Software Open Access
Nicholas Tierney; cregouby; Maëlle Salmon; Nic Crane; Sean Hughes; Mara Averick; tierneyn; Noam Ross; Anthony Raborn; Carson Sievert; Jeroen Ooms; Jim Hester; Matthias Grenié; Romain François; John Muschelli
vis_value()
for visualising all values in a dataset. It rescales values to be between 0 and 1. See #100vis_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.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()
.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)abbreviate_vars()
function to assist with abbreviating data names (#140)vis_miss()
is now rounding to integers - for more accurate representation of missingness summaries please use the naniar
R package.gather_
(#141)vis_value()
displayed constant values as NA values (#128) - these constant values are now shown as 1.vis_expect
would reorder columns (#133), fixed in #143 by @muschellij2.cli
internally for error messages.Name | Size | |
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ropensci/visdat-v0.6.0.zip
md5:7b3786c00e561bf1b65e602fcfcdd58f |
12.8 MB | Download |
All versions | This version | |
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Data volume | 500.4 MB | 12.8 MB |
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