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View() now renders correctly inside
webR (the in-browser R that powers the ModernDive
book’s live exercises). webR has no pandoc, so a
DT::datatable() htmlwidget cannot be saved as the
self-contained HTML the cell needs (DT::saveWidget()
errors), and the auto-print path is gated by interactive()
being FALSE. In webR, View() now builds a
self-contained static HTML table and pushes it through webR’s viewer
hook, so the data displays inline instead of only printing the
explanatory message. Outside webR the DT::datatable()
behaviour is unchanged.get_regression_points() and
get_regression_summaries() now handle in-formula
transformations on either side of the model formula
(e.g. lm(log(y) ~ poly(x, 2))). LHS transforms previously
errored; they now produce a sanitized outcome column on the model’s
scale (e.g. log_mpg, log_mpg_hat). RHS
transforms no longer leak basis matrices or wrapper columns
(poly() matrix columns, scale(),
I()) into the points table; the original predictor variable
is shown instead. The .rownames column is no longer leaked
into the output.get_regression_table(),
get_regression_points(), and
get_regression_summaries() now accept glm()
model objects (resolves issue #20). For
glm() models, get_regression_points() returns
fitted values and residuals on the response scale (e.g. probabilities
for logistic regression). get_regression_summaries()
returns a glm-shaped summary (mse, rmse,
deviance, null_deviance, aic,
bic, log_lik, df_residual,
df_null, nobs) — R² columns are not included
since they don’t apply to glm. get_regression_table() gains
an exponentiate argument (default FALSE) for
returning odds/rate ratios for log/logit-link models.get_regression_table() is now applied to the tidy output’s
term column rather than model$coefficients
names, which avoids breaking confint.glm’s
profile-likelihood refits.@docType package tag from
R/moderndive.R (resolves issue #133).
The "_PACKAGE" sentinel was already in place, so the
moderndive-package alias is generated correctly.pennies_resamples so the replicate
column is correctly numbered 1..35 instead of being uniformly
1 (resolves issue #130).
The bug was an ungroup() missing in the
data-raw/process_data_sets.R pipeline, so
mutate(replicate = 1:n()) ran per-group on a single-row
nested tibble. The dataset has been regenerated; row count and structure
are otherwise unchanged.View() wrapper (resolves issue #99). In
an interactive R session it behaves identically to
utils::View(). In non-interactive contexts (R Markdown,
Quarto, scripts) where utils::View() typically errors, it
instead renders an interactive DT::datatable() inline so
documents can still knit/render. DT is now in
Imports. A short packageStartupMessage() is
emitted only on non-interactive attach to explain the override;
interactive sessions see no extra message. Attaching
moderndive masks utils::View. For large data
frames the inline DT::datatable() is slow and warns that
the data is too big for a client-side table, so in non-interactive
contexts View() now shows a random sample
of n rows (default 1000) when x
is larger, emitting a message that says so. New arguments n
(sample size), full = FALSE (set TRUE to show
every row), seed (reproducible sample), and
quiet = FALSE (silence the message) control this; the
sample never disturbs the caller’s RNG stream, and the interactive
utils::View() path is unchanged.moderndive datasets
instead of base R / ggplot2 ones. View(),
get_correlation(), get_regression_table(),
get_regression_points(),
get_regression_summaries(),
plot_3d_regression(), and the package-level overview now
use un_member_states_2024 (with
life_expectancy_2022 ~ gdp_per_capita-style models).
