The package pubtheme contains a ggplot theme theme_pub for
creating data journalism-style data visualizations with color palettes
and formatting similar to those used by media organizations like BBC, NY
Times, and ESPN. Several templates for scatter plot, line plots, etc.,
are provided below for easy copying/pasting. A helpful function pub
can be used to reduce then amount of code that needs to be typed when
the user is comfortable with the default settings.
Organization-specific color palettes and logos can be used as well via
the package orgthemes. See https://github.com/bmacGTPM/orgthemes.
If you don’t have the package devtools, install it using
install.packages('devtools'). If you have devtools, you can install
the GitHub version of pubtheme with:
devtools::install_github("bmacGTPM/pubtheme")If you get an error about download method, try changing this option before installing.
options(download.file.method = 'libcurl')Load the package using
library(pubtheme)as usual. The theme will change some of your ggplot defaults the first time you use it. To change them back, restart R, or use
restore.ggplot.defaults()at any time. It is recommended that you update your version of
tidyverse and especially ggplot2 to use this package.
dg = mtcars %>%
select(wt, mpg, cyl) %>%
mutate(Cylinders = as.factor(cyl)) %>%
rename(MPG = mpg)
title = "Title in Upper Lower"
g = ggplot(dg,
aes(x = wt,
y = MPG,
color = Cylinders,
size = MPG)) +
geom_point() +
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption with more info, X handle, or shameless promotion of pubtheme",
x = 'Horizontal Axis Label in Upper Lower',
y = 'Vertical Axis Label in Upper Lower') +
scale_x_continuous(limits = c(0, 6),
breaks = c(0, 3, 6),
oob = squish,
labels = comma) +
scale_y_continuous(limits = c(0,40),
breaks = c(0,20,40),
oob = squish,
labels = comma) +
scale_size(range = c(2, 6)) +
coord_cartesian(clip = 'off',
expand = F) +
theme_pub(type = 'scatter')
print(g)
## Save to a file using base_size = 36
gg = g +
scale_size(range = c(6, 18)) +
theme_pub(type = 'scatter',
base_size = 36)
ggsave(filename = paste0("img/", gsub("%", " Perc", title), ".jpg"),
plot = gg,
width = 20, ## do not change
height = 20, ## can change from 20 if desired
units = 'in', ## do not change
dpi = 72) ## do not change
g.scatter = g ## save for later
You must have a subfolder called img in order for the ggsave chunk
above to work.
Note that the default is base_size = 12, which works well when viewing
the image in RStudio. Use ggsave and base_size = 36 when saving an
image instead of exporting from the RStudio viewer. Do not adjust the
width = 20 in ggsave.
Do not change width = 20, units = 'in', or dpi = 72. Height
can be adjusted if desired. A square image is often preferred, so when
in doubt, keep height at 20.
Upper Lower means First letter of each word is capitalized. The option
expand = FALSE removes the default padding. The option
breaks=c(0, 3, 6) sets 3 lines at left, middle, and right. You can
certainly add lines if there is a reason to, but when in doubt you can
stick with just 3 lines (left/middle/right) only. Similarly, for the
y-axis, top/middle/bottom only.
You’ll notice a scale_size(range = c(6, 18) when preparing the plot to
be saved. If you are using size inside aes(), you’ll need that
change the scale, otherwise the points will be too small.
We explicitly specified the scale* and coord_cartesian above. To use
the default settings in pubtheme, you can save a lot of typing by
using the function pub, which applies theme_pub and also
automatically adds scale* and coord* similar to above. The function
also aligns the legend with the left side of the title and subtitle.
title = "Title in Upper Lower"
g = ggplot(dg,
aes(x = wt,
y = MPG,
color = Cylinders,
size = MPG)) +
geom_point() +
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
x = 'Horizontal Axis Label in Upper Lower',
y = 'Vertical Axis Label in Upper Lower')
g %>%
pub(xlim = c(0, 6),
ylim = c(0, 40))
## Save to a file using base_size = 36
gg = g %>%
pub(xlim = c(0, 6),
ylim = c(0, 40),
base_size = 36)
ggsave(filename = paste0("img/",
gsub("%", " Perc", title),
".jpg"),
plot = gg,
width = 20, ## do not change
height = 20, ## can change from 20 if desired
units = 'in', ## do not change
dpi = 72) ## do not change
To save to a file, we again need base_size = 36. We simply copy and
paste the pub code and add base_size = 36.
Make a correlation plot in the look of pubtheme. Since corrplot
gives a corrplot object, pub can’t be used with it, so we have to
make a correlation plot from scratch using ggcorrplot.
We can instead use geom_tile.
## choose order of variables
cols = sort(unique(colnames(mtcars)))
corr <- round(cor(mtcars[,cols]), 2)
head(corr,2)
#> am carb cyl disp drat gear hp mpg qsec vs wt
#> am 1.00 0.06 -0.52 -0.59 0.71 0.79 -0.24 0.60 -0.23 0.17 -0.69
#> carb 0.06 1.00 0.53 0.39 -0.09 0.27 0.75 -0.55 -0.66 -0.57 0.43
# title = "Title in Upper Lower"
# g = ggcorrplot(corr) +
# scale_fill_gradientn(colors = c('red4',
# pubred,
# publightred,
# pubbackgray,
# publightblue,
# pubblue,
# 'navy'),
# na.value = pubmediumgray, ## same color as below
# oob = squish,
# breaks = c(-1, 0, 1),
# limits = c(-1, 1)) +
# labs(title = title,
# subtitle = 'Optional Subtitle In Upper Lower',
# #caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
# x = 'Day (Optional Axis Label in Upper Lower)',
# y = NULL, ## Optional
# fill = 'Value') #+
# g
#
# g %>%
# pub(type = 'grid', base_size = 10) +
# theme(axis.text.x.top = element_text(angle = 90,
# hjust = 0,
# vjust = 0.7))
dg = corr %>%
as.data.frame() %>%
## longer format
rownames_to_column(var = 'x') %>%
pivot_longer(cols = -x,
names_to = 'y',
values_to = 'value') %>%
## order them however you'd like
mutate(x = factor(x, levels = rev(sort(unique(x)))),
y = factor(y, levels = sort(unique(y))))
title = "Title in Upper Lower"
g = ggplot(dg) +
geom_tile(aes(x = x,
y = y,
fill = value),
linewidth = 0.4,
show.legend = T,
color = pubdarkgray) +
scale_fill_gradientn(colors = c('red4',
pubred,
publightred,
'white', ## or 'pubbackgray'
publightblue,
pubblue,
'navy'),
na.value = pubmediumgray, ## same color as below
oob = squish,
breaks = c(-1, 0, 1),
limits = c(-1, 1)) +
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
x = 'Day (Optional Axis Label in Upper Lower)',
y = NULL, ## Optional
fill = 'Value')
g %>%
pub(type = 'grid') +
theme(axis.text.x.top = element_text(angle = 90,
hjust = 0,
vjust = 0.3))
gg = g %>%
pub(type = 'grid',
base_size = 36)
ggsave(filename = paste0("img/", gsub("%", " Perc", title), ".jpg"),
plot = gg,
width = 20, ## do not change
height = 24, ## can change from 20 if desired. We use 12 here to make the tiles square
units = 'in', ## do not change
dpi = 72) ## do not change
Adding rectangles around clusters, as is often done in corrplot.
