, thanks for reporting @dcaseykc & helping @bschneidr).
Fix for upcoming version of tibble (#72).
filtering on grouped survey designs now works correctly (#54, thanks for reporting @dcaseykc)
Added function pull (#63, thanks @dcaseykc)
df parameter now set to be degrees of freedom of survey for quantiles and variance to match other functions.
Updated tests to work with upcoming version of survey (#66).
Small update to quasiquotation syntax inside unweighted to improve consistency with recent rlang updates (#54).
Added functions survey_tally() and survey_count() (#53)
New functions survey_var and survey_sd to calculate population variance and standard deviaton.
Computation of standard errors in all survey_ functions can be suppressed by setting vartype=NULL (#45, thanks @tzoltak).
Fixed an issue where you’d get an error when summarize components returned different lengths of data - usually when factor levels were not present in the data (#49).
Removed references to MonetDBLite since it has been removed from CRAN.
Small updates to replace soft-deprecated dplyr functions with their tibble and tidyselect equivalents (#52, thanks @bschneidr).
survey_mean/survey_total allow deff="replace" like their survey package forbearers. (#46, thanks @mandes95)
Fixes for new release of dplyr
Add warning to explain that design effects cannot be calculated on proportions. (#39, thanks @mlaviolet)
Remove dependency on stringr in tests and add DBI to suggests so that test dependencies are correctly specified (#40, thanks CRAN!)
When converting from a survey db-backed survey to a srvyr one srvyr now tries to capture the updates you’ve already sent. If dbplyr can convert the function, then it will bring the update. If it can’t it will warn you (#35).
Small bug fixes, mostly having to do with CRAN checks, running on CI services, or for upstream rev dep checks.
srvyr now uses tidy evaluation from rlang. The “underscore” functions have been soft deprecated in favor of quosure splicing. See dplyr’s vignette “programming” for more details. In almost all cases, the old syntax will still work, with one exception: the standard evaluation function as_survey_twophase_() had to be changed slightly so that the entire list is inside quotation.
Datbase support has been rewritten. It should be faster now and doesn’t require a unique identifier. You also can now convert survey db-backed surveys to srvyr with as_survey.
srvyr now has a pkgdown site, check it out at http://gdfe.co/srvyr
Added support for dplyr mutate_at/_if/_all and summarize_at/_if/_all for srvyr surveys.
Fixed a few bugs introduced with dplyr 0.6. This version of srvyr will work with both old versions of dplyr and 0.6, but may be full of warnings if you update dplyr. Full support for the new dplyr is coming soon.
Fixed a problem with confidence levels not being passed into quantiles
Added deff parameter to survey_mean(), survey_total() and survey_median(), and a df parameter to those functions and survey_quantile() / survey_median().
summarize and mutate match dplyr’s behavior when arguments aren’t named (uses dplyr::auto_name())
New function cascade summarizes groups, and cascades to create summary statistics of groups of groups.
Fixed a bug for confidence intervals for survey_total() on groups.
Fixed some issues with the upcoming version of dplyr.