[英]shrink plot width to make more room for ggrepel labels
I want to shrink the plot area so there is more room for ggrepel
labels that currently get cut off. 我想缩小绘图区域,以便有更多的空间可以将
ggrepel
标签切断。 I can't seem to offset the labels any more via nudge_x()
, and I do not want to shrink the text size. 我似乎无法通过
nudge_x()
来偏移标签,我不想缩小文本大小。
I'm trying to find a way to compress the chart so that the groups all move closer to the center, leaving more room for labels at the extremes of the x-axis. 我正试图找到一种压缩图表的方法,以便所有组都移近中心,在x轴的极端处为标签留出更多空间。
Specifically, I am trying to knit this figure into a portrait PDF. 具体来说,我试图将这个数字编成一幅肖像PDF。 I tried controlling
fig.width
in the chunk options, but this just made the entire chart smaller. 我尝试在块选项中控制
fig.width
,但这只会使整个图表变小。
I want to maximize the width on the portrait page, but shrink the plot area relative to the area for labels. 我想最大化纵向页面上的宽度,但缩小相对于标签区域的绘图区域。
---
title : "The title"
shorttitle : "Title"
author:
- name : "Me"
affiliation : "1"
corresponding : yes # Define only one corresponding author
address : "Address"
email : "email"
affiliation:
- id : "1"
institution : "Company"
authornote: |
Note here
abstract: |
Abstract here.
floatsintext : yes
figurelist : no
tablelist : no
footnotelist : no
linenumbers : no
mask : no
draft : no
note : "\\clearpage"
documentclass : "apa6"
classoption : "man,noextraspace"
header-includes:
- \usepackage{pdfpages}
- \usepackage{setspace}
- \AtBeginEnvironment{tabular}{\singlespacing}
- \makeatletter\let\expandableinput\@@input\makeatother
- \interfootnotelinepenalty=10000
- \usepackage{float} #use the 'float' package
- \floatplacement{figure}{H} #make every figure with caption = h
- \raggedbottom
output : papaja::apa6_pdf
---
```{r test, fig.cap="Caption.", fig.height=8, include=TRUE, echo=FALSE}
library("papaja")
library(tidyverse)
library(ggrepel)
ageGenderF <- structure(list(genAge = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L), .Label = c("Women, 15-19",
"Women, 20-24", "Women, 25-35", "Women, 36+"), class = "factor"),
word_ = c("this is label 2", "this is label 3", "this is label 4",
"this is label 1", "this is label 7", "this is label 5",
"this is label 8", "this is label 10", "this is label 11",
"this is label 20", "this is label 12", "this is label 6",
"this is label 17", "this is label 9", "this is label 15",
"this is label 21", "this is label 31", "this is label 25",
"this is label 26", "this is label 19", "this is label 24",
"this is label 28", "this is label 29", "this is label 30",
"this is label 14", "this is label 22", "this is label 18",
"this is label 54", "this is label 32", "this is label 44",
"this is label 52", "this is label 34", "this is label 59",
"this is label 48", "this is label 23", "this is label 47",
"this is label 38", "this is label 35", "this is label 61",
"this is label 56", "this is label 39", "this is label 72",
"this is label 42", "this is label 16", "this is label 66",
"this is label 37", "this is label 51", "this is label 27",
"this is label 40", "this is label 73", "this is label 60",
"this is label 113", "this is label 50", "this is label 45",
"this is label 81", "this is label 84", "this is label 53",
"this is label 49", "this is label 67", "this is label 68",
"this is label 46", "this is label 65", "this is label 41",
"this is label 57", "this is label 1", "this is label 2",
"this is label 3", "this is label 4", "this is label 5",
"this is label 6", "this is label 7", "this is label 8",
"this is label 9", "this is label 10", "this is label 11",
"this is label 12", "this is label 13", "this is label 14",
"this is label 15", "this is label 16", "this is label 17",
"this is label 18", "this is label 19", "this is label 20",
"this is label 21", "this is label 22", "this is label 23",
"this is label 24", "this is label 25", "this is label 26",
"this is label 27", "this is label 28", "this is label 29",
"this is label 30", "this is label 31", "this is label 32",
"this is label 33", "this is label 34", "this is label 35",
"this is label 36", "this is label 37", "this is label 38",
"this is label 39", "this is label 40", "this is label 41",