geom_categorical_model() now uses evals
(score ~ rank) instead of ggplot2::mpg
(hwy ~ drv)._pkgdown.yml: site url: now includes the
https:// scheme so pkgdown::check_pkgdown()
matches it against the URL listed in DESCRIPTION.README: added descriptive alt text to the
hex-sticker image.get_correlation() now accepts multiple right-hand-side
variables in the formula (e.g. mpg ~ hp + cyl + wt)
(resolves issue #29). The
default output is a long tibble with one row per predictor; pass
wide = TRUE for one column per predictor. Single-RHS
behavior is unchanged. A one-time message points users to
corrr::correlate() if they want a full pairwise correlation
matrix; suppress it with quiet = TRUE.plot_3d_regression() function for interactive 3D
scatterplots with a fitted regression plane (resolves issue #27). Pass
a formula z ~ x + y and the function returns a
[plotly][plotly::plotly] htmlwidget. plotly is
in Suggests; install it with
install.packages("plotly") to use this function.un_member_states_2024 data for upcoming
ModernDive v2 updatesspotify_by_genre data for upcoming ModernDive v2
updatestidy_summary() function to summarize data frame
columns for upcoming ModernDive v2 updatesold_faithful_2024 data for upcoming ModernDive v2
updatescoffee_quality data for upcoming ModernDive v2
updatesalmonds_sample data for upcoming ModernDive v2
updatesalmonds_bowl and almonds_sample_100
data for upcoming ModernDive v2 updates to Inference chaptersearly_january_2023_weather and
envoy_flights data for upcoming ModernDive v2 updates
derived from data in the nycflights23 packagebroom reverse dependency issue https://github.com/moderndive/moderndive/issues/128early_january_weather consisting of January
subset of nycflights13::weathercoffee_quality dataset: 1340 samples of coffee tested for
their quality levelamazon_books dataset: sample of books available for
purchase on Amazon.comipf_lifts consisting of international power lifting
resultsbabies on maternal smoking and infant healthev_charging: information from 3,395 high resolution
electric vehicle charging sessions.ma_traffic_2020_vs_2019 consisting of collisions
information sourced from reports produced by the Massachusetts Traffic
Data Management System.mass_traffic_2020 consisting of traffic data for 13
Massachusetts countiesmario_kart_auction datasetavocados consisting of avocado prices dataset downloaded
from the Hass Avocado Board website in May of 2018.saratoga_houses random sample of 1057 houses taken
from full Saratoga Housing Data.alaska_flights consisting of Alaska Airlines
subset of nycflights13::flightsconf.level argument to
get_regression_table() inherited from
broom::tidy.lm()vignettes/paper.mdpkgdown and covr issues, defragged
documentation.vignettes/why-moderndive.Rmd main
vignettegeom_parallel_slopes() with new arguments:
fullrange=TRUE to draw regression lines over the
entire support of the x-axis (by @wjhopper)level to set different level of confidence interval
shading (by @echasnovski)geom_categorical_model() for
visualizing regression models with one categorical explanatory/predictor
variable (by @wjhopper)gg_parallel_slopes()
directing users to use geom_parallel_slopes() instead (by
@mariumtapal)geom_parallel_slopes() geom extension to
ggplot2 package to plot parallel slopes regression models
with one numerical and one categorical variable (this is not possible
using ggplot2::geom_smooth()). Note this renders
gg_parallel_slopes() function added in v0.3.0
obsolete.geom_parallel_slopes() to “Why
moderndive?” vignettepennies_resamples data frame columnsget_correlation() now:
dplyr::group_by() groupingna.rm = TRUE
argument or by passing standard
stats:cor(use = "complete.obs") argument via
...gg_parallel_slopes(). In the future we hope to
define a new ggplot2 geom.moderndive?” vignetteget_regression_points() to return
a column that identifies the observational units/rowsDD_vs_SB: Dunkin Donuts and Starbucks in Eastern
Massachusetts data collected by @DelaneyMoranpromotions: tibble version of
openintro::gender.discrimination used to illustrate
permutation test.MA_schools: Relationship between SAT scores and
socio-economic status for Massachusetts high schools.mythbusters_yawn: Data from study on Mythbusters
show on whether yawning ispromotions_shuffled: one instance of
promotions with gender permuted/shuffledpennies_sample sample of 40 pennies from
pennies has been renamed orig_pennies_sample.
New pennies_sample consists of 50 pennies sampled from bank
in Northampton, MA, USA on 2019/2/1.pennies_resamples: 35 bootstrap resamples of new
pennies_samplemovies_genre: random sample of 32 action and 36
romance movies from ggplot2movies::moviesassertive::assert() codehouse_prices$date from dttm
(date-time) to date per R4DS comment
on using simplest data type possibleUpdated package for:
evals and house_prices datasets and
updated get_regression_table() and
get_regression_points() functions.Details:
get_correlation() function to omit
$ syntax and return a data frameinfer::rep_sample_n() instead of our own defined
version, as this function is now included in
inferevals, house_prices,
tactile_prop_red, pennies_sample and
mythbusters_yawn datasetsget_regression_summaries()newdata argument to
get_regression_points(). When:
newdata,
output it as well as residual (See Issue 17).residualtidyverse from Depends, Imports, or
SuggestsFixed broken url in ?bowl_samples
get_regression_* functions meant for novice
R users/regression fitters that process regression model outputspennies: 800 pennies to be treated as a population from
which to simulate sampling a numerical variable from (year
of minting)bowl: Bowl of 2400 balls of which 900 are red to be
treated as a population from which to simulate sampling a categorical
variable from (color). Also known as the urn sampling
framework .bowl_samples: data from tactile version of sampling
from bowl done in class: 10 groups sampled n=50 balls from
and counted the number red [ADD MODERNDIVE LINK]These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.