A ggplot2 Tutorial for Beautiful Plotting in R-blog version

Dongbei University of Finance & Economics

Abstract

历史虽是记录事实之书，但吾辈之探求，则为理而非事。理是概括众事的，事则是只是一事。天下事没有两件真正相同的，执应付此事的方法，以应付彼事，自然要失败。根据于包含众事之理，以应付诸事，则不至于此了。然而理是因事而见的，舍事而求理，无有是处。所以我们求学，不能不顾事实，亦不能死记事实。

1 加载经常用的R包

library(pacman)
# 读数据
p_load(readxl,writexl,data.table,openxlsx,haven,rvest)

# 数据探索
p_load(tidyverse,DT,skimr,DataExplorer,explore,vtable,stringr,kableExtra,lubridate)

# 模型
p_load(grf,glmnet,caret,tidytext,fpp2,forecast,car,tseries,hdm,tidymodels,broom)

# 可视化
p_load(patchwork,ggrepel,ggcorrplot,gghighlight,ggthemes,shiny)

# 其它常用包
p_load(magrittr,listviewer,devtools,here,janitor,reticulate,jsonlite)

2 Preparation

• {ggplot2}, part of the {tidyverse} package collection
• {dplyr} for data wrangling
• {tibble} for modern data frames
• {tidyr} for data cleaning
• {forcats} for handling factors
• {colorspace} for manipulating colors
• {corrr} for calculating correlation matrices
• {cowplot} for composing ggplots
• {ggdark} for themes and inverting colors
• {ggforce} for sina plots and other cool stuff
• {ggrepel} for nice text labeling
• {ggridges} for ridge plots
• {ggsci} for nice color palettes
• {ggtext} for advanced text rendering
• {ggthemes} for additional themes
• {grid} for creating graphical objects
• {gridExtra} for additional functions for “grid” graphics
• {patchwork} for multi-panel plots
• {rcartocolor} for great color palettes
• {scico} for perceptional uniform palettes
• {showtext} for custom fonts
• {shiny} for interactive apps
• a number of packages for interactive visualizations
  • {charter}
  • {echarts4r}
  • {ggiraph}
  • {highcharter}
  • {plotly}

3 The Dataset

chic <- read.csv("https://raw.githubusercontent.com/Z3tt/R-Tutorials/master/ggplot2/chicago-nmmaps.csv")
chic %>% head()

chic %>% skimr::skim()

Table 3.1: Data summary

Name	Piped data
Number of rows	1461
Number of columns	10
_______________________
Column type frequency:
character	3
numeric	7
________________________
Group variables	None

Variable type: character

skim_variable	n_missing	complete_rate	min	max	empty	n_unique	whitespace
city	0	1	4	4	0	1	0
date	0	1	10	10	0	1461	0
season	0	1	6	6	0	4	0

Variable type: numeric

skim_variable	n_missing	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
death	0	1.00	111.28	14.64	69.00	101.00	110.00	120.00	164.00	▁▇▇▂▁
temp	0	1.00	51.00	19.02	-3.00	36.00	52.00	67.00	90.00	▁▅▇▇▃
dewpoint	0	1.00	41.36	17.92	-10.38	28.10	41.20	56.25	77.10	▁▃▇▇▅
pm10	17	0.99	32.09	19.24	0.20	18.38	28.85	41.07	125.38	▇▇▂▁▁
o3	0	1.00	19.24	9.85	0.09	10.92	18.65	26.20	54.69	▆▇▆▂▁
time	0	1.00	4384.00	421.90	3654.00	4019.00	4384.00	4749.00	5114.00	▇▇▇▇▇
year	0	1.00	1998.50	1.12	1997.00	1998.00	1999.00	2000.00	2000.00	▇▇▁▇▇

head(chic)

4 The {ggplot2} Package

ggplot2 is a system for declaratively creating graphics, based on The Grammar of Graphics. You provide the data, tell ggplot2 how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details.

5 A Default ggplot

5.1 A Default ggplot

chic %<>% 
  mutate(date = ymd(date))

theme_set(theme_grey())
chic %>% 
  ggplot(aes(x = date,y = temp)) +
  geom_point() + 
  mytheme

chic %>% 
  ggplot(aes(x = date,y = temp)) +
  geom_point() + 
  geom_line() +
  mytheme

5.2 Change Properties of Geometries

chic %>% 
  ggplot(aes(x = date,y = temp)) +
  geom_point(col = "firebrick",shape = "diamond",size = 2) + 
  geom_line(col = "firebrick",linetype = "dotted",size = 0.3) +
  mytheme

6 Working with Axes

6.1 Change Axis Titles

chic %>% 
  ggplot(aes(x = date,y = temp)) +
  geom_point(col = "firebrick",shape = "diamond",size = 2) + 
  geom_line(col = "firebrick",linetype = "dotted",size = 0.3) +
  labs(x = "Year",y = "Temperature(°F)") +
  mytheme

💁 You can also add each axis title via xlab() and ylab(). Expand to see example.

expression(paste("Temperature (", degree ~ F, ")"^"(Hey, why should we use metric units?!)"))

## expression(paste("Temperature (", degree ~ F, ")"^"(Hey, why should we use metric units?!)"))

chic %>% 
  ggplot(aes(x = date,y = temp)) +
  geom_point(col = "firebrick",shape = "diamond",size = 2) + 
  geom_line(col = "firebrick",linetype = "dotted",size = 0.3) +
  labs(x = "Year",
       y = expression(paste("Temperature (", degree ~ F, ")"^"(Hey, why should we use metric units?!)")
                      )
       ) +
  mytheme

6.2 Increase Space between Axis and Axis Titles

chic %>% 
  ggplot(aes(x = date,y = temp)) +
  geom_point(col = "firebrick",shape = "diamond",size = 2) + 
  geom_line(col = "firebrick",linetype = "dotted",size = 0.3) +
  labs(x = "Year",
       y = expression(paste("Temperature (",
                            degree ~ F, 
                            ")"^"(Hey, why should we use metric units?!)")
                      )
       ) +
  theme(axis.title.x = element_text(vjust = 0, size = 15),
        axis.title.y = element_text(vjust = 2, size = 15)) +
  mytheme

chic %>% 
  ggplot(aes(x = date,y = temp)) +
  geom_point(col = "firebrick",shape = "diamond",size = 2) + 
  geom_line(col = "firebrick",linetype = "dotted",size = 0.3) +
  labs(x = "Year",
       y = expression(paste("Temperature (",
                            degree ~ F, 
                            ")"^"(Hey, why should we use metric units?!)")
                      )
       ) +
  theme(axis.title.x = element_text(margin = margin(t = 10), size = 15),
        axis.title.y = element_text(margin = margin(r = 10), size = 15)) +
  mytheme

The labels t and r within the margin() object refer to top and right, respectively. You can also specify the four margins as margin(t, r, b, l). Note that we now have to change the right margin to modify the space on the y axis, not the bottom margin.

chic %>% 
  ggplot(aes(x = date,y = temp)) +
  geom_point(col = "firebrick",shape = "diamond",size = 2) + 
  geom_line(col = "firebrick",linetype = "dotted",size = 0.3) +
  labs(x = "Year",
       y = expression(paste("Temperature (",
                            degree ~ F, 
                            ")"^"(Hey, why should we use metric units?!)")
                      )
       ) +
  theme(axis.text = element_text(family = enfont),
        axis.title.x = element_text(size = 15,
                                    color = "firebrick",
                                    face = "italic"),
        axis.title.y = element_text(size = 15,
                                    color = "firebrick",
                                    face = "italic"))

chic %>% 
  ggplot(aes(x = date,y = temp)) +
  geom_point(col = "firebrick",shape = "diamond",size = 2) + 
  geom_line(col = "firebrick",linetype = "dotted",size = 0.3) +
  labs(x = "Year",
       y = expression(paste("Temperature (",
                            degree ~ F, 
                            ")"^"(Hey, why should we use metric units?!)")
                      )
       ) +
  theme(axis.title.x = element_text(color = "sienna", size = 15),
        axis.title.y = element_text(color = "orangered", size = 15),
        text = element_text(family = enfont))

6.3 Change Aesthetics of Axis Text

chic %>% 
  ggplot(aes(x = date,y = temp)) +
  geom_point(col = "firebrick",shape = "diamond",size = 2) + 
  geom_line(col = "firebrick",linetype = "dotted",size = 0.3) +
  labs(x = "Year",
       y = expression(paste("Temperature (",
                            degree ~ F, 
                            ")"^"(Hey, why should we use metric units?!)")
                      )
       ) +
  theme(axis.text = element_text(color = "dodgerblue", size = 12),
        axis.text.x = element_text(face = "italic"),
        text = element_text(family = enfont))

Specifying an angle allows you to rotate any text elements. With hjust and vjust you can adjust the position of the text afterwards horizontally (0 = left, 1 = right) and vertically (0 = top, 1 = bottom):

6.4 Rotate Axis Text

chic %>% 
  ggplot(aes(x = date,y = temp)) +
  geom_point(col = "firebrick",shape = "diamond",size = 2) + 
  geom_line(col = "firebrick",linetype = "dotted",size = 0.3) +
  labs(x = "Year",
       y = expression(paste("Temperature (",
                            degree ~ F, 
                            ")"^"(Hey, why should we use metric units?!)")
                      )
       ) +
  theme(axis.text = element_text(color = "dodgerblue", size = 12),
        axis.text.x = element_text(face = "italic",angle = 45,hjust = 1,vjust = 1),
        text = element_text(family = enfont))

6.5 Remove Axis Text & Ticks

Remove Axis Text & Ticks: There may be rarely a reason to do so—but this is how it works:

chic %>% 
  ggplot(aes(x = date,y = temp)) +
  geom_point(col = "firebrick",shape = "diamond",size = 2) + 
  geom_line(col = "firebrick",linetype = "dotted",size = 0.3) +
  labs(x = "Year",
       y = expression(paste("Temperature (",
                            degree ~ F, 
                            ")"^"(Hey, why should we use metric units?!)")
                      )
       ) +
  theme(axis.text = element_text(color = "dodgerblue", size = 12),
        axis.text.x = element_text(face = "italic",angle = 45,hjust = 1,vjust = 1),
        text = element_text(family = enfont),
        axis.ticks.y = element_blank(),
        axis.text.y = element_blank())

💡 If you want to get rid of a theme element, the element is always element_blank().