"this is label 42", "this is label 43", "this is label 44",
"this is label 45", "this is label 46", "this is label 47",
"this is label 48", "this is label 49", "this is label 50",
"this is label 51", "this is label 52", "this is label 53",
"this is label 54", "this is label 55", "this is label 56",
"this is label 57", "this is label 58", "this is label 59",
"this is label 60", "this is label 61", "this is label 62",
"this is label 63", "this is label 64", "this is label 1",
"this is label 2", "this is label 3", "this is label 6",
"this is label 4", "this is label 5", "this is label 12",
"this is label 7", "this is label 8", "this is label 9",
"this is label 10", "this is label 14", "this is label 11",
"this is label 18", "this is label 29", "this is label 45",
"this is label 27", "this is label 15", "this is label 26",
"this is label 71", "this is label 37", "this is label 13",
"this is label 25", "this is label 23", "this is label 22",
"this is label 41", "this is label 42", "this is label 55",
"this is label 52", "this is label 36", "this is label 34",
"this is label 17", "this is label 63", "this is label 24",
"this is label 19", "this is label 28", "this is label 38",
"this is label 32", "this is label 21", "this is label 30",
"this is label 35", "this is label 16", "this is label 64",
"this is label 20", "this is label 31", "this is label 53",
"this is label 77", "this is label 39", "this is label 70",
"this is label 57", "this is label 48", "this is label 43",
"this is label 132", "this is label 51", "this is label 66",
"this is label 58", "this is label 85", "this is label 120",
"this is label 65", "this is label 40", "this is label 121",
"this is label 78", "this is label 59", "this is label 141",
"this is label 1", "this is label 12", "this is label 6",
"this is label 2", "this is label 3", "this is label 5",
"this is label 4", "this is label 45", "this is label 52",
"this is label 26", "this is label 77", "this is label 8",
"this is label 7", "this is label 10", "this is label 14",
"this is label 31", "this is label 59", "this is label 178",
"this is label 18", "this is label 27", "this is label 42",
"this is label 70", "this is label 29", "this is label 37",
"this is label 330", "this is label 78", "this is label 25",
"this is label 34", "this is label 21", "this is label 450",
"this is label 83", "this is label 185", "this is label 57",
"this is label 16", "this is label 50", "this is label 126",
"this is label 895", "this is label 63", "this is label 402",
"this is label 19", "this is label 724", "this is label 40",
"this is label 11", "this is label 43", "this is label 758",
"this is label 1099", "this is label 73", "this is label 62",
"this is label 46", "this is label 183", "this is label 819",
"this is label 295", "this is label 1100", "this is label 17",
"this is label 282", "this is label 153", "this is label 1101",
"this is label 41", "this is label 1102", "this is label 446",
"this is label 216", "this is label 13", "this is label 109",
"this is label 20"), n = c(774L, 635L, 618L, 495L, 329L,
284L, 259L, 217L, 197L, 181L, 163L, 163L, 162L, 160L, 138L,
124L, 114L, 112L, 110L, 107L, 99L, 98L, 97L, 92L, 85L, 84L,
84L, 78L, 74L, 72L, 68L, 67L, 66L, 66L, 65L, 60L, 60L, 60L,
58L, 57L, 55L, 51L, 51L, 51L, 50L, 50L, 48L, 47L, 47L, 46L,
46L, 44L, 44L, 44L, 43L, 43L, 43L, 43L, 42L, 41L, 41L, 41L,
41L, 41L, 1568L, 1366L, 1220L, 1012L, 687L, 682L, 633L, 516L,
464L, 374L, 372L, 326L, 326L, 304L, 293L, 292L, 274L, 261L,
259L, 257L, 236L, 232L, 229L, 223L, 223L, 221L, 221L, 213L,
210L, 205L, 198L, 191L, 189L, 167L, 165L, 164L, 146L, 142L,
140L, 140L, 139L, 136L, 134L, 129L, 122L, 121L, 115L, 115L,
115L, 113L, 112L, 110L, 110L, 109L, 107L, 104L, 103L, 102L,
99L, 99L, 99L, 97L, 96L, 93L, 426L, 332L, 310L, 290L, 197L,
166L, 147L, 134L, 125L, 113L, 105L, 104L, 97L, 83L, 78L,
77L, 77L, 74L, 69L, 69L, 69L, 69L, 68L, 61L, 61L, 59L, 59L,
58L, 58L, 58L, 57L, 57L, 56L, 54L, 51L, 48L, 47L, 46L, 43L,
42L, 38L, 38L, 36L, 34L, 34L, 33L, 32L, 32L, 32L, 32L, 31L,
29L, 29L, 28L, 28L, 27L, 27L, 27L, 27L, 27L, 26L, 26L, 25L,