# ## note that the function corrRect.hclust is used there
# corrplot::corrplot
#
# ## note that this converts corr to a distance matrix, and then uses cutree to get the clusters
# corrplot::corrRect.hclust
corr = cor(mtcars)
ds = as.dist(1-corr)
dh = hclust(ds)
hc = cutree(dh, k = 4)
dr = data.frame(order = dh$order,
cluster = hc) %>%
mutate(cluster = factor(cluster,
levels = c(1,3,4,2))) %>% ## this order looks better
arrange(cluster, order) %>%
mutate(x = 1:n(),
y = n():1) ## gotta reverse the order
dr
#> order cluster x y
#> drat 3 1 1 11
#> am 5 1 2 10
#> gear 9 1 3 9
#> mpg 11 1 4 8
#> vs 1 3 5 7
#> qsec 8 3 6 6
#> carb 10 4 7 5
#> hp 2 2 8 4
#> disp 4 2 9 3
#> cyl 6 2 10 2
#> wt 7 2 11 1
dg = corr %>%
as.data.frame() %>%
## longer format
rownames_to_column(var = 'x') %>%
pivot_longer(cols = -x,
names_to = 'y',
values_to = 'value') %>%
## order them the same way as dr
mutate(x = factor(x, levels = rownames(dr)),
y = factor(y, levels = rev(rownames(dr))))
polys = dr %>%
group_by(cluster) %>%
summarise(xmin = min(x),
xmax = max(x),
ymin = min(y),
ymax = max(y)) %>%
mutate(xmin = xmin - 0.5,
xmax = xmax + 0.5,
ymin = ymin - 0.5,
ymax = ymax + 0.5,
linewidth = 1.5)
polys
#> # A tibble: 4 × 6
#> cluster xmin xmax ymin ymax linewidth
#> <fct> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 0.5 4.5 7.5 11.5 1.5
#> 2 3 4.5 6.5 5.5 7.5 1.5
#> 3 4 6.5 7.5 4.5 5.5 1.5
#> 4 2 7.5 11.5 0.5 4.5 1.5
g = ggplot(dg) +
## Tiles
geom_tile(aes(x = x,
y = y,
fill = value),
linewidth = 0.4,
show.legend = T,
color = pubdarkgray) +
## Rectangles
geom_rect(data = polys,
aes(xmin = xmin,
xmax = xmax,
ymin = ymin,
ymax = ymax,
group = cluster,
linewidth = linewidth),
fill = NA,
color = 'black',
linejoin = 'mitre', ## mitre or round
lineend = 'square') + ## square or round
guides(linewidth = 'none') +
scale_fill_gradientn(colors = c('red4',
pubred,
publightred,
pubbackgray,
publightblue,
pubblue,
'navy'),
na.value = pubmediumgray, ## same color as below
oob = squish,
breaks = c(-1, 0, 1),
limits = c(-1, 1)) +
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
x = 'Day (Optional Axis Label in Upper Lower)',
y = NULL, ## Optional
fill = 'Value')
g %>%
pub(type = 'grid')
gg = g %>%
pub(type = 'grid',
base_size = 36)
ggsave(filename = paste0("img/", gsub("%", " Perc", title), ".jpg"),
plot = gg,
width = 20, ## do not change
height = 24, ## can change from 20 if desired. We use 12 here to make the tiles square
units = 'in', ## do not change
dpi = 72) ## do not change
This could be made with ggcorrplot as well. I’m not sure if the method
above or below will be more convenient, so I’m leaving both examples
here for now.
library(ggcorrplot)
corr = cor(mtcars)
ds = as.dist(1-corr)
dh = hclust(ds)
hc = cutree(dh, k = 4)
dr = data.frame(order = dh$order,
cluster = hc) %>%
mutate(cluster = factor(cluster,
levels = c(1,3,4,2))) %>% ## this order looks better
arrange(cluster, order) %>%
mutate(x = 1:n(),
y = n():1) ## gotta reverse the order
dr
#> order cluster x y
#> drat 3 1 1 11
#> am 5 1 2 10
#> gear 9 1 3 9
#> mpg 11 1 4 8
#> vs 1 3 5 7
#> qsec 8 3 6 6
#> carb 10 4 7 5
#> hp 2 2 8 4
#> disp 4 2 9 3
#> cyl 6 2 10 2
#> wt 7 2 11 1
polys = dr %>%
group_by(cluster) %>%
summarise(xmin = min(x),
xmax = max(x),
ymin = min(y),
ymax = max(y)) %>%
mutate(xmin = xmin - 0.5,
xmax = xmax + 0.5,
ymin = ymin - 0.5,
ymax = ymax + 0.5,
linewidth = 1.5)
polys
#> # A tibble: 4 × 6
#> cluster xmin xmax ymin ymax linewidth
#> <fct> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 0.5 4.5 7.5 11.5 1.5
#> 2 3 4.5 6.5 5.5 7.5 1.5
#> 3 4 6.5 7.5 4.5 5.5 1.5
#> 4 2 7.5 11.5 0.5 4.5 1.5
corr = corr[ rownames(dr),
rev(rownames(dr))]
title = "Title in Upper Lower"
g = ggcorrplot(corr,
outline.color = pubbackgray) +
geom_rect(data = polys,
aes(x = NULL,
y = NULL,
xmin = xmin,
xmax = xmax,
ymin = ymin,
ymax = ymax,
group = cluster,
linewidth = linewidth
),
fill = NA,
color = 'black',
linejoin = 'mitre', ## mitre or round
lineend = 'square') + ## square or round
guides(linewidth = 'none') +
scale_fill_gradientn(colors = c('red4',
pubred,
publightred,
pubbackgray,
publightblue,
pubblue,
'navy'),
na.value = pubmediumgray, ## same color as below
oob = squish,
breaks = c(-1, 0, 1),
limits = c(-1, 1)) +
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
#caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
x = 'Day (Optional Axis Label in Upper Lower)',
y = NULL, ## Optional
fill = 'Value') #+
g %>%
pub(type = 'grid', base_size = 10) #+
# theme(axis.text.x.top = element_text(angle = 90,
# hjust = 0,
# vjust = 0.7))
gg = g %>%
pub(type = 'grid',
base_size = 36) #+
# theme(axis.text.x.top = element_text(angle = 90,
# hjust = 0,
# vjust = 0.7))
ggsave(filename = paste0("img/", gsub("%", " Perc", title), ".jpg"),
plot = gg,
width = 20, ## do not change
height = 24, ## can change from 20 if desired. We use 12 here to make the tiles square
units = 'in', ## do not change
dpi = 72) ## do not change
library(GGally) ## Needed for ggpairs function
dg = mtcars %>%
select(mpg, cyl, wt, carb) %>%
mutate(Cylinders = factor(cyl))
title = 'Title in Upper Lower'
g = ggpairs(dg,
aes(color = Cylinders,
fill = Cylinders),
columns = c('mpg', 'wt', 'carb'),
diag = list(continuous = pub.density)) +
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
x = 'Horizontal Axis Label in Upper Lower',
y = 'Vertical Axis Label in Upper Lower') +
theme_pub(type = 'pairs')
print(g)
## Save to a file using base_size = 36
gg = g +
theme_pub(type = 'pairs',
base_size = 36)
ggsave(filename = paste0("img/", gsub("%", " Perc", title), ".jpg"),
plot = gg,
width = 20, ## do not change
height = 20, ## can change from 20 if desired
units = 'in', ## do not change
dpi = 72) ## do not change
Note that since the object g resulting from using ggpairs is not a
ggplot object, pub can’t be used with it.