Remove Axis Titles: We could again use theme_blank() but it is way simpler to just remove the label in the labs() (or xlab()) call:

6.6 Remove Axis Titles

chic %>% 
  ggplot(aes(x = date,y = temp)) +
  geom_point(col = "firebrick",shape = "diamond",size = 2) + 
  geom_line(col = "firebrick",linetype = "dotted",size = 0.3) +
  labs(x = "Year",
       y = expression(paste("Temperature (",
                            degree ~ F, 
                            ")"^"(Hey, why should we use metric units?!)")
                      )
       ) +
  mytheme +
  labs(x = NULL,y = "")

💡 Note that NULL removes the element (similarly to element_blank()) while empty quotes "" will keep the spacing for the axis title and simply print nothing.

6.7 Limit Axis Range

chic %>% 
  ggplot(aes(x = date,y = temp)) +
  geom_point(col = "firebrick",size = 2,shape = 1,alpha = 0.5) +
  labs(x = "Year", y = "Temperature (°F)") +
  ylim(0,50) +
  mytheme

## Warning: Removed 777 rows containing missing values (geom_point).

Alternatively you can use scale_y_continuous(limits = c(0, 50)) or coord_cartesian(ylim = c(0, 50)). The former removes all data points outside the range while the second adjusts the visible area and is similar to ylim(c(0, 50)). You may wonder: So in the end both result in the same. But not really, there is an important difference—compare the two following plots:

chic %>% 
  ggplot(aes(x = date,y = temp)) +
  geom_point(col = "firebrick",size = 2,shape = 1,alpha = 0.5) +
  scale_y_continuous(limits = c(0,50)) +
  labs(x = "Year", y = "Temperature (°F)") +
  mytheme -> p1

chic %>% 
  ggplot(aes(x = date,y = temp)) +
  geom_point(col = "firebrick",size = 2,shape = 1,alpha = 0.5) +
  coord_cartesian(ylim = c(0,50)) +
  labs(x = "Year", y = "Temperature (°F)") +
  mytheme -> p2

p1 + p2

## Warning: Removed 777 rows containing missing values (geom_point).

6.8 Force Plot to Start at Origin

Related to that, you can force R to plot the graph starting at the origin:

chic_high <- dplyr::filter(chic, temp > 25, o3 > 20)

ggplot(chic_high, aes(x = temp, y = o3)) +
  geom_point(color = "darkcyan") +
  labs(x = "Temperature higher than 25°F",
       y = "Ozone higher than 20 ppb") +
  expand_limits(x = 0, y = 0) +
  mytheme

💁 Using coord_cartesian(xlim = c(0, NA), ylim = c(0, NA)) will lead to the same result. Expand to see example.

chic_high <- dplyr::filter(chic, temp > 25, o3 > 20)

ggplot(chic_high, aes(x = temp, y = o3)) +
  geom_point(color = "darkcyan") +
  labs(x = "Temperature higher than 25°F",
       y = "Ozone higher than 20 ppb") +
  coord_cartesian(xlim = c(0, NA), ylim = c(0, NA)) +
  mytheme

But we can also force it to literally start at the origin!

ggplot(chic_high, aes(x = temp, y = o3)) +
  geom_point(color = "darkcyan") +
  labs(x = "Temperature higher than 25°F",
       y = "Ozone higher than 20 ppb") +
  expand_limits(x = 0, y = 0) +
  scale_x_continuous(expand = c(0, 0)) +
  scale_y_continuous(expand = c(0, 0)) +
  coord_cartesian(clip = "off") +
  mytheme

💡 The argument clip = "off" in any coordinate system, always starting with coord_*, allows to draw outside of the panel area.

Here, I call it to make sure that the tick marks at c(0, 0) are not cut.

For demonstrating purposes, let’s plot temperature against temperature with some random noise. The coord_equal() is a coordinate system with a specified ratio representing the number of units on the y-axis equivalent to one unit on the x-axis. The default, ratio = 1, ensures that one unit on the x-axis is the same length as one unit on the y-axis:

6.9 Axes with Same Scaling

ggplot(chic, aes(x = temp, 
                 y = temp + rnorm(nrow(chic),
                                  sd = 20))
       ) +
  geom_point(color = "sienna") +
  labs(x = "Temperature (°F)", y = "Temperature (°F) + random noise") +
  xlim(c(0, 100)) + ylim(c(0, 150)) +
  coord_fixed() +
  mytheme

## Warning: Removed 45 rows containing missing values (geom_point).

Ratios higher than one make units on the y axis longer than units on the x-axis, and vice versa:

ggplot(chic, aes(x = temp, y = temp + rnorm(nrow(chic), sd = 20))) +
  geom_point(color = "sienna") +
  labs(x = "Temperature (°F)", y = "Temperature (°F) + random noise") +
  xlim(c(0, 100)) + ylim(c(0, 150)) +
  coord_fixed(ratio = 1/5) +
  mytheme

## Warning: Removed 55 rows containing missing values (geom_point).

6.10 Use a Function to Alter Labels

ggplot(chic, aes(x = date, y = temp)) +
  geom_point(color = "firebrick") +
  labs(x = "Year", y = NULL) +
  scale_y_continuous(label = function(x) {return(paste(x, "Degrees Fahrenheit"))})  +
  mytheme

7 Working with Titles

7.1 Add a Title

Alternatively, you can use labs(). Here you can add several arguments, e.g. additionally a subtitle, a caption and a tag (as well as axis titles as shown before):

chic %>% head()

chic %>% 
  ggplot(aes(x = date,y = temp)) +
  geom_point(col = "red",size = 2) +
  geom_line(col = "red",size = 0.5) +
  ggtitle("Temperatures in Chicago") +
  mytheme

chic %>% 
  ggplot(aes(x = date,y = temp)) +
  geom_point(col = "red",size = 2) +
  geom_line(col = "red",size = 0.5) +
  labs(x = "Year",
       y = "Temperature (°F)",
       title = "Temperatures in Chicago",
       subtitle = "Seasonal pattern of daily temperatures from 1997 to 2001",
       caption = "Data: NMMAPS",
       tag = "Fig. 1") +
  mytheme

7.2 Make Title Bold & Add a Space at the Baseline

chic %>% 
  ggplot(aes(x = date,y = temp)) +
  geom_point(col = "red",size = 2) +
  geom_line(col = "red",size = 0.5) +
  labs(x = "Year",
       y = "Temperature (°F)",
       title = "Temperatures in Chicago",
       subtitle = "Seasonal pattern of daily temperatures from 1997 to 2001",
       caption = "Data: NMMAPS",
       tag = "Fig. 1") +
  theme(title = element_text(family = enfont)) +
  mytheme

7.3 Adjust Position of Titles

chic %>% 
  ggplot(aes(x = date,y = temp)) +
  geom_point(col = "red",size = 2) +
  geom_line(col = "red",size = 0.2) +
  labs(x = "Year", 
       y = "",
       title = "Temperatures in Chicago",
       caption = "Data: NMMAPS") + 
  theme(text = element_text(family = enfont),
        plot.title = element_text(hjust = 1,size = 16,face = "bold.italic"))

(
  g <- ggplot(chic, aes(x = date, y = temp)) +
    geom_point(color = "firebrick") +
    scale_y_continuous(
      label = function(x) {
        return(paste(x, "Degrees Fahrenheit"))
      }
    ) +
    labs(
      x = "Year",
      y = NULL,
      title = "Temperatures in Chicago between 1997 and 2001 in Degrees Fahrenheit",
      caption = "Data: NMMAPS"
    ) +
    theme(
      plot.title = element_text(size = 14, face = "bold.italic"),
      plot.caption = element_text(hjust = 0)
    ) +
    mytheme
)

g + theme(plot.title.position = "plot",
          plot.caption.position = "plot")

7.4 Use a Non-Traditional Font in Your Title

library(showtext)

## Loading required package: sysfonts

## Loading required package: showtextdb

## 
## Attaching package: 'showtextdb'

## The following object is masked from 'package:extrafont':
## 
##     font_install

font_add_google("Playfair Display", ## name of Google font
                "Playfair")  ## name that will be used in R
font_add_google("Bangers", "Bangers")

Now, we can use those font families using—yeah, you guessed right—theme():

ggplot(chic, aes(x = date, y = temp)) +
  geom_point(color = "firebrick") +
  labs(
    x = "Year",
    y = "Temperature (°F)",
    title = "Temperatures in Chicago",
    subtitle = "Daily temperatures in °F from 1997 to 2001"
  ) +
  theme(
    plot.title = element_text(
      family = "Bangers",
      hjust = .5,
      size = 25
    ),
    plot.subtitle = element_text(
      family = "Playfair",
      hjust = .5,
      size = 15
    )
  )

## Warning in grid.Call(C_stringMetric, as.graphicsAnnot(x$label)): Windows字体数据
## 库里没有这样的字体系列

## Warning in grid.Call(C_stringMetric, as.graphicsAnnot(x$label)): Windows字体数据
## 库里没有这样的字体系列

## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## Windows字体数据库里没有这样的字体系列

## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## Windows字体数据库里没有这样的字体系列

## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## Windows字体数据库里没有这样的字体系列

## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## Windows字体数据库里没有这样的字体系列

## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## Windows字体数据库里没有这样的字体系列

## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## Windows字体数据库里没有这样的字体系列

You can also set a non-default font for all text elements of your plots, for more details see section “Working with Themes”. I am going to use Roboto Condensed as new default font for all the plots that follow.

