explore_col() for simple bar plots without
aggregationyyyymm_calc() for calculation with periods (format
yyyymm)use_data_wordle(): data from a wordle
challangeabtest.Rmdexplore_cor() when using
geom_pointsnthread to
explain_xgboost(). (#45)interact(). (#47)create_data_abtest().explore() &
abtest() functions.get_color()explore() from title to subtitle.
(#48)explore()subtitle.color parameter for explore(),
explore_*(), report()bins parameter to
target_explore_num()mix_color() with one color as parameter generates
colors from light to darktarget_explore_num() bar positioning changes from max
to mean valueexplore_*.Rmd to
explore-*.Rmdexplain_xgboost() (#42)drop_var_by_names() (#43)drop_var_not_numeric() (#43)drop_var_low_variance() (#43)drop_var_no_variance() (#43)drop_var_with_na() (#43)drop_obs_with_na() (#43)drop_obs_if() (#43)mix_color()show_color()create_data_esoteric()create_data_empty() has no longer a parameter
seedcheck_vec_low_variance() (internal helper
function)get_nrow()
(#41)explain_logreg() and explain_forest(), you
will receive a prompt to install these packages in interactive sessions.
(#2 1, @olivroy)explain_forest().predict_target().create_data_newsletter().use_data_beer() and
use_data_starwars() functions (#20, #23)abtest() now supports numeric target (t-test).abtest_targetpct() with count data (parameter
n).abtest() and explore() can now run without
data (shiny app). If no data are provided,
palmerpenguins::penguins is used. (#25)create_data_() use_data_*() return data
sets as tibble.fct_explicit_na() (forcats >= 1.0.0) and
use linewidth for ggplot2 (>= 3.4.0) (deprecated) (#15,
@olivroy)add_var_random_01() creates variable of type
integertarget_name & factorise_target
parameter to more create_data_*()target1_prob parameter to more
create_data_*()create_data_*()abtest()explore_tbl()explore() median if NA
valuesexplore() (no error if data contains
NA)%>% in vignettes (compatibility R
< 4.1) (#6)create_data_unfair()create_data_app() gains a screen_size
argument.create_data_app()report() >100 variablesexplore_count()explore_tbl()explore_density() plotcreate_data_churn()add_var_random_moon()%>% to
|>create_notebook_explore()create_data_x()add_var_x()create_data_*() functionsadd_var_*() functionsexplain_tree(): set default
minsplit = 20explain_tree(): set prior probabilitiesexplore() and report():
targetpct as alternative to split
parameterbalance_target(): add parameter seedcreate_data_x()dwh_*() functions are no longer included in
{explore} Alternative: source https://github.com/rolkra/dwhcreate_fake_data()create_random_data()add_random_var()get_var_buckets()total_fig_height(): parameters
var_name_target, var_name_ntheme_light() into
individual theme() so that set_theme
works.explain_tree() gains a weights
parameter.minsplit for count-dataweight_target()plot_legend_targetpct()explore_bar(): NA in plotexplore_count(): convert target into factorexplore_count(): add default title (cat name)explore_count(): add parameter numeric, max_cat,
max_target_catexplain_tree(): convert character variables into
factors (count data)explain_tree(): parameter out (“plot” | “model”)explain_logreg(): parameter out (“tibble” |
“model”)vignette("explore_titanic"): change to tibblevignette("explore_mtcars"): add explanationsvignette("explore_penguins")vignette("explore_titanic") (count
data)explore_count(): plot count() outputn for count data:
explore(), explore_all(),
explore_tbl(), explain_tree(),
report(), describe(),
describe_cat(), describe_num(),
describe_tbl(), total_fig_height()explore_tree(): default value for minsplit = 10% of
obsexplore_cor(): use geom_point() for small
datasetsexplore_shiny(): use browseURL() with
parameter browser=NULLdescribe_tbl(): add observations containing
NAguess_cat_num(): parameter description (optional)count_pct(): no renaming of variables.Maintenance update:
Maintenance update:
... in description (PR#16223, see https://bugs.r-project.org/show_bug.cgi?id=16223)explore_bar(): add parameter numericdescribe_all() returns a tibbledescribe_all(): column ‘variable’ is character (not
factor)report() split = TRUE as defaultrescale01()rescale01 to
clean_var()count_pct()out='tibble' to describe_cat()explore_targetpct()format_num_auto() without bracketsreport() fix automatic file extension .htmlsimplify_text()simplify_text to
clean_var()Prepare for new dplyr 0.8.4 (#2, @romainfrancois)
explore_tbl() for dplyr 0.8.4describe_num() with default digits=6describe_cat() bugfix variable with all NAdescribe_all() bugfix variable with all NAexplain_tree() bugfix dataframe with 0 rowsdescribe() text output (RMarkdown)explore() now checks if data is a data.frameInteractive data exploration now accept categorical and numerical targets (next to a binary target).
explain_tree(): target can be bin/num/catexplain_tree(): add parameter max_target_catexplore_shiny(): target can be bin/num/catformat_num_auto()total_fig_height() replaces the now deprecated
get_nrow().explore_cor()describe()title to
explore_density()nvar to
total_fig_height()Many functions now accept categorical and numerical targets (next to
a binary target). If you want to force which geom is used for
visualisation, you can use explore_bar() and
explore_density(). New function explore_tbl()
to visualise a dataframe/table (type of variables, number of NA, …)
explore_bar()explore_density() now using correct tidy eval, target
cat > 2 possibletarget_explore_cat() now using correct tidy evaltarget_explore_num() now using correct tidy evaladd plot_var_info() - plots a info-text to a variable
as ggplot obj.plot_var_info() used in explore/explore_all if
plot_var_info() used if explore empty datamax_cat in explore_bar(),
explore_density() and explain_tree()explore_tbl()explore_cat() &
explore_num()explore_shiny()format_num() -> format_num_kMB(),
format_num_space()format_target() -> if numeric split 0/1 by meanreport() -> default .html file extensiondescribe_tbl() -> fix target if not bindescribe(): change out=“vector” to out=“list”explore(): auto_scale,
naNA in explore() (move code
before auto_scale)explore_density() with target: drop plot title
“propensity by”explore_shiny(): use output_dir /
tempdir()