Since name and value will be more common column names when using
these in the wild, we’ll rename some columns to be name and value, to
simplify copying and pasting later.
Continuous variables for x seem to be more common, so we’ll convert
date to days for this example, so that copying and pasting later becomes
easier. We’ll use toupper() to avoid using variables with all
lowercase letters in the legend.
dg = economics_long %>%
mutate(name = toupper(variable),
days = as.numeric(date - min(date)),
value = value01) %>%
select(date, days, name, value)
head(dg)
#> # A tibble: 6 × 4
#> date days name value
#> <date> <dbl> <chr> <dbl>
#> 1 1967-07-01 0 PCE 0
#> 2 1967-08-01 31 PCE 0.000265
#> 3 1967-09-01 62 PCE 0.000762
#> 4 1967-10-01 92 PCE 0.000471
#> 5 1967-11-01 123 PCE 0.000916
#> 6 1967-12-01 153 PCE 0.00157
title = "Title in Upper Lower"
g = ggplot(dg,
aes(x = days,
y = value,
color = name)) +
geom_line() +
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
x = 'Horizontal Axis Label in Upper Lower',
y = 'Vertical Axis Label in Upper Lower',
color = 'Legend Label') +
guides(color = guide_legend(nrow = 2))
g %>%
pub(type = 'line',
ylim = c(0, 1)) +
theme(legend.text.align = 0)
## Save to a file using base_size = 36
gg = g %>%
pub(type = 'line',
ylim = c(0, 1),
base_size = 36) +
theme(legend.text.align = 0)
ggsave(filename = paste0("img/", gsub("%", " Perc", title), ".jpg"), ## must have a subfolder called 'img'
plot = gg,
width = 20, ## do not change
height = 20, ## can change from 20 if desired
units = 'in', ## do not change
dpi = 72) ## do not change 
Note that once again we set breaks for the y-axis at the top, middle, and bottom.
You can use the same code as Line Plot above (except use x = date),
and pub will detect the date scale and format appropriately. You can
change the format of the labels as shown below with xlabels.
title = "Title in Upper Lower"
g = ggplot(dg,
aes(x = date,
y = value,
color = name)) +
geom_line() +
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
x = 'Horizontal Axis Label in Upper Lower',
y = 'Vertical Axis Label in Upper Lower',
color = 'Legend Label') +
guides(color = guide_legend(nrow = 2))
g %>%
pub(type = 'line',
ylim = c(0, 1),
xbreaks = as.Date(c('1970-01-01',
'1990-01-01',
'2010-01-01')), ## optional
xlabels = function(x) format(x, '%b%e, %Y')) + ## optional
theme(legend.text.align = 0)
dg = economics %>%
filter(date <= '2008-01-01') %>%
rename(value = unemploy)
title = "Title in Upper Lower"
g = ggplot(dg,
aes(x = value)) +
geom_histogram(fill = pubblue,
color = pubbackgray,
binwidth = 500) + ## set a reasonable binwidth
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
x = 'Horizontal Axis Label in Upper Lower', ## Required.
y = 'Count')
g %>%
pub(type = 'hist')
## Save to a file using base_size = 36
gg = g %>%
pub(type = 'hist',
base_size = 36)
ggsave(filename = paste0("img/", gsub("%", " Perc", title), ".jpg"),
plot = gg,
width = 20, ## do not change
height = 20, ## can change from 20 if desired
units = 'in', ## do not change
dpi = 72) ## do not change
The binwidth will almost surely need to be changed for your data.
We’ll use the mtcars data again, with some modifications. For
cylinder, we’ll add -cylinder to the numbers so it looks nice. We’ll
then convert it a factor so that we can specify the order. We’ll also
create a column called max which controls the length of the lightgray
bars in the background. Finally, we’ll rename cyl and mpg to name
and value, which will be convenient when copying and pasting this
code.
dg = mtcars %>%
group_by(cyl) %>%
summarise(mpg = mean(mpg)) %>%
mutate(cyl = paste0(cyl, '-cylinder'),
cyl = factor(cyl,
levels = c('8-cylinder',
'6-cylinder',
'4-cylinder'))) %>% ## for background cars
rename(name = cyl,
value = mpg)
title = "Title in Upper Lower"
g = ggplot(dg,
aes(x = value,
y = name,
label = round(value,2))) +
geom_col(aes(x = 30),
fill = publightgray,
width = 0.8) + ## optional background bars.
geom_col(width = 0.8) +
geom_text(hjust = -0.1) + ## optional numbers with reasonable number of digits
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
x = 'Horizontal Axis Label in Upper Lower', ## Optional.
y = NULL) ## Optional. Upper Lower.
g %>%
pub(type = 'bar')
## Save to a file using base_size = 36
gg = g %>%
pub(type = 'bar',
base_size = 36)
ggsave(filename = paste0("img/", gsub("%", " Perc", title), ".jpg"), ## must have a subfolder called 'img'
plot = gg,
width = 20, ## do not change
height = 15, ## can change from 20 if desired. We use 15 here b/c there are only 3 bars
units = 'in', ## do not change
dpi = 72) ## do not change
If you are using digits next to the bars, you can increase the max so
the text fits.
You may want to remove x and y axis titles. If not used, use
x = NULL and/or y = NULL above. Do not use x = '' and/or y = ''.