font_add_google("Roboto Condensed", "Roboto Condensed")
ggplot(chic, aes(x = date, y = temp)) +
  geom_point(color = "firebrick") +
  labs(
    x = "Year",
    y = "Temperature (°F)",
    title = "Temperatures in Chicago",
    subtitle = "Daily temperatures in °F from 1997 to 2001"
  ) +
  theme(text = element_text(family = "Roboto Condensed"))

7.5 Change Spacing in Multi-Line Text

ggplot(chic, aes(x = date, 
                 y = temp)) +
  geom_point(color = "firebrick") +
  labs(x = "Year", 
       y = "Temperature (°F)") +
  ggtitle("Temperatures in Chicago\nfrom 1997 to 2001") +
  theme(plot.title = element_text(lineheight = 2, size = 16)) +
  mytheme

8 Working with Legends

We will color code the plot based on season. Or to phrase it in a more ggplot’ish way: we map the variable season to the aesthetic color. One nice thing about {ggplot2} is that it adds a legend by default when mapping a variable to an aesthetic. You can see that by default the legend title is what we specified in the color argument:

ggplot(chic,
       aes(x = date, 
           y = temp, 
           color = season)) +
  geom_point() +
  geom_line(aes(group = 1)) +
  labs(x = "Year", 
       y = "Temperature (°F)") +
  ggtitle("Temperatures in Chicago\nfrom 1997 to 2001") +
  mytheme

8.1 Turn Off the Legend

ggplot(chic,
       aes(x = date, 
           y = temp, 
           color = season)) +
  geom_point() +
  geom_line(aes(group = 1)) +
  labs(x = "Year", 
       y = "Temperature (°F)") +
  ggtitle("Temperatures in Chicago\nfrom 1997 to 2001") +
  theme(legend.position = "none") +
  mytheme

chic %>% 
  ggplot(aes(x = date,y = temp,col = season,shape = season)) +
  geom_point() +
  geom_line(aes(group = 1),size = 0.2) +
  mytheme

You can also use guides(color = "none") or scale_color_discrete(guide = "none") depending on the specific case. While the change of the theme element removes all legends at once, you can remove particular legends with the latter options while keeping some others:

chic %>% 
  ggplot(aes(x = date,
             y = temp,
             col = season,
             shape = season)) +
  geom_point() +
  geom_line(aes(group = 1),size = 0.2) +
  guides(color = "none") +
  mytheme -> p1

chic %>% 
  ggplot(aes(x = date,
             y = temp,
             col = season,
             shape = season)) +
  geom_point() +
  geom_line(aes(group = 1),size = 0.2) +
  guides(shape = "none") +
  mytheme -> p2

p1 / p2

8.2 Remove Legend Titles

As we already learned, use element_blank() to draw nothing:

chic %>% 
  ggplot(aes(x = date,y = temp,col = season)) +
  geom_point() +
  geom_line(aes(group = 1)) +
  scale_y_continuous(limits = c(NA,90),breaks = seq(-5,90,5),
                     labels = str_c(seq(-5,90,5),"$")) +
  labs(x = "Year", y = "Temperature (°F)") +
  ggthemes::scale_color_economist() +
  ggthemes::theme_economist() +
  mytheme +
  theme(legend.title = element_blank()) 

💁 You can achieve the same by setting the legend name to NULL, either via scale_color_discrete(name = NULL) or labs(color = NULL).

8.3 Change Legend Position

chic %>% 
  ggplot(aes(x = date,y = temp,col = season)) +
  geom_point() +
  geom_line(aes(group = 1)) +
  scale_y_continuous(limits = c(NA,90),
                     breaks = seq(-5,90,5),
                     labels = str_c(seq(-5,90,5),"$")) +
  labs(x = "Year",
       y = "Temperature (°F)") +
  ggthemes::scale_color_economist() +
  ggthemes::theme_economist() +
  theme(legend.position = "top") +
  mytheme 

ggplot(chic, aes(x = date, y = temp, color = season)) +
  geom_point() +
  labs(x = "Year", y = "Temperature (°F)",
       color = NULL) +
  theme(legend.position = c(.15, .15),
        legend.background = element_rect(fill = "transparent")) +
  mytheme

8.4 Change Legend Direction

ggplot(chic, aes(x = date, y = temp, color = season)) +
  geom_point() +
  labs(x = "Year", y = "Temperature (°F)") +
  theme(legend.position = c(.5, .97),
        legend.background = element_rect(fill = "transparent")) +
  guides(color = guide_legend(direction = "horizontal")) +
  mytheme

8.5 Change Style of the Legend Title

You can change the appearance of the legend title by adjusting the theme element legend.title:

ggplot(chic, aes(x = date, 
                 y = temp, 
                 color = season)) +
  geom_point() +
  labs(x = "Year",
       y = "Temperature (°F)") +
  theme(legend.title = element_text(family = "Playfair",
                                    color = "chocolate",
                                    size = 14, 
                                    face = "bold")) +
  mytheme

## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## Windows字体数据库里没有这样的字体系列

## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## Windows字体数据库里没有这样的字体系列

8.6 Change Legend Title

The easiest way to change the title of the legend is the labs() layer,The legend details can be changed via scale_color_discrete(name = "title") or guides(color = guide_legend("title")):

ggplot(chic, aes(x = date, 
                 y = temp, 
                 color = season)) +
  geom_point() +
  labs(x = "Year", 
       y = "Temperature (°F)",
       color = "Seasons\nindicated\nby colors:") +
  theme(legend.title = element_text(family = "Playfair",
                                    color = "chocolate",
                                    size = 14,
                                    face = "bold")) -> p1

ggplot(chic, aes(x = date, 
                 y = temp, 
                 color = season)) +
  geom_point() +
  labs(x = "Year", 
       y = "Temperature (°F)") +
  scale_color_discrete(name = "Seasons\nindicated\nby colors:") +
  theme(legend.title = element_text(family = "Playfair",
                                    color = "chocolate",
                                    size = 14,
                                    face = "bold")) -> p2

p1 / p2

## Warning in grid.Call(C_stringMetric, as.graphicsAnnot(x$label)): Windows字体数据
## 库里没有这样的字体系列

## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## Windows字体数据库里没有这样的字体系列

## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## Windows字体数据库里没有这样的字体系列

## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## Windows字体数据库里没有这样的字体系列

## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## Windows字体数据库里没有这样的字体系列

8.7 Change Order of Legend Keys

factor(1:10,labels = letters[1:10])

##  [1] a b c d e f g h i j
## Levels: a b c d e f g h i j

chic$season <- 
  factor(chic$season, 
         levels = c("Winter", "Spring", "Summer", "Autumn"))

ggplot(chic, aes(x = date, y = temp, color = season)) +
  geom_point() +
  labs(x = "Year", y = "Temperature (°F)") +
  mytheme

8.8 Change Legend Labels

We are going to replace the seasons by the months which they are covering by providing a vector of names in the scale_color_discrete() call:

ggplot(chic, aes(x = date, 
                 y = temp, 
                 color = season)) +
  geom_point() +
  labs(x = "Year", 
       y = "Temperature (°F)") +
  scale_color_discrete(name = "Seasons:", 
                       labels = c("Mar—May", "Jun—Aug",
                                              "Sep—Nov", "Dec—Feb")) +
  mytheme

8.9 Change Background Boxes in the Legend

ggplot(chic, aes(x = date, y = temp, color = season)) +
  geom_point() +
  labs(x = "Year", y = "Temperature (°F)") +
  scale_color_discrete(name = "Seasons:") +
  theme(legend.key = element_rect(fill = "darkgoldenrod1"),
        legend.title = element_text(family = "Playfair",
                                    color = "chocolate",
                                    size = 14, face = 2)) 

## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## Windows字体数据库里没有这样的字体系列

## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :
## Windows字体数据库里没有这样的字体系列

If you want to get rid of them entirely use fill = NA or fill = "transparent".

8.10 Change Size of Legend Symbols

ggplot(chic, aes(x = date, 
                 y = temp, 
                 color = season)) +
  geom_point() +
  labs(x = "Year", 
       y = "Temperature (°F)") +
  theme(legend.key = element_rect(fill = NA),
        legend.title = element_text(color = "chocolate",
                                    size = 14,
                                    face = 2)) +
  scale_color_discrete("Seasons:") +
  guides(color = guide_legend(override.aes = list(size = 6)))

8.11 Leave a Layer Off the Legend

ggplot(chic, aes(x = date, y = temp, color = season)) +
  geom_point() +
  labs(x = "Year", y = "Temperature (°F)")  +
  geom_rug() + 
  mytheme

ggplot(chic, aes(x = date, y = temp, color = season)) +
  geom_point() +
  labs(x = "Year", y = "Temperature (°F)")  +
  geom_rug(show.legend = FALSE) + 
  mytheme

8.12 Manually Adding Legend Items

ggplot(chic, aes(x = date, y = o3)) +
  geom_line(color = "gray") +
  geom_point(color = "darkorange2") +
  labs(x = "Year", y = "Ozone") +
  mytheme

ggplot(chic, aes(x = date, y = o3)) +
  geom_line(aes(color = "line")) +
  geom_point(aes(color = "points")) +
  labs(x = "Year", y = "Ozone") +
  scale_color_discrete("Type:") +
  mytheme

We are getting close but this is not what we want. We want gray and red! To change the color, we use scale_color_manual(). Additionally, we override the legend aesthetics using the guide() function.

ggplot(chic, aes(x = date, 
                 y = o3)) +
  geom_line(aes(color = "line")) +  
  geom_point(aes(color = "points")) +
  labs(x = "Year", y = "Ozone") +
  scale_color_manual(name = NULL,
                     guide = "legend",
                     values = c("points" = "darkorange2",
                                "line" = "gray")) +
  guides(color = guide_legend(override.aes = list(linetype = c(1, 0),
                                                  shape = c(NA, 16)))) +
  mytheme

8.13 Use Other Legend Styles

The default legend for categorical variables such as season is a guide_legend() as you have seen in several previous examples. If you map a continuous variable to an aesthetic, {ggplot2} will by default not use guide_legend() but guide_colorbar() (or guide_colourbar()):

ggplot(chic,
       aes(x = date, y = temp, color = temp)) +
  geom_point() +
  labs(x = "Year", y = "Temperature (°F)", color = "Temperature (°F)") +
  mytheme

