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explore_col()
for simple bar plots without
aggregationyyyymm_calc()
for calculation with periods (format
yyyymm)use_data_wordle()
: data from a wordle
challangeabtest.Rmd
explore_cor()
when using
geom_points
nthread
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-*.Rmd
explain_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
seed
check_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 = 20
explain_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_n
theme_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=NULL
describe_tbl()
: add observations containing
NA
guess_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
,
na
NA
in explore()
(move code
before auto_scale
)explore_density()
with target: drop plot title
“propensity by”explore_shiny()
: use output_dir /
tempdir()
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