You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
vis_value() for visualising all values in a dataset. It rescales values to be between 0 and 1. See #100
vis_binary() for visualising datasets with binary values - similar to vis_value(), but just for binary data (0, 1, NA). See #125. Thank you to Trish Gilholm for her suggested use case for this.
Implemented facetting in vis_dat() and vis_cor(), and vis_miss() see (#78). The next release will implement facetting for vis_value(), vis_binary(), vis_compare(), vis_expect(), and vis_guess().
Implemented data methods for plots with data_vis_dat(), data_vis_cor(), and data_vis_miss() see (#78).
vis_dat()vis_miss() and vis_guess() now render missing values in list-columns (@cregouby#138)
Added abbreviate_vars() function to assist with abbreviating data names (#140)
Percentage missing in columns for vis_miss() is now rounding to integers - for more accurate representation of missingness summaries please use the naniar R package.
A new vignette on customising colour palettes in visdat, "Customising colour palettes in visdat".