If you do use axes titles, they should be in Upper Lower.
dg = airquality %>%
mutate(Month = month.abb[Month],
Month = factor(Month, levels = rev(month.abb[month.abb %in% Month])),
Day = factor(Day, levels = 1:31)) %>%
rename(x = Day,
y = Month,
value = Temp)
## Do this so that all combos have a tile
dg = dg %>%
complete(x,
y,
fill = list(value = NA))
head(dg)
#> # A tibble: 6 × 6
#> x y Ozone Solar.R Wind value
#> <fct> <fct> <int> <int> <dbl> <int>
#> 1 1 Sep 96 167 6.9 91
#> 2 1 Aug 39 83 6.9 81
#> 3 1 Jul 135 269 4.1 84
#> 4 1 Jun NA 286 8.6 78
#> 5 1 May 41 190 7.4 67
#> 6 2 Sep 78 197 5.1 92
title = "Title in Upper Lower"
g = ggplot(dg,
aes(x = x,
y = y,
fill = value,
alpha = '')) + ## hacky way to add a legend for NA values. See below
geom_tile(linewidth = 0.4,
show.legend = T,
color = pubdarkgray) +
scale_fill_gradient(low = pubgradgray,
high = pubblue,
na.value = pubmediumgray, ## same color as below
oob = squish,
breaks = c(60, 75, 90)) +
## hacky way to add a legend for NA values
scale_alpha_manual(values = NA) +
guides(alpha = guide_legend(
title = "No data",
override.aes = list(fill = pubmediumgray))) + ## same color as above
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
x = 'Day (Optional Axis Label in Upper Lower)',
y = NULL, ## Optional
fill = 'Value')
g %>%
pub(type = 'grid',
xbreaks = seq(2, 32, by = 2))
## Save to a file using base_size = 36
gg = g %>%
pub(type = 'grid',
xbreaks = seq(2, 32, by=2),
base_size = 36)
ggsave(filename = paste0("img/", gsub("%", " Perc", title), ".jpg"),
plot = gg,
width = 20, ## do not change
height = 12, ## can change from 20 if desired. We use 12 here to make the tiles square
units = 'in', ## do not change
dpi = 72) ## do not change
dg = economics_long %>%
mutate(name = toupper(variable),
days = as.numeric(date - min(date)),
y= value01,
x = as.character(date)) %>%
select(x, name, y) %>%
filter(x %in% range(x),
name != 'PCE') %>% ## keep first and last date
mutate(time = ifelse(x == min(x), "", "end")) %>%
pivot_wider(names_from = time,
values_from = c(x, y),
names_sep = '') %>%
mutate(diff = yend - y,
perc = diff/y*100,
label1 = paste0(name, ', ',
round(y, 2)),
label2 = paste0(
round(yend, 2), ' (',
sprintf("%+.2f", diff), '), ', ## show a plus when positive
name
))title = "Title in Upper Lower"
g = ggplot(dg,
aes(x = x,
y = y,
color = name,
size = 4,
linewidth = .25)) +
## lines
geom_segment(aes(xend = xend,
yend = yend)) +
## text labels
geom_text_repel(aes(label = label1,
color = name),
#color = pubtextgray,
nudge_x = -0.08,
hjust = 1,
vjust = 0.5,
direction = 'y',
min.segment.length = 1) +
geom_text_repel(aes(x = xend,
y = yend,
label = label2,
color = name),
#color = pubtextgray,
nudge_x = 0.08,
hjust = 0,
vjust = 0.5,
direction = 'y',
min.segment.length = 1) +
## points
geom_point(show.legend = F) +
geom_point(show.legend = F,
aes(x = xend,
y = yend)) +
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
x = 'Horizontal Axis Label in Upper Lower', ## Optional.
y = NULL) + ## Optional. Upper Lower.
guides(size = 'none',
linewidth = 'none',
color = 'none')
g %>%
pub(type = 'slope')
## Save to a file using base_size = 36
gg = g %>%
pub(type = 'slope',
base_size = 36)
ggsave(filename = paste0("img/", gsub("%", " Perc", title), ".jpg"), ## must have a subfolder called 'img'
plot = gg,
width = 20, ## do not change
height = 20, ## can change from 20 if desired. We use 15 here because there are only 5 barbells
units = 'in', ## do not change
dpi = 72) ## do not change
We’ll make a horizontal lollipop plot. It can be used an alternative to a bar plot, and it is often preferred, especially when the visualization will eventually be printed since the lollipop plot used far less ink/toner.
dg = airquality %>%
mutate(Month = month.abb[Month],
Month = factor(Month,
levels = rev(month.abb))) %>%
group_by(Month) %>%
summarise(Temp = mean(Temp)) %>%
rename(name = Month,
value = Temp)
title = "Title in Upper Lower"
g = ggplot(dg,
aes(x = value,
y = name,
label = round(value,2),
size = 1, ## these are constant put these in aes() anyway
linewidth = .75)) + ## so they change when base_size changes
geom_segment(aes(x = 0,
xend = value,
y = name,
yend = name),
color = pubred) +
geom_point(color = pubred,
show.legend = F) +
geom_text(hjust = -0.3) + ## optional numbers with reasonable number of digits
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
x = 'Horizontal Axis Label in Upper Lower', ## Optional.
y = NULL) + ## Optional. Upper Lower.
guides(size = 'none',
linewidth = 'none')
g %>%
pub(type = 'pop',
xlim = c(0, 120))
## Save to a file using base_size = 36
gg = g %>%
pub(type = 'pop',
xlim = c(0, 120),
base_size = 36)
ggsave(filename = paste0("img/", gsub("%", " Perc", title), ".jpg"), ## must have a subfolder called 'img'
plot = gg,
width = 20, ## do not change
height = 12, ## can change from 20 if desired. We use 12 here because there are only 5 lollipops
units = 'in', ## do not change
dpi = 72) ## do not change
Same plot using geom_linerange instead of geom_segment. We have to
switch the x and y aesthetics and use coord_flip.
# title = "Title in Upper Lower"
# g = ggplot(dg,
# aes(x = name,
# y = value,
# label = round(value,2),
# size = 1, ## these are constant put these in aes() anyway
# linewidth = .75)) + ## so they change when base_size changes
# geom_linerange(aes(ymin = 0,
# ymax = value),
# color = pubred) #+
# # geom_point(color = pubred,
# # show.legend = F) +
# # geom_text(vjust = -0.3) + ## optional numbers with reasonable number of digits
# # coord_flip() +
# # labs(title = title,
# # subtitle = 'Optional Subtitle In Upper Lower',
# # caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
# # x = 'Horizontal Axis Label in Upper Lower', ## Optional.
# # y = NULL) + ## Optional. Upper Lower.
# # guides(size = 'none',
# # linewidth = 'none')
#
# g %>%
# pub(type = 'pop',
# xlim = c(0, 120), )
#
# ## Save to a file using base_size = 36
# gg = g %>%
# pub(type = 'pop',
# xlim = c(0, 120),
# base_size = 36)
#
# ggsave(filename = paste0("img/", gsub("%", " Perc", title), ".jpg"), ## must have a subfolder called 'img'
# plot = gg,
# width = 20, ## do not change
# height = 12, ## can change from 20 if desired. We use 12 here because there are only 5 lollipops
# units = 'in', ## do not change
# dpi = 72) ## do not changeThis still uses type = 'pop' but we’ll use a different template for
copying/pasting.
dg = data.frame(name = 0:10,
value = dbinom(0:10, 10, .5))
title = "Title in Upper Lower"
g = ggplot(dg,
aes(x = name,
y = value,
label = round(value,2),
size = 5,
linewidth = 0.5)) +
geom_point(color = pubred) +
geom_segment(aes(x = name,
xend = name,
y = 0,
yend = value),
color = pubred) +
geom_text(vjust = -1) + ## optional numbers with reasonable number of digits
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
x = 'Horizontal Axis Label in Upper Lower', ## Optional.
