skimr 2.1.3

MINOR IMPROVEMENTS

skimr 2.1.2

MINOR IMPROVEMENTS

BUG FIXES

skimr 2.1.1 (2020-04-15)

MINOR IMPROVEMENTS

skimr 2.1.0 (2020-01-10)

NEW FEATURES

We’ve made to_long() generic, supporting a more intuitive interface.

Thanks @sethlatimer for suggesting this feature.

BUG FIXES

skimr 2.0.1 (2019-11-23)

BUG FIXES

Address failed build in CRAN due to lack of UTF-8 support in some platforms.

skimr 2.0.0 (2019-11-12)

Welcome to skimr V2

V2 is a complete rewrite of skimr, incorporating all of the great feedback the developers have received over the last year. A big thank you goes to @GShotwell, @akraemer007, @puterleat, @tonyfischetti, @Nowosad, @rgayler, @jrosen48, @randomgambit, @elben10, @koliii, @AndreaPi, @rubenarslan, @GegznaV, @svraka, @dpprdan and to our ROpenSci reviewers @jenniferthompson and @jimhester for all of the great support and feedback over the last year. We couldn’t have done this without you.

For most users using skimr will not change in terms of visual outputs. However for users who use skimr outputs as part of a larger workflow the differences are substantial.

Breaking changes

The skim_df

We’ve changed the way data is represented within skimr to closer match expectations. It is now wide by default. This makes piping statistics much simpler

skim(iris) %>%
  dplyr::filter(numeric.sd > 1)

This means that the old reshaping functions skim_to_wide() and skim_to_list() are deprecated. The latter is replaced with a reshaping function called partition() that breaks a skim_df into a list by data type. Similarly, yank() gets a specific data type from the skim_df. to_long() gets you data that is closest to the format in the old API.

As the above example suggests, columns of summary statistics are prefixed by skim_type. That is, statistics from numeric columns all begin numeric., those for factors all begin factor., and so on.

Rendering

We’ve deprecated support for pander() and our kable() method. Instead, we now support knitr through the knit_print() API. This is much more seamless than before. Having a skim_df as the final object in a code chunk should produce nice results in the majority of RMarkdown formats.

Customizing and extending

We’ve deprecated the previous approach customization. We no longer use skim_format() and skim_with() no longer depends on a global state. Instead skim_with() is now a function factory. Customization creates a new skimming function.

my_skim <- skim_with(numeric = sfl(mad = mad))

The fundamental tool for customization is the sfl object, a skimmer function list. It is used within skim_with() and also within our new API for adding default functions for new data types, the generic get_skimmers().

Most of the options set in skim_format are now either in function arguments or print arguments. The former can be updated using skim_with, the latter in a call to print(). In RMarkdown documents, you can change the number of displayed digits by adding the skimr_digits option to your code chunk.

OTHER NEW FEATURES

BUG FIXES

MINOR IMPROVEMENTS

skimr 1.0.6 (2019-05-27)

BUG FIXES

skimr 1.0.5 (2019-01-05)

This is likely to be the last release of skimr version 1. Version 2 has major changes to the API. Users should review and prepare for those changes now.

BUG FIXES

skimr 1.0.4 (2018-01-12)

This is likely to be the last release of skimr version 1. Version 2 has major changes to the API. Users should review and prepare for those changes now.

BUG FIXES

skimr 1.0.3 (2018-06-06)

NEW FEATURES

BUG FIXES

skimr 1.0.2 (2018-04-04)

NEW FEATURES

MAJOR CHANGES

MINOR IMPROVEMENTS

BUG FIXES

skimr 1.0.1 (2018-01-09)

NEW FEATURES

MAJOR CHANGES

MINOR IMPROVEMENTS

BUG FIXES

skimr 0.92 (2017-12-19)

MAJOR CHANGES

NEW FEATURES

skimr 0.91 (2017-10-14)

NEW FEATURES

MINOR IMPROVEMENTS

BUG FIXES

skimr 0.900 (2017-07-16)

BUG FIXES