I’m planning to release ggplot2 2.2.0 in early November. In preparation, I’d like to announce that a release candidate is now available: version 2.1.0.9001. Please try it out, and file an issue on GitHub if you discover any problems. I hope we can find and fix any major issues before the official release.

Install the pre-release version with:

# install.packages("devtools")
devtools::install_github("hadley/ggplot2")

If you discover a major bug that breaks your plots, please file a minimal reprex, and then roll back to the released version with:

install.packages("ggplot2")

ggplot2 2.2.0 will be a relatively major release including:

The majority of this work was carried out by Thomas Pedersen, who I was lucky to have as my “ggplot2 intern” this summer. Make sure to check out other visualisation packages: ggraph, ggforce, and tweenr.

Subtitles and captions

Thanks to Bob Rudis, you can now add subtitles and captions:

ggplot(mpg, aes(displ, hwy)) +
  geom_point(aes(color = class)) +
  geom_smooth(se = FALSE, method = "loess") +
  labs(
    title = "Fuel efficiency generally decreases with engine size",
    subtitle = "Two seaters (sports cars) are an exception because of their light weight",
    caption = "Data from fueleconomy.gov"
  )

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These are controlled by the theme settings plot.subtitle and plot.caption.

The plot title is now aligned to the left by default. To return to the previous centering, use theme(plot.title = element_text(hjust = 0.5)).

Facets

The facet and layout implementation has been moved to ggproto and received a large rewrite and refactoring. This will allow others to create their own facetting systems, as descrbied in the Extending ggplot2 vignette. Along with the rewrite a number of features and improvements has been added, most notably:

ggplot(diamonds, aes(carat, price)) +
  geom_hex(bins = 20) +
  facet_wrap(~cut_number(depth, 6))

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ggplot(mpg, aes(displ, hwy)) +
  geom_point() +
  facet_wrap(~class)

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ggplot(mpg, aes(displ, hwy)) +
  geom_point() +
  scale_x_continuous(position = "top") +
  scale_y_continuous(position = "right")

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ggplot(mpg, aes(displ, hwy)) +
  geom_point() +
  scale_y_continuous(
    "mpg (US)",
    sec.axis = sec_axis(~ . * 1.20, name = "mpg (UK)")
  )

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ggplot(mpg, aes(displ, hwy)) +
  geom_point() +
  facet_wrap(~ drv, strip.position = "bottom") +
  theme(
    strip.placement = "outside",
    strip.background = element_blank(),
    strip.text = element_text(face = "bold")
  ) +
  xlab(NULL)

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Theming

arrow <- arrow(length = unit(0.4, "cm"), type = "closed")

ggplot(mpg, aes(displ, hwy)) +
  geom_point() +
  theme_minimal() +
  theme(
    axis.line = element_line(arrow = arrow)
  )

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ggplot(mpg, aes(displ, hwy, shape = drv, colour = fl)) +
  geom_point() +
  theme(
    legend.justification = "top",
    legend.box.margin = margin(3, 3, 3, 3, "mm"),
    legend.box.background = element_rect(colour = "grey50")
  )

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Stacking bars

position_stack() and position_fill() now stack values in the reverse order of the grouping, which makes the default stack order match the legend.

avg_price <- diamonds %>%
  group_by(cut, color) %>%
  summarise(price = mean(price)) %>%
  ungroup() %>%
  mutate(price_rel = price - mean(price))

ggplot(avg_price) +
  geom_col(aes(x = cut, y = price, fill = color))

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(Note also the new geom_col() which is short-hand for geom_bar(stat = "identity"), contributed by Bob Rudis.)

Additionally, you can now stack negative values:

ggplot(avg_price) +
  geom_col(aes(x = cut, y = price_rel, fill = color))

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The overall ordering cannot necessarily be matched in the presence of negative values, but the ordering on either side of the x-axis will match.

If you want to stack in the opposite order, try forcats::fct_rev():

ggplot(avg_price) +
  geom_col(aes(x = cut, y = price, fill = fct_rev(color)))

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