y = NULL) + ## Optional. Upper Lower.
guides(size = 'none',
linewidth = 'none')
g %>%
pub(type = 'pop',
xlim = c(0, 10),
ylim = c(0, .3),
xbreaks = 0:10)
## Save to a file using base_size = 36
gg = g %>%
pub(type = 'pop',
xlim = c(0, 10),
ylim = c(0, .3),
xbreaks = 0:10,
base_size = 36)
ggsave(filename = paste0("img/", gsub("%", " Perc", title), ".jpg"), ## must have a subfolder called 'img'
plot = gg,
width = 20, ## do not change
height = 15, ## can change from 20 if desired. We choose 15 here b/c the extra space isn't needed
units = 'in', ## do not change
dpi = 72) ## do not change
This still uses type = 'pop' but we’ll use a different template for
copying/pasting.
dg = airquality %>%
mutate(Month = month.abb[Month],
Month = factor(Month,
levels = rev(month.abb))) %>%
group_by(Month) %>%
summarise(x = min(Temp),
xend = max(Temp)) %>%
rename(name = Month)
title = "Title in Upper Lower"
g = ggplot(dg,
aes(x = x,
y = name,
size = 4,
linewidth = .5)) +
geom_point(color = pubred) +
geom_point(color = pubred,
aes(x = xend)) +
geom_segment(aes(xend = xend,
yend = name),
color = pubred) +
geom_text(aes(label = round(x, 2)),
hjust = 1.5) + ## optional numbers with reasonable number of digits
geom_text(aes(x = xend,
label = round(xend, 2)),
hjust = -0.5) + ## optional numbers with reasonable number of digits
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
x = 'Horizontal Axis Label in Upper Lower', ## Optional.
y = NULL) + ## Optional. Upper Lower.
guides(size = 'none',
linewidth = 'none')
g %>%
pub(type = 'pop',
xlim = c(0, 120))
## Save to a file using base_size = 36
gg = g %>%
pub(type = 'pop',
xlim = c(0, 120),
base_size = 36)
ggsave(filename = paste0("img/", gsub("%", " Perc", title), ".jpg"), ## must have a subfolder called 'img'
plot = gg,
width = 20, ## do not change
height = 15, ## can change from 20 if desired. We use 15 here because there are only 5 barbells
units = 'in', ## do not change
dpi = 72) ## do not change
It is often desirable to visualize regression coefficients using a dot and whiskers plot instead of showing a table of coefficients and standard errors. We’ll make up a regression model and demonstrate that here.
This still uses type = 'pop' but we’ll use a different template for
copying/pasting.
## standardize predictors so they are roughly the same scale
d = mtcars %>%
mutate(wt = scale(wt),
cyl = scale(cyl),
disp = scale(disp),
hp = scale(hp))
m1 = lm(mpg ~ wt + cyl + disp + hp,
data = d)
#summary(m1)
dg = summary(m1)$coefficients %>%
as.data.frame() %>%
rownames_to_column(var = 'var') %>%
rename(coef = Estimate,
se = `Std. Error`) %>%
select(var,
coef,
se) %>%
filter(var != '(Intercept)') %>%
mutate(var = toupper(var))
title = "Title in Upper Lower"
g = ggplot(dg,
aes(x = coef,
y = var,
size = 4,
linewidth = 0.5)) +
geom_segment(aes(x = coef - se,
xend = coef + se,
y = var,
yend = var),
color = pubred) +
geom_point(color = pubred) +
geom_text(aes(label = round(coef, 2)),
vjust = -1,
nudge_y = 0) +
geom_vline(xintercept = 0,
color = pubmediumgray) +
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
x = 'Coefficient',
y = NULL) + ## Optional.
guides(size = 'none',
linewidth = 'none')
g %>%
pub(type = 'dot',
xlim = c(-5, 5))
## Save to a file using base_size = 36
gg = g %>%
pub(type = 'dot',
xlim = c(-5, 5),
base_size = 36)
ggsave(filename = paste0("img/", gsub("%", " Perc", title), ".jpg"),
plot = gg,
width = 20, ## do not change
height = 10, ## can change from 20 if desired. We use 10 here because there are only 4 coefficients.
units = 'in', ## do not change
dpi = 72) ## do not change
Use the same data as above
## standardize predictors so they are roughly the same scale
d = mtcars %>%
mutate(wt = scale(wt),
cyl = scale(cyl),
disp = scale(disp),
hp = scale(hp))
m1 = lm(mpg ~ wt + cyl + disp + hp,
data = d)
#summary(m1)
dg = summary(m1)$coefficients %>%
as.data.frame() %>%
rownames_to_column(var = 'var') %>%
rename(coef = Estimate,
se = `Std. Error`) %>%
select(var,
coef,
se) %>%
filter(var != '(Intercept)') %>%
mutate(var = toupper(var))
title = "Title in Upper Lower"
g = ggplot(dg,
aes(x = coef,
y = var,
size = 4,
linewidth = 0.5)) +
geom_errorbarh(aes(xmin = coef - se,
xmax = coef + se),
color = pubred,
height = 0.2) +
geom_point(color = pubred) +
geom_text(aes(label = round(coef, 2)),
vjust = -1,
nudge_y = 0) +
geom_vline(xintercept = 0,
color = pubmediumgray) +
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
x = 'Coefficient',
y = NULL) + ## Optional.
guides(size = 'none',
linewidth = 'none')
g %>%
pub(type = 'dot',
xlim = c(-5, 5))
## Save to a file using base_size = 36
gg = g %>%
pub(type = 'dot',
xlim = c(-5, 5),
base_size = 36)
ggsave(filename = paste0("img/", gsub("%", " Perc", title), ".jpg"),
plot = gg,
width = 20, ## do not change
height = 12, ## can change from 20 if desired. We use 10 here because there are only 4 coefficients.
units = 'in', ## do not change
dpi = 72) ## do not change
For vertical error bars, use geom_errorbar() instead of
geom_errorbarh().
We’ll use our scatter plot example, but with facet_wrap to make
separate plots for each cyl, and we add a facet = T argument to make
some formatting more appropriate for faceted plots.
dg = mtcars %>%
select(wt,
mpg,
cyl) %>%
mutate(cyl = paste0(cyl, '-cylinder')) %>%
rename(name = cyl)
title = "Title in Upper Lower" ## to be used by ggplot and ggsave
g = ggplot(dg,
aes(x = wt,
y = mpg,
size = mpg,
color = name)) +
geom_point(show.legend = F) +
facet_wrap(~name,
nrow = 1) +
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
x = 'Horizontal Axis Label in Upper Lower',
y = 'Vertical Axis Label in Upper Lower')
g %>%
pub(xlim = c(0, 6),
ylim = c(0, 40),
facet = T)
## Save to a file using base_size = 36
gg = g %>%
pub(xlim = c(0, 6),
ylim = c(0, 40),
facet = T,
base_size = 36)
ggsave(filename = paste0("img/", gsub("%", " Perc", title), ".jpg"), ## must have a subfolder called 'img'
plot = gg,
width = 20, ## do not change
height = 13, ## can change from 20 if desired. Here we choose 13 so each subplot is square
units = 'in', ## do not change
dpi = 72) ## do not change
Let’s make up some data. Let’s also define a new “reverse_trans”
function called reverse2_trans.