24L, 37L, 26L, 26L, 20L, 19L, 18L, 17L, 15L, 14L, 12L, 12L,
12L, 12L, 12L, 11L, 10L, 9L, 9L, 9L, 9L, 8L, 7L, 7L, 7L,
7L, 7L, 7L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L), rank = c(1L, 2L,
3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L,
16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L,
28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L,
40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 51L,
52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 60L, 61L, 62L, 63L,
64L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L,
14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L,
26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L,
38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L,
50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 60L, 61L,
62L, 63L, 64L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L,
12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L,
24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L,
36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L,
48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L,
60L, 61L, 62L, 63L, 64L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L,
9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L,
21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L,
33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L,
45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L,
57L, 58L, 59L, 60L, 61L, 62L, 63L, 64L)), class = c("grouped_df",
"tbl_df", "tbl", "data.frame"), row.names = c(NA, -256L), groups = structure(list(
genAge = structure(1:4, .Label = c("Women, 15-19", "Women, 20-24",
"Women, 25-35", "Women, 36+"), class = "factor"), .rows = list(
1:64, 65:128, 129:192, 193:256)), row.names = c(NA, -4L
), class = c("tbl_df", "tbl", "data.frame"), .drop = TRUE))
ageGenderFLow <-
ageGenderF %>%
filter(genAge=="Women, 15-19") %>%
filter(rank<=10)
ageGenderFHigh <-
ageGenderF %>%
filter(genAge=="Women, 36+") %>%
filter(rank<=10)
ageGenderF_ <-
ageGenderF %>%
filter(word_ %in% ageGenderFLow$word_ |
word_ %in% ageGenderFHigh$word_)
# get rank order of words for low set
ageGenderFLowRank <-
ageGenderF_ %>%
filter(genAge=="Women, 15-19") %>%
arrange(rank) %>%
mutate(order = 1:n())
ageGenderF_ %>%
mutate(word = factor(word_, ordered=TRUE, levels=ageGenderFLowRank$word_)) %>%
# https://ibecav.github.io/slopegraph/
ggplot(., aes(x = genAge, y = reorder(rank, -rank), group = word_)) +
geom_line(aes(color = word_, alpha = 1), size = 1.5) +
#geom_line(size = 0.5, color="lightgrey") +
geom_text_repel(data = . %>% filter(genAge == "Women, 15-19"),
aes(label = word) ,
hjust = "left",
#fontface = "bold",
size = 3,
nudge_x = -3,
direction = "y") +
geom_text_repel(data = . %>% filter(genAge == "Women, 36+"),
aes(label = word) ,
hjust = "right",
#fontface = "bold",
size = 3,
nudge_x = 3,
direction = "y") +
geom_label(aes(label = rank),
size = 2.5,
label.padding = unit(0.15, "lines"),
label.size = 0.0) +
scale_x_discrete(position = "top") +
theme_bw() +
# Remove the legend
theme(legend.position = "none") +
# Remove the panel border
theme(panel.border = element_blank()) +
# Remove just about everything from the y axis
theme(axis.title.y = element_blank()) +
theme(axis.text.y = element_blank()) +
theme(panel.grid.major.y = element_blank()) +
theme(panel.grid.minor.y = element_blank()) +
# Remove a few things from the x axis and increase font size
theme(axis.title.x = element_blank()) +
theme(panel.grid.major.x = element_blank()) +
theme(axis.text.x.top = element_text(size=10)) +
# Remove x & y tick marks
theme(axis.ticks = element_blank()) +
# Format title & subtitle
theme(plot.title = element_text(size=10, face = "bold", hjust = 0.5)) +
theme(plot.subtitle = element_text(hjust = 0.5))
```
If you are willing to change your approach, you could make a big switch and use the text you are using as labels as the axis labels. 如果您愿意更改方法,可以进行大转换并使用您用作标签的文本作为轴标签。 You could take advantage of the secondary axis to do separate labels for each side of the plot, so things will look a lot like what you are doing now.