However, by using guide_legend() you can force the legend to show discrete colors for a given number of breaks as in case of a categorical variable:

ggplot(chic,
       aes(x = date, 
           y = temp, 
           color = temp)) +
  geom_point() +
  labs(x = "Year", 
       y = "Temperature (°F)",
       color = "Temperature (°F)") +
  guides(color = guide_legend()) +
  mytheme

ggplot(chic,
       aes(x = date, y = temp, color = temp)) +
  geom_point() +
  labs(x = "Year", y = "Temperature (°F)", color = "Temperature (°F)") +
  guides(color = guide_bins()) +
  mytheme

ggplot(chic,
       aes(x = date, y = temp, color = temp)) +
  geom_point() +
  labs(x = "Year", y = "Temperature (°F)", color = "Temperature (°F)") +
  guides(color = guide_colorsteps()) +
  mytheme

9 Working with Backgrounds & Grid Lines

9.1 Change Grid Lines

There are two types of grid lines: major grid lines indicating the ticks and minor grid lines between the major ones. You can change all of these by overwriting the defaults for panel.grid or for each set of gridlines separately panel.grid.major and panel.grid.minor.

ggplot(chic, aes(x = date,
                 y = temp)) +
  geom_point(color = "firebrick") +
  labs(x = "Year", 
       y = "Temperature (°F)") +
  theme(panel.background = element_rect(fill = "gray90"),
        panel.grid.major = element_line(color = "gray10", size = .5),
        panel.grid.minor = element_line(color = "gray70", size = .25)) +
  mytheme

ggplot(chic, aes(x = date, y = temp)) +
  geom_point(color = "firebrick") +
  labs(x = "Year", y = "Temperature (°F)") +
  theme(panel.background = element_rect(fill = "gray90"),
        panel.grid.major = element_line(size = .5, linetype = "dashed"),
        panel.grid.minor = element_line(size = .25, linetype = "dotted"),
        panel.grid.major.x = element_line(color = "red1"),
        panel.grid.major.y = element_line(color = "blue1"),
        panel.grid.minor.x = element_line(color = "red4"),
        panel.grid.minor.y = element_line(color = "blue4")) +
  mytheme

ggplot(chic, aes(x = date, y = temp)) +
  geom_point(color = "firebrick") +
  labs(x = "Year", y = "Temperature (°F)") +
  theme(panel.grid.minor = element_blank()) +
  mytheme

ggplot(chic, aes(x = date, y = temp)) +
  geom_point(color = "firebrick") +
  labs(x = "Year", y = "Temperature (°F)") +
  theme(panel.grid = element_blank()) +
  mytheme

Furthermore, you can also define the breaks between both, major and minor grid lines:

ggplot(chic, aes(x = date, y = temp)) +
  geom_point(color = "firebrick") +
  labs(x = "Year", y = "Temperature (°F)") +
  scale_y_continuous(breaks = seq(0, 100, 10),
                     minor_breaks = seq(0, 100, 2.5)) +
  mytheme

9.2 Change the Panel Background Color

To change the background color (fill) of the panel area (i.e. the area where the data is plotted), one needs to adjust the theme element panel.background:

ggplot(chic, aes(x = date, y = temp)) +
  geom_point(color = "#1D8565", size = 2) +
  labs(x = "Year", y = "Temperature (°F)") +
  theme(panel.background = element_rect(fill = "#64D2AA",
                                        color = "#64D2AA", 
                                        size = 2)) +
  mytheme

ggplot(chic, aes(x = date, y = temp)) +
  geom_point(color = "#1D8565", size = 2) +
  labs(x = "Year", y = "Temperature (°F)") +
  theme(panel.border = element_rect(fill = "#64D2AA99",
                                    color = "#64D2AA", size = 2)) +
  mytheme

9.3 Change the Plot Background Color

ggplot(chic, aes(x = date, 
                 y = temp)) +
  geom_point(color = "firebrick") +
  labs(x = "Year", 
       y = "Temperature (°F)") +
  theme(plot.background = element_rect(fill = "gray60",
                                       color = "gray30",
                                       size = 2)) +
  mytheme

You can achieve a unique background color by either setting the same colors in both panel.background and plot.background or by setting the background filling of the panel to "transparent" or NA:

ggplot(chic, aes(x = date,
                 y = temp)) +
  geom_point(color = "firebrick") +
  labs(x = "Year", 
       y = "Temperature (°F)") +
  theme(panel.background = element_rect(fill = "red"),
        plot.background = element_rect(fill = "gray60",
                                       color = "gray30", 
                                       size = 2)) +
  mytheme

10 Working with Margins

ggplot(chic, aes(x = date, y = temp)) +
  geom_point(color = "firebrick") +
  labs(x = "Year", y = "Temperature (°F)") +
  theme(plot.background = element_rect(fill = "green"),
        plot.margin = unit(c(1, 3, 1, 8), "cm")) +
  mytheme

The order of the margin sides is top, right, bottom, left—a nice way to remember this order is "trouble that sorts the first letter of the four sides.

11 Working with Multi-Panel Plots

11.1 Create a Multi-Panel Plots Based on One Variable

facet_wrap creates a facet of a single variable, written with a tilde in front: facet_wrap(~ variable). The appearance of these subplots is controlled by the arguments ncol and nrow:

g <- ggplot(chic, aes(x = date, y = temp)) +
       geom_point(color = "chartreuse4", alpha = .3) +
       labs(x = "Year", y = "Temperature (°F)") +
  mytheme
g
g + 
  scale_y_continuous(breaks = seq(0,90,10)) +
  facet_wrap(~year,nrow = 1) +
  theme(axis.text.x = element_text(angle = 45,vjust = 0.5))

g + 
  scale_y_continuous(breaks = seq(0,90,10)) +
  facet_wrap(~year,nrow = 2) +
  theme(axis.text.x = element_text(angle = 45,vjust = 0.5))

11.2 Allow Scales to Roam Free

lct <- Sys.getlocale("LC_TIME")
Sys.setlocale("LC_TIME", "C")

## [1] "C"

g + 
  scale_y_continuous(breaks = seq(0,90,10)) +
  facet_wrap(~year,nrow = 2,scales = "free") +
  theme(axis.text.x = element_text(angle = 45,vjust = 0.5))

Note that both, x and y axes differ in their range!

11.3 Create a Grid of Plots Based on Two Variables

g + 
  scale_y_continuous(breaks = seq(0,90,10)) +
  facet_grid(year ~ season) +
  theme(axis.text.x = element_text(angle = 45,vjust = 0.5))

11.4 Modify Style of Strip Texts

By using theme, you can modify the appearance of the strip text(i.e. the title for each facet) and the strip text boxes:

g + facet_wrap(~ year, 
               nrow = 1, 
               scales = "free_x") +
  mytheme +
  theme(strip.text = element_text(face = "bold",
                                  color = "chartreuse4",
                                  hjust = 0.5, 
                                  size = 20),
        strip.background = element_rect(fill = "chartreuse3", linetype = "dotted"),
        axis.text.x = element_text(angle = 45,vjust = 0.5))

library(ggtext)
library(rlang)

element_textbox_highlight <- function(..., hi.labels = NULL, 
                                      hi.fill = NULL,
                                      hi.col = NULL, 
                                      hi.box.col = NULL, 
                                      hi.family = NULL) {
  structure(
    c(element_textbox(...),
      list(hi.labels = hi.labels, hi.fill = hi.fill, hi.col = hi.col, hi.box.col = hi.box.col, hi.family = hi.family)
    ),
    class = c("element_textbox_highlight", "element_textbox", "element_text", "element")
  )
}

element_grob.element_textbox_highlight <- function(element, label = "", ...) {
  if (label %in% element$hi.labels) {
    element$fill <- element$hi.fill %||% element$fill
    element$colour <- element$hi.col %||% element$colour
    element$box.colour <- element$hi.box.col %||% element$box.colour
    element$family <- element$hi.family %||% element$family
  }
  NextMethod()
}

Now you can use it and specify for example all strip texts showing year:

g + facet_wrap(year ~ season, nrow = 4, scales = "free_x") +
  mytheme +
  theme(
    strip.background = element_blank(),
    strip.text = element_textbox_highlight(
      family = enfont, 
      size = 12, 
      face = "bold",
      fill = "white",
      box.color = "chartreuse4", 
      color = "chartreuse4",
      halign = .5, 
      linetype = 1,
      r = unit(5, "pt"), 
      width = unit(1, "npc"),
      padding = margin(5, 0, 3, 0), 
      margin = margin(0, 1, 3, 1),
      hi.labels = c("1997", "1998", "1999", "2000"),
      hi.fill = "chartreuse4",
      hi.box.col = "black", 
      hi.col = "white"
    )
  )

ggplot(chic, aes(x = date, 
                 y = temp)) +
  geom_point(aes(color = (season == "Summer")), 
             alpha = .3) +
  labs(x = "Year", y = "Temperature (°F)") +
  facet_wrap(~ season, 
             nrow = 1) +
  scale_color_manual(values = c("gray40", "firebrick")) +
  mytheme +
  theme(
    axis.text.x = element_text(angle = 45,
                               vjust = 1, 
                               hjust = 1),
    legend.position = "none",
    strip.background = element_blank(),
    strip.text = element_textbox_highlight(
      size = 12, 
      face = "bold",
      fill = "white", 
      box.color = "white",
      color = "gray40",
      halign = .5, 
      linetype = 1, 
      r = unit(0, "pt"), 
      width = unit(1, "npc"),
      padding = margin(2, 0, 1, 0), 
      margin = margin(0, 1, 3, 1),
      hi.labels = "Summer", 
      hi.family = enfont,
      hi.fill = "firebrick",
      hi.box.col = "firebrick",
      hi.col = "white"
    )
  )

ggplot(chic, aes(x = date,
                 y = temp)) +
  geom_point(aes(color = season == "Summer"), 
             alpha = .3) +
  labs(x = "Year", 
       y = "Temperature (°F)") +
  facet_wrap(~ season,
             nrow = 1) +
  scale_color_manual(values = c("gray40", "firebrick"),
                     guide = "none") +
  mytheme +
  theme(
    axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1),
    strip.background = element_blank(),
    strip.text = element_textbox_highlight(
      size = 12, 
      face = "bold",
      fill = "white",
      box.color = "white", 
      color = "gray40",
      halign = .5, 
      linetype = 1,
      r = unit(0, "pt"),
      width = unit(1, "npc"),
      padding = margin(2, 0, 1, 0), 
      margin = margin(0, 1, 3, 1),
      hi.labels = "Summer", 
      hi.family = enfont,
      hi.fill = "firebrick", 
      hi.box.col = "firebrick", 
      hi.col = "white"
    )
  )