current.year = as.numeric(format(Sys.Date(), "%Y"))
dg = data.frame(date =
as.Date(
c(paste0(current.year,
c('-01-01',
'-07-04',
'-12-25',
'-12-31')),
paste0(current.year + 1,
c('-01-01',
'-07-04',
'-12-25',
'-12-31')))),
text = c("New Year's Day",
"Independence Day",
"Christmas Day",
"New Year's Eve",
"New Year's Day",
"Independence Day",
"Christmas Day",
"New Year's Eve")) %>%
mutate(text = paste0(text, ', ', date),
name = case_when(grepl('Christmas', text) ~ 'Christmas',
grepl('Indep' , text) ~ 'Indep',
TRUE ~ 'Other'),
name = factor(name, levels = c('Christmas',
'Indep',
'Other')))
dg
#> date text name
#> 1 2024-01-01 New Year's Day, 2024-01-01 Other
#> 2 2024-07-04 Independence Day, 2024-07-04 Indep
#> 3 2024-12-25 Christmas Day, 2024-12-25 Christmas
#> 4 2024-12-31 New Year's Eve, 2024-12-31 Other
#> 5 2025-01-01 New Year's Day, 2025-01-01 Other
#> 6 2025-07-04 Independence Day, 2025-07-04 Indep
#> 7 2025-12-25 Christmas Day, 2025-12-25 Christmas
#> 8 2025-12-31 New Year's Eve, 2025-12-31 Other
## Now make the timeline using ggrepel for the text
library(ggrepel) ## for geom_text_repel() or geom_label_repel()
## Function for reverse date axes
## Copied from https://github.com/tidyverse/ggplot2/issues/4014
## Will be used by pub. If you are using theme_pub instead of pub,
## you will need this function and scale_y_continuous(trans = 'reverse2').
reverse2_trans <- function() {
trans_new(
"reverse2",
function(x) -1 * as.numeric(x), # Force values to be numeric for Date objects
function(x) -1 * as.numeric(x)
)
}
## Define breaks, title, and plot
breaks = as.Date(paste0(current.year + 0:2,
'-01-01'))
title = "Title in Upper Lower" ## to be used by ggplot and ggsave
g = ggplot(dg,
aes(x = 0,
y = date,
color = name,
label = text)) +
geom_segment(aes(x = 0,
xend = 0,
y = min(date),
yend = max(date)),
show.legend = F,
color = publightgray) +
geom_point(show.legend = F) +
geom_label_repel(nudge_x = 1,
hjust = 0,
direction = 'y',
show.legend = F) +
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption, X handle, or shameless promotion of pubtheme",
x = '',
y = '')
g %>%
pub(type = 'timeline',
xlim = c(0, 5),
ybreaks = breaks,
ylabels = function(x) format(x, '%b %d, %Y'),
ytrans = 'reverse2')
## Save to a file using base_size = 36
gg = g %>%
pub(type = 'timeline',
xlim = c(0, 5),
ybreaks = breaks,
ylabels = function(x) format(x, '%b %d, %Y'),
ytrans = 'reverse2',
base_size = 36)
ggsave(filename = paste0("img/", gsub("%", " Perc", title), ".jpg"), ## must have a subfolder called 'img'
plot = gg,
width = 20, ## do not change
height = 30, ## can change if you want. Here we made it longer to have more space
units = 'in', ## do not change
dpi = 72) ## do not change
This theme changes your default ggplot colors to those found in
colors.r. The palette for discrete color scales
scale_colour_discrete and scale_fill_discrete consists of red, blue,
gray, light red, and light blue, as seen in the Line Plot above. Recall
that if you want to undo the changes made by this theme, you can use
restore.ggplot.defaults() at any time.
If more than 5-6 colors are needed, a 14-color colorblind friendly
palette cb.pal can be used by adding
+ scale_color_manual(values = cb.pal) or
+ scale_fill_manual( values = cb.pal) to a plot. For example,
dg = mtcars %>%
mutate(gear = paste0(gear, ' gear'),
cyl = paste0(cyl , ' cyl' ),
name = paste0(gear, ', ', cyl))
title = "Title in Upper Lower" ## to be used by ggplot and ggsave
g = ggplot(dg,
aes(x = wt,
y = mpg,
color = name)) +
geom_point() +
facet_grid(cyl ~ gear) +
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
x = 'Horizontal Axis Label in Upper Lower',
y = 'Vertical Axis Label in Upper Lower',
color = 'Gears and Cylinders') +
scale_color_manual(values = cb.pal) +
guides(color = guide_legend(nrow = 3))
g %>%
pub(xlim = c(0, 6),
ylim = c(0, 40),
facet = T)
dg = data.frame(city = c('New York', 'Los Angeles'),
lat = c( 40.7128, 34.0522),
lon = c(-74.0060, -118.2437))
title = "Title in Upper Lower"
g = ggplot(dg,
aes(x = lon,
y = lat)) +
borders('state',
colour = publightgray) +
geom_point(color = pubred) +
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme")
g %>%
pub(type = 'map')
The function geom_hex can be used for making a heat map with hexagonal
bins. Those can be colored by count.
dg = economics
title = 'Title in Upper Lower'
g = ggplot(dg,
aes(x = psavert,
y = uempmed)) +
geom_hex(color = pubbackgray,
bins = 20,
show.legend = TRUE) +
scale_fill_gradient(low = pubbackgray,
high = pubblue,
na.value = pubmediumgray,
oob = squish,
limits = c(0,20),
breaks = c(0, 10, 20)
) +
guides(fill = guide_colourbar())+
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
x = 'Personal Savings Rate',
y = 'Median Duration of Unemployment',
fill = 'Observations')
g %>%
pub(xlim = c(0, 20),
ylim = c(0, 30))
## Save to a file using base_size = 36
gg = g %>%
pub(xlim = c(0, 20),
ylim = c(0, 30),
base_size = 36)
ggsave(filename = paste0("img/", gsub("%", " Perc", title), ".jpg"), ## must have a subfolder called 'img'
plot = gg,
width = 20, ## do not change
height = 20, ## can change from 20 if desired
units = 'in', ## do not change
dpi = 72) ## do not change
If you want to size the hexagons by count, and color by another
variable, the only way I know is to use geom_star with
starshape = 'hexagon'. The following code creates some data with
cell ID, cell location x and y, the count to be used for size,
and a column mean.pop to be used for fill. This is a reasonable
solution but it is not ideal and is still under development.