您可以利用辅助轴为绘图的每一侧执行单独的标注,因此事情看起来很像您现在正在做的事情。
The advantage I see to this is that the text fits because it's now part of the axis. 我看到的优点是文本适合,因为它现在是轴的一部分。
First here's an example using rank
as a factor. 首先,这是一个使用
rank
作为因子的例子。 You have to make the factor into something numeric via as.numeric()
in order to get duplicate axes (so far discrete axes don't have secondary axes). 您必须通过
as.numeric()
将该因子转换为数字,以获得重复的轴(到目前为止,离散轴没有辅助轴)。 Then there's some work to do be done getting the breaks and labels for the axis on each side, so I move data manipulation into a second step (and make rank2
as the reordered factor for ease of doing the breaks
later). 然后还需要做一些工作来获取每一侧的轴的断点和标签,因此我将数据操作移到第二步(并将
rank2
作为重新排序的因子,以便以后进行breaks
)。
Note also the use of expand
in scale_x_discrete()
to remove space from around the edges of the panel area. 另请注意,在
scale_x_discrete()
使用expand
可以从面板区域的边缘移除空间。
ageGenderF_ = ageGenderF_ %>%
ungroup() %>%
mutate(word = factor(word_, ordered = TRUE, levels = ageGenderFLowRank$word_),
rank2 = reorder(rank, -rank) )
ageGenderF_ %>%
# https://ibecav.github.io/slopegraph/
ggplot(., aes(x = genAge, y = as.numeric(rank2), group = word_)) +
geom_line(aes(color = word_, alpha = 1), size = 1.5) +
geom_label(aes(label = rank),
size = 2.5,
label.padding = unit(0.15, "lines"),
label.size = 0.0) +
scale_x_discrete(position = "top", expand = c(0, .05) ) +
scale_y_continuous(breaks = filter(ageGenderF_, genAge == "Women, 15-19") %>% pull(rank2) %>% as.numeric(),
labels = filter(ageGenderF_, genAge == "Women, 15-19") %>% pull(word),
sec.axis = dup_axis(~.,
breaks = filter(ageGenderF_, genAge == "Women, 36+") %>% pull(rank2) %>% as.numeric(),
labels = filter(ageGenderF_, genAge == "Women, 36+") %>% pull(word) ) ) +
theme_bw() +
# Remove the legend
theme(legend.position = "none",
# Remove the panel border
panel.border = element_blank(),
# Remove just about everything from the y axis
axis.title.y = element_blank(),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
# Remove a few things from the x axis and increase font size
axis.title.x = element_blank(),
panel.grid.major.x = element_blank(),
axis.text.x.top = element_text(size=10),
# Remove x & y tick marks
axis.ticks = element_blank(),
axis.ticks.length = unit(0, "cm"),
# Format title & subtitle
plot.title = element_text(size=10, face = "bold", hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5) )
From a simple r markdown document this looks similar to your example (although not exact): 从简单的r markdown文档看起来与您的示例类似(尽管不完全相同):
You can do the exact same thing with rank
as numeric, using scale_y_reverse()
to reverse the y axis. 你可以用
rank
作为数字做同样的事情,使用scale_y_reverse()
来反转y轴。
ageGenderF_ = ageGenderF_ %>%
ungroup() %>%
mutate(word = factor(word_, ordered = TRUE, levels = ageGenderFLowRank$word_))
ageGenderF_ %>%
# https://ibecav.github.io/slopegraph/
ggplot(., aes(x = genAge, y = rank, group = word_)) +
geom_line(aes(color = word_, alpha = 1), size = 1.5) +
geom_label(aes(label = rank),
size = 2.5,
label.padding = unit(0.15, "lines"),
label.size = 0.0) +
scale_x_discrete(position = "top", expand = c(0, .05) ) +
scale_y_reverse(breaks = filter(ageGenderF_, genAge == "Women, 15-19") %>% pull(rank),
labels = filter(ageGenderF_, genAge == "Women, 15-19") %>% pull(word),
sec.axis = dup_axis(~.,
breaks = filter(ageGenderF_, genAge == "Women, 36+") %>% pull(rank),
labels = filter(ageGenderF_, genAge == "Women, 36+") %>% pull(word) ) ) +
theme_bw() +
# Remove the legend
theme(legend.position = "none",
# Remove the panel border
panel.border = element_blank(),
# Remove just about everything from the y axis
axis.title.y = element_blank(),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
# Remove a few things from the x axis and increase font size
axis.title.x = element_blank(),
panel.grid.major.x = element_blank(),
axis.text.x.top = element_text(size=10),
# Remove x & y tick marks
axis.ticks = element_blank(),
axis.ticks.length = unit(0, "cm"),
# Format title & subtitle
plot.title = element_text(size=10, face = "bold", hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5) )
One option is to save your plot as an object ( p
) and then use the set_panel_size
argument in the egg
package to explicitly set height and width of the panel (as done in this answer ). 一种选择是将绘图保存为对象(
p
),然后使用egg
包中的set_panel_size
参数显式设置面板的高度和宽度(如本答案中所述 )。 Something like this gets you close: 这样的事情会让你接近:
library(egg)
library(grid)
p2 <- set_panel_size(p, width=unit(7,"in"), height=unit(10, "in"))
grid.draw(p2)
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