11.5 Create a Multi-Panel Plot Based on (Different) Plots

There are several ways how plots can be combined. The easiest approach in my opinion is the {patchwork} package by Thomas Lin Pedersen:

p1 <- ggplot(chic, aes(x = date,
                       y = temp,
                       color = season)) +
  geom_point() +
  geom_rug() +
  scale_y_continuous(breaks = seq(0, 90, 10)) +
  labs(x = "Year",
       y = "Temperature (°F)") +
  mytheme

p2 <- ggplot(chic, aes(x = date,
                       y = o3)) +
  geom_line(color = "gray") +
  geom_point(color = "darkorange2") +
  scale_y_continuous(breaks = seq(0, 60, 10)) +
  labs(x = "Year",
       y = "Ozone") +
  mytheme

p1 + p2

We can change the order by “dividing” both plots (and note the alignment even though one has a legend and one doesn’t!):

p1 / p2

(g + p2) / p1

The same idea of defining a layout can be used with {patchwork} as well which allows to create complex compositions:

layout <- "
AABBBB#
AACCDDE
##CCDD#
##CC###
"

p2 + p1 + p1 + g + p2 +
  plot_layout(design = layout)

12 Working with Colors

chic %>% 
  ggplot(aes(year)) +
  geom_bar(aes(fill = season),col = "gray",size = 2) +
  labs(x = "Year", y = "Observations",fill = "Season:") +
  mytheme

12.1 Specify Single Colors

ggplot(chic, aes(x = date, 
                 y = temp)) +
  geom_point(color = "steelblue", 
             size = 2) +
  labs(x = "Year", 
       y = "Temperature (°F)") +
  mytheme

ggplot(chic, aes(x = date, 
                 y = temp)) +
  geom_point(shape = 21, 
             size = 2,
             stroke = 1,
             color = "#3cc08f",
             fill = "#c08f3c") +
  labs(x = "Year", y = "Temperature (°F)") +
  mytheme

12.2 Assign Colors to Variables

In {ggplot2}, colors that are assigned to variables are modified via the scale_color_* and the scale_fill_* functions. In order to use color with your data, most importantly you need to know if you are dealing with a categorical or continuous variable. The color palette should be chosen depending on type of the variable, with sequential or diverging color palettes being used for continuous variables and qualitative color palettes for categorical variables:

12.3 Qualitative Variables

Qualitative or categorical variables represent types of data which can be divided into groups (categories). The variable can be further specified as nominal, ordinal, and binary (dichotomous). Examples of qualitative/categorical variables are:

(ga <- ggplot(chic, aes(x = date, y = temp, color = season)) +
  geom_point() +
  labs(x = "Year", y = "Temperature (°F)") +
  mytheme)

12.4 Manually Select Qualitative Colors

You can pick your own set of colors and assign them to a categorical variables via the function scale_*_manual() (the * can be either color, colour, or fill). The number of specified colors has to match the number of categories:

ga + scale_color_manual(values = c("dodgerblue4",
                                   "darkolivegreen4",
                                   "darkorchid3",
                                   "goldenrod1"))

12.5 Use Built-In Qualitative Color Palettes

The ColorBrewer palettes is a popular online tool for selecting color schemes for maps. The different sets of colors have been designed to produce attractive color schemes of similar appearance ranging from three to twelve. Those palettes are available as built-in functions in the {ggplot2} package and can be applied by calling scale_*_brewer():

chic %>% 
  ggplot(aes(x = date,y = temp)) +
  geom_point(aes(col = season)) +
  scale_color_brewer(palette = "Set1") +
  mytheme

💡 You can explore all schemes available via RColorBrewer::display.brewer.all().

RColorBrewer::display.brewer.all()

RColorBrewer::display.brewer.pal(n = 10,name = "Set3")

RColorBrewer::brewer.pal(n = 6,name = "Set1") %>% scales::show_col()

12.6 Use Qualitative Color Palettes from Extension Packages

The {ggthemes} package for example lets R users access the Tableau colors. Tableau is a famous visualiztion software with a well-known color palette.

ga + ggthemes::scale_color_tableau()

The {ggsci} package provides scientific journal and sci-fi themed color palettes. Want to have a plot with colors that look like being published in Science or Nature? Here you go!

library(ggsci)
g1 <- ga + scale_color_aaas()
g2 <- ga + scale_color_npg()

(g1 + g2) * theme(legend.position = "top")

12.7 Quantitative Variables

In our example we will change the variable we want to color to ozone, a continuous variable that is strongly related to temperature (higher temperature = higher ozone). The function scale_*_gradient() is a sequential gradient while scale_*_gradient2() is diverging.

gb <- ggplot(chic, aes(x = date, 
                       y = temp, 
                       color = temp)) +
  geom_point() +
  labs(x = "Year", 
       y = "Temperature (°F)", 
       color = "Temperature (°F):")

gb + scale_color_continuous() + mytheme

This code produces the same plot:

gb + scale_color_gradient() + mytheme

mid <- mean(chic$temp)  ## midpoint

gb + scale_color_gradient2(midpoint = mid) + mytheme

12.8 Manually Set a Sequential Color Scheme

You can manually set gradually changing color palettes for continuous variables via scale_*_gradient():

gb +
  scale_color_gradient(low = "darkkhaki",
                       high = "darkgreen") +
  mytheme

Temperature data is normally distributed so how about a diverging color scheme (rather than sequential)… For diverging color you can use the scale_*_gradient2() function:

gb + scale_color_gradient2(midpoint = mid,
                           low = "#dd8a0b",
                           mid = "grey92", 
                           high = "#32a676") +
  mytheme

12.9 The Beautiful Viridis Color Palette

p1 <- gb + 
  scale_color_viridis_c() + 
  ggtitle("'viridis' (default)") +
  mytheme
p2 <- gb + 
  scale_color_viridis_c(option = "inferno") +
  ggtitle("'inferno'") +
  mytheme
p3 <- gb + 
  scale_color_viridis_c(option = "plasma") +
  ggtitle("'plasma'") +
  mytheme
p4 <- gb + 
  scale_color_viridis_c(option = "cividis") + 
  ggtitle("'cividis'") +
  mytheme

(p1 + p2 + p3 + p4) * theme(legend.position = "bottom") 

ga + theme(legend.position = "NULL")

12.10 Use Quantitative Color Palettes from Extension Packages

library(rcartocolor)

g1 <- gb + scale_color_carto_c(palette = "BurgYl") + mytheme

g2 <- gb + scale_color_carto_c(palette = "Earth") + mytheme

(g1 + g2) * theme(legend.position = "bottom") 

The {scico} package provides access to the color palettes developed by Fabio Crameri. These color palettes are not only beautiful and often unusual but also a good choice since they have been developed to be perceptually uniform and ordered. In addition, they work for people with color vision deficiency and in grayscale:

library(scico)

g1 <- gb + scale_color_scico(palette = "berlin") + mytheme
g2 <- gb + scale_color_scico(palette = "hawaii", direction = -1) + mytheme

(g1 + g2) * theme(legend.position = "bottom")

12.11 Modify Color Palettes Afterwards

library(ggdark)

ggplot(chic, aes(date, 
                 temp, 
                 color = temp)) +
  geom_point(size = 5) +
  geom_point(aes(color = temp,
                 color = after_scale(invert_color(color))),
             size = 2) +
  scale_color_scico(palette = "hawaii", 
                    guide = "none") +
  labs(x = "Year", 
       y = "Temperature (°F)") +
  mytheme

## Warning: Duplicated aesthetics after name standardisation: colour

library(colorspace)

ggplot(chic, aes(date, temp)) +
  geom_boxplot(aes(color = season,
                   fill = after_scale(desaturate(lighten(color, .6), .6))),
               size = 1) +
  scale_color_brewer(palette = "Dark2", guide = "none") +
  labs(x = "Year", y = "Temperature (°F)") +
  mytheme