library(hexbin)
library(ggstar)
df = economics
h = hexbin(x = df$psavert,
y = df$uempmed,
xbins = 20,
IDs = TRUE)
hh = data.frame(hcell2xy(h),
cell = h@cell,
count = h@count,
xcm = h@xcm,
ycm = h@ycm)
head(hh)
#> x y cell count xcm ycm
#> 1 9.7500 4.000000 11 2 9.90000 4.10
#> 2 10.5050 4.000000 12 4 10.40000 4.25
#> 3 11.2600 4.000000 13 3 11.23333 4.40
#> 4 12.0150 4.000000 14 3 11.83333 4.30
#> 5 13.5250 4.000000 16 1 13.30000 4.10
#> 6 4.8425 4.917987 25 1 4.50000 5.20
df$cell = h@cID
dg <- df %>%
group_by(cell) %>%
summarise(n = n(), ## for size
pop = sum(pop)) %>% ## for fill
ungroup() %>%
mutate(mean.pop = pop/n) %>%
right_join(hh,
by = "cell") %>%
select(cell, x, y,
count, n,
pop, mean.pop)
title = 'Title in Upper Lower'
g = ggplot(dg,
aes(x = x,
y = y,
fill = mean.pop,
size = n)) +
geom_star(colour = pubbackgray,
starshape = 'hexagon',
show.legend = T) +
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
x = 'Personal Savings Rate',
y = 'Median Duration of Unemployment',
size = 'Observations',
fill = 'Mean Population') +
scale_fill_gradient(guide = 'legend',
low = publightgray,
high = pubblue) +
guides(size = guide_legend(nrow = 3,
override.aes = list(fill = pubdarkgray)),
fill = guide_legend(nrow = 2,
override.aes = list(size = 5)))
g %>%
pub(xlim = c(0, 20),
ylim = c(0, 30)) +
scale_size(range = c(1, 5)) ## adjust the max, and maybe the min, manually
## Save to a file using base_size = 36
gg = g %>%
pub(xlim = c(0, 20),
ylim = c(0, 30),
base_size = 36) +
scale_size(range = c(1, 5)*3) ## same as above, but times 3
ggsave(filename = paste0("img/", gsub("%", " Perc", title), ".jpg"), ## must have a subfolder called 'img'
plot = gg,
width = 20, ## do not change
height = 20, ## can change, but hexagons may look distorted
units = 'in', ## do not change
dpi = 72) ## do not change
Let’s use the ggtext https://wilkelab.org/ggtext/ package to add
images as labels.
First let’s choose a couple of images, and create a data frame with the image URLs, the country name and GDP per capita (taken from https://en.wikipedia.org/wiki/List_of_countries_by_GDP_(nominal)_per_capita on 11/21/2023).
First, let’s get a couple of PNG files from the web.
# us = 'https://upload.wikimedia.org/wikipedia/en/thumb/a/a4/Flag_of_the_United_States.svg/35px-Flag_of_the_United_States.svg.png'
# can = 'https://upload.wikimedia.org/wikipedia/commons/thumb/d/d9/Flag_of_Canada_%28Pantone%29.svg/35px-Flag_of_Canada_%28Pantone%29.svg.png'
# download.file(url = us , destfile = "img/US.png" , method='curl')
# download.file(url = can, destfile = "img/CAN.png", method='curl')
## if you need to write a PNG file from an image you can use `writePNG`
# us = png::readPNG(us )
# can = png::readPNG(can)
# writePNG('img/US.png')
# writePNG('img/CAN.png')library(ggtext)
us = 'img/US.png'
can = 'img/CAN.png'
df = data.frame(country = c('USA', 'Canada'),
GDP.per.cap = c(80412, 53247),
image = c(us, can))
df
#> country GDP.per.cap image
#> 1 USA 80412 img/US.png
#> 2 Canada 53247 img/CAN.pngNow create some HTML code to display the images with the country names. You will likely need to change the width and height, but note that after saving the visualization to a file, the image will appear smaller than it appears on screen.
df = df %>%
mutate(label = paste0("<img src='",
image,
"' style = 'display:inline-block; vertical-align:middle' width='72' height='36'/>"))
df
#> country GDP.per.cap image
#> 1 USA 80412 img/US.png
#> 2 Canada 53247 img/CAN.png
#> label
#> 1 <img src='img/US.png' style = 'display:inline-block; vertical-align:middle' width='72' height='36'/>
#> 2 <img src='img/CAN.png' style = 'display:inline-block; vertical-align:middle' width='72' height='36'/>One way to add images is to use geom_image from ggimage. This
results in a stretched looking image, but we’ll leave it here anyway.
library(ggimage)
title = "Title in Upper Lower"
g = ggplot(df,
aes(x = GDP.per.cap,
y = country,
size = .5, ## these are constant put these in aes() anyway
linewidth = .5)) + ## so they change when base_size changes
geom_point(color = pubred,
show.legend = F) +
geom_segment(aes(x = 0,
xend = GDP.per.cap,
y = country,
yend = country),
color = pubred) +
geom_image(aes(image = image),
size = .05,
by = 'height',
nudge_x = 12000) +
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
x = 'Horizontal Axis Label in Upper Lower', ## Optional.
y = NULL) + ## Optional. Upper Lower.
guides(size = 'none',
linewidth = 'none')
g %>%
pub(type = 'pop',
xlim = c(0, 100000))
## Save to a file using base_size = 36
gg = g %>%
pub(type = 'pop',
xlim = c(0, 100000),
base_size = 36)
ggsave(filename = paste0("img/", gsub("%", " Perc", title), ".jpg"), ## must have a subfolder called 'img'
plot = gg,
width = 20, ## do not change
height = 20, ## can change from 20 if desired. We use 12 here because there are only 5 lollipops
units = 'in', ## do not change
dpi = 72) ## do not change
Now we’ll use geom_richtext instead of geom_text to add labels to
points. These images have a better aspect ratio.
title = "Title in Upper Lower"
g = ggplot(df,
aes(x = GDP.per.cap,
y = country,
label = label,
size = 10, ## these are constant put these in aes() anyway
linewidth = .5)) + ## so they change when base_size changes
geom_point(color = pubred,
show.legend = F) +
geom_segment(aes(x = 0,
xend = GDP.per.cap,
y = country,
yend = country),
color = pubred) +
geom_richtext(hjust = -0.2,
fill = NA,
label.color = NA) +
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
x = 'Horizontal Axis Label in Upper Lower', ## Optional.
y = NULL) + ## Optional. Upper Lower.
guides(size = 'none',
linewidth = 'none')
g %>%
pub(type = 'pop',
xlim = c(0, 100000),
base_size = 12) +
theme(axis.text.y = element_markdown()) ## render the HTML code
## Save to a file using base_size = 36
gg = g %>%
pub(type = 'pop',
xlim = c(0, 100000),
base_size = 36) +
theme(axis.text.y = element_markdown())
ggsave(filename = "img/flag.example.jpg", ## must have a subfolder called 'img'
plot = gg,
width = 20, ## do not change
height = 12, ## can change from 20 if desired. We use 12 here because there are only 5 lollipops
units = 'in', ## do not change
dpi = 72) ## do not change
The images are smaller and less fuzzy when saved using ggsave:
!(img/flag.example.jpg)
For this we can use label as the y-axis label and use
theme(axis.text.y = element_markdown()) to render the HTML code.
