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()