13 Working with Themes

13.1 Change the Overall Plotting Style

chic %>% 
  ggplot(aes(x = date,y = temp,col = season)) +
  geom_point() +
  geom_line(aes(group = 1)) +
  scale_y_continuous(breaks = seq(0,90,10)) +
  theme(axis.text.x = element_text(angle = 45,vjust = 0.5)) +
  mytheme -> p1

chic %>% 
  ggplot(aes(x = date,y = temp,col = season)) +
  geom_point() +
  geom_line(aes(group = 1)) +
  scale_y_continuous(breaks = seq(0,90,10)) +
  theme(axis.text.x = element_text(angle = 45,vjust = 0.5)) +
  theme_bw() +
  mytheme -> p2

chic %>% 
  ggplot(aes(x = date,y = temp,col = season)) +
  geom_point() +
  geom_line(aes(group = 1)) +
  scale_y_continuous(breaks = seq(0,90,10)) +
  theme(axis.text.x = element_text(angle = 45,vjust = 0.5)) +
  theme_classic() +
  mytheme -> p3

chic %>% 
  ggplot(aes(x = date,y = temp,col = season)) +
  geom_point() +
  geom_line(aes(group = 1)) +
  scale_y_continuous(breaks = seq(0,90,10)) +
  theme(axis.text.x = element_text(angle = 45,vjust = 0.5)) +
  theme_dark() +
  mytheme -> p4

chic %>% 
  ggplot(aes(x = date,y = temp,col = season)) +
  geom_point() +
  geom_line(aes(group = 1)) +
  scale_y_continuous(breaks = seq(0,90,10)) +
  theme(axis.text.x = element_text(angle = 45,vjust = 0.5)) +
  theme_light() +
  mytheme -> p5

chic %>% 
  ggplot(aes(x = date,y = temp,col = season)) +
  geom_point() +
  geom_line(aes(group = 1)) +
  scale_y_continuous(breaks = seq(0,90,10)) +
  theme(axis.text.x = element_text(angle = 45,vjust = 0.5)) +
  theme_linedraw() +
  mytheme -> p6

chic %>% 
  ggplot(aes(x = date,y = temp,col = season)) +
  geom_point() +
  geom_line(aes(group = 1)) +
  scale_y_continuous(breaks = seq(0,90,10)) +
  theme(axis.text.x = element_text(angle = 45,vjust = 0.5)) +
  theme_minimal() +
  mytheme -> p7


chic %>% 
  ggplot(aes(x = date,y = temp,col = season)) +
  geom_point() +
  geom_line(aes(group = 1)) +
  scale_y_continuous(breaks = seq(0,90,10)) +
  theme(axis.text.x = element_text(angle = 45,vjust = 0.5)) +
  theme_void() +
  mytheme -> p8

(p1 | p2) / (p3 | p4) / (p5 | p6) / ( p7 | p8)

ggplot(chic, aes(x = date, 
                 y = temp, 
                 color = season)) +
  geom_point() +
  labs(x = "Year", y = "Temperature (°F)") +
  ggtitle("Ups and Downs of Chicago's Daily Temperatures") +
  theme_economist() +
  scale_color_economist(name = NULL)

library(dplyr)
chic_2000 <- filter(chic, year == 2000)

ggplot(chic_2000, aes(x = temp, y = o3)) +
  geom_point() +
  labs(x = "Temperature (°F)", y = "Ozone") +
  ggtitle("Temperature and Ozone Levels During the Year 2000 in Chicago") +
  theme_tufte()

Another neat packages with modern themes and a preset of non-default fonts is the {hrbrthemes} package by Bob Rudis with several light but also dark themes:

chic %>% 
  ggplot(aes(x = temp,y = o3,col = dewpoint)) +
  geom_point() +
  geom_line() +
  scale_color_continuous(guide = "none") +
  labs(x = "Temperature (°F)", y = "Ozone") +
  ggtitle("Temperature and Ozone Levels in Chicago") +
  mytheme +
  hrbrthemes::theme_ipsum_pub()

13.2 Change the Font of All Text Elements

g <- ggplot(chic, aes(x = date, y = temp)) +
  geom_point(color = "firebrick") +
  labs(x = "Year", y = "Temperature (°F)",
       title = "Temperatures in Chicago")

g + theme_bw(base_family = enfont)

13.3 Change the Size of All Text Elements

g + theme_bw(base_size = 30, base_family = "Roboto Condensed")

13.4 Change the Size of All Line and Rect Elements

g + theme_bw(base_line_size = 1, base_rect_size = 1)

13.5 Create Your Own Theme

13.6 Update the Current Theme

You can also set quick changes using theme_update()

14 Working with Lines

14.1 Add Horizonal or Vertical Lines to a Plot

chic %>% 
  ggplot(aes(x = date,y = temp,col = season)) +
  geom_line(aes(group = 1)) +
  geom_point() +
  scale_color_discrete(name = NULL) +
  scale_y_continuous(breaks = seq(0,100,20)) +
  theme(legend.position = "top") +
  labs(x = "Year", y = "Temperature (°F)") +
  geom_hline(yintercept = c(0, 73))  +
  mytheme

g <- ggplot(chic, aes(x = temp, y = dewpoint)) +
  geom_point(color = "dodgerblue", alpha = .5) +
  labs(x = "Temperature (°F)", y = "Dewpoint") +
  mytheme

g +
  geom_vline(
    aes(xintercept = median(temp)),
    size = 1.5,
    color = "firebrick",
    linetype = "dashed"
  ) +
  geom_hline(
    aes(yintercept = median(dewpoint)),
    size = 1.5,
    color = "firebrick",
    linetype = "dashed"
  )

reg <- lm(dewpoint ~ temp, data = chic)

g +
  geom_abline(
    intercept = coefficients(reg)[1],
    slope = coefficients(reg)[2],
    color = "darkorange2",
    size = 1.5
  ) +
  labs(title = paste0("y = ", round(coefficients(reg)[2], 2),
                      " * x ", round(coefficients(reg)[1], 2))) +
  mytheme

14.2 Add a Line within a Plot

g +
  ## vertical line
  geom_linerange(aes(x = 50, ymin = 20, ymax = 55),
                 color = "steelblue", size = 2) +
  ## horizontal line
  geom_linerange(aes(xmin = -Inf, xmax = 25, y = 0),
                 color = "red", size = 1)

g +
  geom_segment(aes(x = 50, xend = 75,
                   y = 20, yend = 45),
               color = "purple", size = 2)

14.3 Add Curved Lines and Arrows to a Plot

g +
  geom_curve(aes(x = 0, 
                 y = 60, 
                 xend = 75,
                 yend = 0),
             size = 2, 
             color = "tan") +
  geom_curve(aes(x = 0, 
                 y = 60,
                 xend = 75,
                 yend = 0),
             curvature = -0.7,
             angle = 45,
             color = "darkgoldenrod1", 
             size = 1) +
  geom_curve(aes(x = 0,
                 y = 60, 
                 xend = 75,
                 yend = 0),
             curvature = 0, 
             size = 1.5)

g +
  geom_curve(aes(x = 0, y = 60, xend = 75, yend = 0),
             size = 2, color = "tan",
             arrow = arrow(length = unit(0.07, "npc"))) +
  geom_curve(aes(x = 5, y = 55, xend = 70, yend = 5),
             curvature = -0.7, angle = 45,
             color = "darkgoldenrod1", size = 1,
             arrow = arrow(length = unit(0.03, "npc"),
                           type = "closed",
                           ends = "both"))

15 Working with Text

15.1 Add Labels to Your Data

set.seed(2020)
chic %>% 
  group_by(season) %>% 
  sample_frac(size = 0.01) %>% 
  ungroup() %>% 
  ggplot(aes(x = date, y = temp, color = season)) +
  geom_point() +
  geom_label(aes(label = season), hjust = .5, vjust = -.5,family = enfont) +
  labs(x = "Year", y = "Temperature (°F)") +
  scale_x_date(limits = c(ymd(19970101),ymd(20001231)),
               breaks = "1 year",
               date_labels = "%Y") +
  scale_y_continuous(limits = c(0,90),
                     breaks = seq(0,90,15)) +
  theme(axis.text.x = element_text(angle = 45,vjust = 0.5)) +
  mytheme

set.seed(2020)
chic %>% 
  group_by(season) %>% 
  sample_frac(size = 0.01) %>% 
  ungroup() %>% 
  ggplot(aes(x = date, y = temp,col = season)) +
  geom_point() +
  geom_label_repel(aes(label = season), hjust = .5, vjust = -.5,family = enfont,
                   show.legend = FALSE) +
  scale_color_brewer(palette = "Set1") +
  labs(x = "Year", y = "Temperature (°F)") +
  scale_x_date(limits = c(ymd(19970101),ymd(20001231)),
               breaks = "1 year",
               date_labels = "%Y") +
  scale_y_continuous(limits = c(0,90),
                     breaks = seq(0,90,15)) +
  theme(axis.text.x = element_text(angle = 45,vjust = 0.5)) +
  mytheme

chic %>% 
  group_by(season) %>% 
  sample_frac(size = 0.01) %>% 
  ungroup() %>% 
  ggplot(aes(x = date, y = temp)) +
  geom_point(size = 2.5,aes(col = season),show.legend = FALSE) +
  geom_point(data = chic,aes(x = date,y = temp),size = 0.5) + 
  geom_label_repel(aes(label = season), hjust = .5, vjust = -.5,family = enfont) +
  scale_color_brewer(palette = "Set1") +
  labs(x = "Year", y = "Temperature (°F)") +
  scale_x_date(limits = c(ymd(19970101),ymd(20001231)),
               breaks = "1 year",
               date_labels = "%Y") +
  scale_y_continuous(limits = c(-5,90),
                     breaks = seq(0,90,15)) +
  theme(axis.text.x = element_text(angle = 45,vjust = 0.5),
        legend.position = "none") +
  mytheme

15.2 Add Text Annotations

g <- 
  ggplot(chic, aes(x = temp, 
                   y = dewpoint)) +
  geom_point(alpha = .5) +
  labs(x = "Temperature (°F)", 
       y = "Dewpoint") +
  mytheme

g +
  geom_text(aes(x = 25, 
                y = 60,
                label = "This is an useful annotation"))

g + 
  geom_text(aes(x = 25, y = 60,
                label = "This is an useful annotation"),
            stat = "unique",
            family = enfont,
            size = 7,
            color = "darkcyan") +
  mytheme

ann <- data.frame(
  o3 = 30,
  temp = 20,
  season = factor("Summer", levels = levels(chic$season)),
  label = "Here is enough space\nfor some annotations."
)
ann %>% str()

## 'data.frame':    1 obs. of  4 variables:
##  $ o3    : num 30
##  $ temp  : num 20
##  $ season: Factor w/ 4 levels "Winter","Spring",..: 3
##  $ label : chr "Here is enough space\nfor some annotations."