title = "Title in Upper Lower"
g = ggplot(df,
aes(x = GDP.per.cap,
y = label,
label = round(GDP.per.cap,2),
size = 12, ## these are constant put these in aes() anyway
linewidth = .5)) + ## so they change when base_size changes
geom_point(color = pubred,
show.legend = F) +
geom_segment(aes(x = 0,
xend = GDP.per.cap,
y = label,
yend = label),
color = pubred) +
geom_text(hjust = -0.3) + ## optional numbers with reasonable number of digits
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
x = 'Horizontal Axis Label in Upper Lower', ## Optional.
y = NULL) + ## Optional. Upper Lower.
guides(size = 'none',
linewidth = 'none')
g %>%
pub(type = 'pop',
xlim = c(0, 100000),
base_size = 12) +
theme(axis.text.y = element_markdown())
## Save to a file using base_size = 36
gg = g %>%
pub(type = 'pop',
xlim = c(0, 100000),
base_size = 36) +
theme(axis.text.y = element_markdown())
ggsave(filename = paste0("img/", gsub("%", " Perc", title), ".jpg"), ## must have a subfolder called 'img'
plot = gg,
width = 20, ## do not change
height = 12, ## can change from 20 if desired. We use 12 here because there are only 5 lollipops
units = 'in', ## do not change
dpi = 72) ## do not change
You can use layout_pub to get similar formatting for plotly figures
that use ggplotly or plot_ly. This is under development. Only using
type = 'scatter' with plot_ly is currently supported. Others may
work and will be added “soon”, according to some definition of “soon”.
Here is an example using plot_ly:
library(htmlwidgets)
dg = mtcars %>%
select(wt,
mpg,
cyl) %>%
mutate(cyl = factor(cyl)) %>%
rownames_to_column('name')
base_size = 12
p = plot_ly(data = dg,
width = 1440*base_size/36,
height = 1440*base_size/36) %>%
add_trace(type = 'scatter',
mode = 'markers',
x = ~wt,
y = ~mpg,
color = ~cyl,
size = ~mpg,
text = ~name,
colors = default.pal[1:3], ## change 3 to number of categories
marker = list(opacity = 1),# add size = 30*base_size/36 if no size above
hovertemplate = paste0(
"<b>%{text}</b><br>",
"%{yaxis.title.text}: %{y:,.3f}<br>",
"%{xaxis.title.text}: %{x:,.2f}<br>",
"<extra></extra>")) %>%
layoutpub(type = 'scatter',
base_size = base_size,
subtitle = T,
caption = F,
legend.rows = 1) %>%
layout(
title = list(text = maketitle(title = 'Title In Upper Lower',
subtitle = 'Optional Subtitle in Upper Lower',
base_size = base_size)),
xaxis = list(title = list(text = 'Wt'),
range = c(0, 6),
tickvals = c(0, 3, 6)),
yaxis = list(title = list(text = 'MPG'),
range = c(0, 40),
tickvals = c(0, 20, 40)),
legend = list(title = list(text = 'Cylinders'))
)
print(p)
htmlwidgets::saveWidget(widget = p,
file = paste0("img/", gsub("%", " Perc", title), ".html"),
libdir = "lib",
selfcontained = F)Click here or click on the image below to view the interactive version of the plot.
knitr::include_url("https://bmacgtpm.github.io/pubtheme/img/Title%20in%20Upper%20Lower.html")
Note that the subtitle and the caption at the bottom of the plot are currently not functioning properly.
Here is an example using ggplotly.
dg = mtcars %>%
select(wt,
mpg,
cyl) %>%
mutate(Cylinders = as.factor(cyl)) %>%
rename(MPG = mpg,
Weight = wt) %>%
rownames_to_column('name')
g = ggplot(dg,
aes(x = Weight,
y = MPG,
color = Cylinders,
text = name)) +
geom_point() +
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
x = 'Horizontal Axis Label in Upper Lower',
y = 'Vertical Axis Label in Upper Lower',
size = "MPG")
## Convert g to plotly using ggplotly
base_size = 12
p = g %>%
#labs(title = paste0('<b>', title, '</b>'))
pub(xlim = c(0, 6),
ylim = c(0, 40)) %>%
ggplotly(width = 1440*base_size/36,
height = 1440*base_size/36,
tooltip = c('x', 'y', 'color', 'text')) %>%
layoutpub(type = 'scatter',
base_size = base_size,
subtitle = T,
caption = F,
legend.rows = 1) %>%
style(marker.sizeref = 1.5)
p
htmlwidgets::saveWidget(widget = p,
file = paste0("img/", gsub("%", " Perc", title), ".html"),
libdir = "lib",
selfcontained = F)The plot isn’t interactive here. Run the code to see the interactive plot.
Note that the subtitle does not currently display. And the points in the legend are different sizes for some reason #shrugs.
As with non-interactive plots above, you can use pub to save a lot of
typing if you are ok with accepting more default settings. If you use
pub with int = TRUE (int for interactive), the ggplot object
will be converted to a plotly object using the ggplotly and
layoutpub code above. You’ll just need to specify the arguments
subtitle, caption and legend.rows required by layoutpub. This is
in development and works for this example but may not work for other
plots.
g %>%
pub(xlim = c(0, 6),
ylim = c(0, 40),
int = T,
tooltip = c('x', 'y', 'color', 'text'),
subtitle = T,
caption = F,
legend.rows = 1) 
If you want to customize the tooltip (e.g. when you are unable to
specify the order that you want), you can create a text column that
has the information you want, in the order that you want. You can also
include HTML code to format the text.
In the example below, the car name is bolded using <b> </b>, and
Weight, MPG, and Cylinders appear as additional information. The
function tooltip.text helps make it easier. You can list unquoted
column names in the order you want them. The entries in the tooltip are
typically of the from “ColumnName: Value”. If there is a name column
listed, it automatically makes it bold and removes name: from the
tooltip, like this:
Toyota Corolla
Weight: 1.835
MPG: 33.9
Cylinders: 4
dg = mtcars %>%
select(wt,
mpg,
cyl) %>%
mutate(Cylinders = as.factor(cyl)) %>%
rename(MPG = mpg,
Weight = wt) %>%
rownames_to_column('name') %>%
mutate(text = tooltip.text(name,
Weight,
MPG,
Cylinders))
g = ggplot(dg,
aes(x = Weight,
y = MPG,
color = Cylinders,
#size = MPG, ## this messes up the legend position or margins
text = text)) +
geom_point() +
labs(title = title,
subtitle = 'Optional Subtitle In Upper Lower',
caption = "Optional caption giving more info, X handle, or shameless promotion of pubtheme",
x = 'Horizontal Axis Label in Upper Lower',
y = 'Vertical Axis Label in Upper Lower',
#size = "MPG"
)
g %>%
pub(xlim = c(0, 6),
ylim = c(0, 40),
int = T,
tooltip = 'text',
subtitle = T,
caption = F,
legend.rows = 1) %>%
layout(legend = list(itemsizing = 'constant'))