g <- 
  ggplot(chic, aes(x = o3, y = temp)) +
  geom_point() +
  labs(x = "Ozone", y = "Temperature (°F)") +
  mytheme

g +
  geom_text(data = ann,
            aes(label = label),
            size = 7,
            fontface = "bold",
            family = "Roboto Condensed") +
  facet_wrap(~season) +
  theme(
    strip.background = element_blank(),
    strip.text = element_textbox_highlight(
      family = enfont, 
      size = 12, 
      face = "bold",
      fill = "white",
      box.color = "chartreuse4", 
      color = "chartreuse4",
      halign = .5, 
      linetype = 1,
      r = unit(5, "pt"), 
      width = unit(1, "npc"),
      padding = margin(5, 0, 3, 0), 
      margin = margin(0, 1, 3, 1),
      hi.labels = c("1997", "1998", "1999", "2000"),
      hi.fill = "chartreuse4",
      hi.box.col = "black", 
      hi.col = "white"
    )
  ) +
  mytheme

g + 
  geom_text(aes(x = 23,
                y = 97, 
                label = "This is not an useful annotation"),
            size = 5, fontface = "bold") +
  scale_y_continuous(limits = c(NA, 100)) +
  facet_wrap(~season, scales = "free_x") +
  theme(
    strip.background = element_blank(),
    strip.text = element_textbox_highlight(
      family = enfont, 
      size = 12, 
      face = "bold",
      fill = "white",
      box.color = "chartreuse4", 
      color = "chartreuse4",
      halign = .5, 
      linetype = 1,
      r = unit(5, "pt"), 
      width = unit(1, "npc"),
      padding = margin(5, 0, 3, 0), 
      margin = margin(0, 1, 3, 1),
      hi.labels = c("1997", "1998", "1999", "2000"),
      hi.fill = "chartreuse4",
      hi.box.col = "black", 
      hi.col = "white"
    )
  ) +
  mytheme

15.3 Use Markdown and HTML Rendering for Annotations

library(ggtext)

lab_md <- "This plot shows **temperature** in *°F* versus **ozone level** in *ppm*"

g + 
  geom_richtext(aes(x = 35,
                    y = 3, 
                    label = lab_md),
                stat = "unique",
                family = enfont) +
  mytheme

lab_html <- "&#9733; This plot shows <b style='color:red;'>temperature</b> in <i>°F</i> versus <b style='color:blue;'>ozone level</b>in <i>ppm</i> &#9733;"

g + 
  geom_richtext(aes(x = 33, y = 3, label = lab_html),
                stat = "unique",
                family =  enfont) +
  mytheme

g + 
  geom_richtext(aes(x = 10, y = 25, label = lab_md),
                stat = "unique",
                angle = 30, 
                color = "white",
                fill = "steelblue", 
                label.color = NA, 
                hjust = 0,
                vjust = 0,
                family = enfont) +
  mytheme

The other geom from the {ggtext} package is geom_textbox(). This geom allows for dynamic wrapping of strings which is very useful for longer annotations such as info boxes and subtitles.

lab_long <- "**Lorem ipsum dolor**<br><i style='font-size:8pt;color:red;'>Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.<br>Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.</i>"

g + 
  geom_textbox(aes(x = 40, 
                   y = 10, 
                   label = lab_long), 
               width = unit(15, "lines"),
               stat = "unique") 

16 Working with Coordinates

16.1 Flip a Plot

chic %>% 
  ggplot(aes(x = season,y = o3)) +
  geom_boxplot(fill = "indianred") +
  labs(x = "Season", y = "Ozone") +
  mytheme +
  coord_flip()

16.2 Fix an Axis

ggplot(chic, aes(x = temp, y = o3)) +
  geom_point() +
  labs(x = "Temperature (°F)", y = "Ozone Level") +
  scale_x_continuous(breaks = seq(0, 80, by = 20)) +
  coord_fixed(ratio = 1) +
  mytheme

16.3 Reverse an Axis

ggplot(chic, aes(x = date, 
                 y = temp, 
                 color = o3)) +
  geom_point() +
  labs(x = "Year",
       y = "Temperature (°F)") +
  scale_y_reverse() +
  mytheme

16.4 Transform an Axis

ggplot(chic, aes(x = date, y = temp, color = o3)) +
  geom_point() +
  labs(x = "Year", y = "Temperature (°F)") +
  scale_y_log10(limits = c(-Inf, 100)) +
  mytheme

## Warning in trans$transform(limits): 产生了NaNs

## Warning in self$trans$transform(x): 产生了NaNs

## Warning: Transformation introduced infinite values in continuous y-axis

## Warning: Removed 3 rows containing missing values (geom_point).

16.5 Circularize a Plot

chic %>%
  dplyr::group_by(season) %>%
  dplyr::summarize(across(o3,list(median = median)))

## `summarise()` ungrouping output (override with `.groups` argument)

chic %>%
  dplyr::group_by(season) %>%
  dplyr::summarize(o3 = median(o3)) %>% 
  ggplot(aes(x = season, y = o3)) +
    geom_col(aes(fill = season), color = NA) +
    labs(x = "",
         y = "Median Ozone Level") +
    coord_polar() +
    guides(fill = FALSE) +
  mytheme

## `summarise()` ungrouping output (override with `.groups` argument)

chic %>%
  dplyr::mutate(o3_avg = median(o3)) %>% 
  dplyr::filter(o3 > o3_avg) %>% 
  dplyr::mutate(n_all = n()) %>% 
  dplyr::group_by(season) %>% 
  dplyr::summarize(rel = n() / unique(n_all)) -> chic_sum

## `summarise()` ungrouping output (override with `.groups` argument)

ggplot(chic_sum, aes(x = "",y = rel)) +
  geom_col(aes(fill = season), 
           width = 1, 
           color = NA) +
  labs(x = "", 
       y = "Proportion of Days Exceeding\nthe Median Ozone Level") +
  coord_polar(theta = "y") +
  scale_fill_brewer(palette = "Set1", 
                    name = "Season:") +
  theme(axis.ticks = element_blank(),
        panel.grid = element_blank()) +
  mytheme

17 Working with Chart Types

17.1 Alternatives to a Box Plot

chic %>% 
  ggplot(aes(x = season,y = o3)) +
  geom_boxplot(aes(col = season),show.legend = FALSE) +
  labs(x = "Season", y = "Ozone") +
  geom_point(aes(col = season),alpha = 0.5) +
  scale_color_brewer(palette = "Dark2") +
  mytheme

chic %>% 
  ggplot(aes(x = season,y = o3)) +
  geom_boxplot(aes(col = season),show.legend = TRUE) +
  labs(x = "Season", y = "Ozone") +
  geom_point(aes(col = season)) +
  geom_violin(aes(col = season),fill = "gray80",size = 1, alpha = 0.5) +
  scale_color_brewer(palette = "Dark2",guide = "none") +
  coord_flip() +
  mytheme

17.2 Create a Rug Representation to a Plot

A rug represents the data of a single quantitative variable, displayed as marks along an axis. In most cases, it is used in addition to scatter plots or heatmaps to visualize the overall distribution of one or both of the variables:

ggplot(chic, aes(x = date, 
                 y = temp, 
                 color = season)) +
  geom_point(show.legend = FALSE) +
  geom_rug(show.legend = FALSE) +
  labs(x = "Year", y = "Temperature (°F)") +
  mytheme

ggplot(chic, aes(x = date,
                 y = temp, 
                 color = season)) +
  geom_point(show.legend = FALSE) +
  geom_rug(sides = "r", 
           alpha = .3, 
           show.legend = FALSE) +
  labs(x = "Year", 
       y = "Temperature (°F)") +
  mytheme

17.3 Create a Correlation Matrix

# Get lower triangle of the correlation matrix
.get_lower_tri <- function(cormat, show.diag = FALSE) {
  if (is.null(cormat)) {
    return(cormat)
  }
  cormat[upper.tri(cormat)] <- NA
  if (!show.diag) {
    diag(cormat) <- NA
  }
  return(cormat)
}

# Get upper triangle of the correlation matrix
.get_upper_tri <- function(cormat, show.diag = FALSE) {
  if (is.null(cormat)) {
    return(cormat)
  }
  cormat[lower.tri(cormat)] <- NA
  if (!show.diag) {
    diag(cormat) <- NA
  }
  return(cormat)
}

# hc.order correlation matrix
.hc_cormat_order <- function(cormat, hc.method = "complete") {
  dd <- stats::as.dist((1 - cormat) / 2)
  hc <- stats::hclust(dd, method = hc.method)
  hc$order
}

.no_panel <- function() {
  ggplot2::theme(
    axis.title.x = ggplot2::element_blank(),
    axis.title.y = ggplot2::element_blank()
  )
}


# Convert a tbl to matrix
.tibble_to_matrix <- function(x){
  x <-  as.data.frame(x)
  rownames(x) <- x[, 1]
  x <- x[, -1]
  as.matrix(x)
}
ggcorrplot1 <- function (corr, method = c("square", "circle"), type = c("full", 
    "lower", "upper"), ggtheme = ggplot2::theme_minimal, 
    title = "", show.legend = TRUE, legend.title = "Corr", 
    show.diag = FALSE, colors = c("blue", "white", 
        "red"), outline.color = "gray", hc.order = FALSE, 
    hc.method = "complete", lab = FALSE, lab_col = "black", 
    lab_size = 4, p.mat = NULL, sig.level = 0.05, insig = c("pch", 
        "blank"), pch = 4, pch.col = "black", pch.cex = 5, 
    tl.cex = 12, tl.col = "black", tl.srt = 45, digits = 2) 
{
    type <- match.arg(type)
    method <- match.arg(method)
    insig <- match.arg(insig)
    if (inherits(corr, "cor_mat")) {
        cor.mat <- corr
        corr <- .tibble_to_matrix(cor.mat)
        p.mat <- .tibble_to_matrix(attr(cor.mat, "pvalue"))
    }
    if (!is.matrix(corr) & !is.data.frame(corr)) {
        stop("Need a matrix or data frame!")
    }
    corr <- as.matrix(corr)
    corr <- base::round(x = corr, digits = digits)
    if (hc.order) {
        ord <- .hc_cormat_order(corr)
        corr <- corr[ord, ord]
        if (!is.null(p.mat)) {
            p.mat <- p.mat[ord, ord]
            p.mat <- base::round(x = p.mat, digits = digits)
        }
    }
    if (type == "lower") {
        corr <- .get_lower_tri(corr, show.diag)
        p.mat <- .get_lower_tri(p.mat, show.diag)
    }
    else if (type == "upper") {
        corr <- .get_upper_tri(corr, show.diag)
        p.mat <- .get_upper_tri(p.mat, show.diag)
    }
    corr <- reshape2::melt(corr, na.rm = TRUE)
    colnames(corr) <- c("Var1", "Var2", "value")
    corr$pvalue <- rep(NA, nrow(corr))
    corr$signif <- rep(NA, nrow(corr))
    if (!is.null(p.mat)) {
        p.mat <- reshape2::melt(p.mat, na.rm = TRUE)
        corr$coef <- corr$value
        corr$pvalue <- p.mat$value
        corr$signif <- as.numeric(p.mat$value <= sig.level)
        p.mat <- subset(p.mat, p.mat$value > sig.level)
        if (insig == "blank") {
            corr$value <- corr$value * corr$signif
        }
    }
    corr$abs_corr <- abs(corr$value) * 10
    p <- ggplot2::ggplot(data = corr, mapping = ggplot2::aes_string(x = "Var1", 
        y = "Var2", fill = "value"))
    if (method == "square") {
        p <- p + ggplot2::geom_tile(color = outline.color)
    }
    else if (method == "circle") {
        p <- p + ggplot2::geom_point(color = outline.color, shape = 21, 
            ggplot2::aes_string(size = "abs_corr")) + ggplot2::scale_size(range = c(4, 
            10)) + ggplot2::guides(size = FALSE)
    }
    p <- p + ggplot2::scale_fill_gradient2(low = colors[1], high = colors[3], 
        mid = colors[2], midpoint = 0, limit = c(-1, 1), space = "Lab", 
        name = legend.title)
    if (class(ggtheme)[[1]] == "function") {
        p <- p + ggtheme()
    }
    else if (class(ggtheme)[[1]] == "theme") {
        p <- p + ggtheme
    }
    p <- p + ggplot2::theme(axis.text.x = ggplot2::element_text(angle = tl.srt, 
        vjust = 1, size = tl.cex, hjust = 1), axis.text.y = ggplot2::element_text(size = tl.cex)) + 
        ggplot2::coord_fixed()
    label <- round(x = corr[, "value"], digits = digits)
    if (!is.null(p.mat) & insig == "blank") {
        ns <- corr$pvalue > sig.level
        if (sum(ns) > 0) 
            label[ns] <- " "
    }
    if (lab) {
        p <- p + ggplot2::geom_text(mapping = ggplot2::aes_string(x = "Var1", 
            y = "Var2"), label = label, color = lab_col, 
            size = lab_size,family = "Times New Roman")
    }
    if (!is.null(p.mat) & insig == "pch") {
        p <- p + ggplot2::geom_point(data = p.mat, mapping = ggplot2::aes_string(x = "Var1", 
            y = "Var2"), shape = pch, size = pch.cex, color = pch.col)
    }
    if (title != "") {
        p <- p + ggplot2::ggtitle(title)
    }
    if (!show.legend) {
        p <- p + ggplot2::theme(legend.position = "none")
    }
    p <- p + .no_panel()
    p
}
data(SaratogaHouses, package="mosaicData")
SaratogaHouses %>% 
  dplyr::select(where(is.numeric)) %>% 
  cor(.,use = "complete.obs") %>% 
  round(.,2) %>% 
  ggcorrplot1(hc.order = TRUE,lab = TRUE) +
  mytheme

17.4 Create a Contour Plot

ggplot(chic, aes(temp, o3)) +
  geom_density_2d() +
  labs(x = "Temperature (°F)", x = "Ozone Level") +
  mytheme

ggplot(chic, aes(temp, o3)) +
  geom_density_2d_filled(show.legend = FALSE) +
  coord_cartesian(expand = FALSE) +
  labs(x = "Temperature (°F)", x = "Ozone Level")

17.5 Create a Heatmap

ggplot(chic, aes(temp, o3)) +
  geom_hex() +
  scale_fill_distiller(palette = "YlOrRd", direction = 1) +
  labs(x = "Temperature (°F)", y = "Ozone Level") +
  mytheme

17.6 Create a Ridge Plot

library(ggridges)
ggplot(chic, aes(x = temp, y = factor(year),fill = year)) +
  geom_density_ridges(alpha = .8, color = "white",
                      scale = 2.5, rel_min_height = .01,show.legend = FALSE) +
  labs(x = "Temperature (°F)", y = "Year") +
  mytheme

## Picking joint bandwidth of 5.23

18 Working with Ribbons (AUC, CI, etc.)

chic$o3run <- as.numeric(stats::filter(chic$o3, rep(1/30, 30), sides = 2))

ggplot(chic, aes(x = date, y = o3run)) +
   geom_line(color = "chocolate", lwd = .8) +
   labs(x = "Year", y = "Ozone") +
  mytheme

## Warning: Removed 29 row(s) containing missing values (geom_path).

chic$mino3 <- chic$o3run - sd(chic$o3run, na.rm = TRUE)
chic$maxo3 <- chic$o3run + sd(chic$o3run, na.rm = TRUE)

ggplot(chic, aes(x = date, y = o3run)) +
   geom_ribbon(aes(ymin = mino3, 
                   ymax = maxo3), alpha = .5,
               fill = "darkseagreen3",
               color = "transparent") +
   geom_line(color = "aquamarine4", 
             lwd = .7) +
   labs(x = "Year", y = "Ozone") +
  mytheme

## Warning: Removed 29 row(s) containing missing values (geom_path).

19 Working with Smoothings

19.1 Default: Adding a LOESS or GAM Smoothing

ggplot(chic, aes(x = date, y = temp)) +
  labs(x = "Year", y = "Temperature (°F)") +
  stat_smooth() +
  geom_point(color = "gray40", alpha = .5) +
  mytheme

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'

19.2 Adding a Linear Fit

ggplot(chic, aes(x = temp, 
                 y = death)) +
   labs(x = "Temperature (°F)",
        y = "Deaths") +
   geom_smooth(method = "lm", 
               se = FALSE, 
               color = "firebrick", 
               size = 1.3) +
   geom_point(color = "gray40", alpha = .5) +
  mytheme

## `geom_smooth()` using formula 'y ~ x'

19.3 Specifying the Formula for Smoothing

ggplot(chic, aes(x = o3, y = temp)) + 
  geom_point(color = "gray40", alpha = .3) +
  geom_smooth(
    method = "lm",
    formula = y ~ x + I(x^2) + I(x^3) + I(x^4) + I(x^5),
    color = "black",
    fill = "firebrick"
  ) +
  labs(x = "Ozone Level", y = "Temperature (°F)") +
  mytheme

cols <- c("darkorange2", "firebrick", "dodgerblue3")

ggplot(chic, aes(x = date, y = temp)) +
  geom_point(color = "gray40", alpha = .3) +
  labs(x = "Year", y = "Temperature (°F)") +
  stat_smooth(aes(col = "10"), 
              method = "gam", 
              formula = y ~ s(x, k = 10),
              se = FALSE, size = 1.3) +
  stat_smooth(aes(col = "30"), 
              method = "gam", 
              formula = y ~ s(x, k = 30),
              se = FALSE, size = 1) +
  stat_smooth(aes(col = "50"),
              method = "gam", 
              formula = y ~ s(x, k = 50),
              se = FALSE, size = .8) +
  scale_color_manual(name = "k", values = cols) +
  mytheme

20 Working with Interactive Plots

20.1 Combination of {ggplot2} and {shiny}

20.2 Plot.ly via {plotly} and {ggplot2}

g <- ggplot(chic, aes(date, temp)) +
  geom_line(color = "grey") +
  geom_point(aes(color = season)) +
  scale_color_brewer(palette = "Dark2", guide = "none") +
  labs(x = NULL, y = "Temperature (°F)") +
  theme_bw() +
  mytheme
g

library(plotly)

ggplotly(g)

20.3 ggiraph and ggplot2

{ggiraph} is an R package that allows you to create dynamic {ggplot2} graphs. This allows you to add tool tips, animations and JavaScript actions to the graphics. The package also allows the selection of graphical elements when used in Shiny applications.

library(ggiraph)

g <- ggplot(chic, aes(date, temp)) +
  geom_line(color = "grey") +
  geom_point_interactive(
    aes(color = season, tooltip = season, data_id = season)
  ) +
  scale_color_brewer(palette = "Dark2", guide = "none") +
  labs(x = NULL, y = "Temperature (°F)") +
  theme_bw() +
  mytheme

girafe(ggobj = g)

20.4 Highcharts via {highcharter}

library(highcharter)

hchart(chic, "scatter", hcaes(x = date, y = temp, group = season))

20.5 Echarts via {echarts4r}

library(echarts4r)

chic %>% 
  e_charts(date) %>% 
  e_scatter(temp, symbol_size = 7) %>% 
  e_visual_map(temp) %>% 
  e_y_axis(name = "Temperature (°F)") %>% 
  e_legend(FALSE)

21 Remarks, Tipps & Resources

21.1 Using ggplot() in Loops and Functions

The grid-based graphics functions in lattice and ggplot2 create a graph object. When you use these functions interactively at the command line, the result is automatically printed, but in source() or inside your own functions you will need an explicit print() statement, i.e. print(g) in most of our examples.

21.2 Additional Resources

• “ggplot2: Elegant Graphics for Data Analysis” by Hadley Wickham, available via open-access!
• “Fundamentals of Data Visualization” by Claus O. Wilke about data visualization in general but using {ggplot2}.
• “Cookbook for R” by Winston Chang with recipes to produce R plots
• Gallery of the Top 50 ggplot2 visualizations
• Gallery of {ggplot2} extension packages
• How to extend {ggplot2} by Hadley Wickham
• The fantastic R4DS Online Learning Community that offers help and mentoring for all things related to the content of the “R for Data Science” book by Hadley Wickham