双 y 轴（1 个数据集比另一个大） - 但两个 y 轴仅针对较小的数据集绘制图表
问题描述 投票：0回答：1
我有一个随时间变化的生存情况图，我想将每月降水量放在这些图上。我遇到的问题是我的生存数据集有 8 个点，我的降水数据集有 19 个点，但只有 8 个点的降水数据（与生存数据集相对应的点）正在绘制图表。
我的 prcp 数据应如下所示：
图代码：
pd<-position_dodge(0.2)
merged_data_date %>%
ggplot(aes( x=date, y=mean, ymin=min, ymax=max, color = plot))+
geom_line(aes(x=date, y=monthprcp*80, color = "blue"))+
geom_line(show.legend = TRUE,
size=.75,
position =pd)+
# geom_line(y=monthprcp, color ="lightblue")+
# geom_line(data=mean[!is.na(mean$combo),])+
geom_hline(yintercept=0, color="#333333", size =0.005)+
geom_point(size =2, position =pd)+
geom_errorbar(width = 0.06, position =pd)+
facet_grid(site~oak,
switch ="y",
scales="free",
labeller = as_labeller(c("Cortana" = "CT", "JJT" = "JT",
"Live" = "Live", "Red" = "Red", "Shin"= "Shin")))+
scale_x_date(date_breaks="4 month", date_labels = "%b %Y")+
# scale_y_continuous (limits =c(0, 24), breaks = seq(0,24, by = 4))+
scale_y_continuous(name = "Mean survival", sec.axis =sec_axis (trans=~./80, name = "Precipitation"))+
scale_color_manual(name =NULL,
breaks =c("C", "CS", "O", "W", "ligthblue"),
values=c( "#C16622FF", "#225EA8","#FECC5C", "#006D2C", "lightblue"),
labels =c ("Cage + No shade", "Cage + Shade", "No cage + No shade", "Wooded", "Precipitation"))+
labs (x="Time",
y="Mean seedling survival per subplot",
# title="Seedling survival over time",
title=NULL,
# subtitle = "Seedling survival on the Cortana and JJT site. Seedlings were counted between fall
# 2019 to fall 2020.",
size = 16)+
# facet_wrap(site~oak, ncol=3, drop = T)+
theme_minimal()+
theme (
legend.justification = "center",
legend.position = "top",
strip.placement = "outside",
# axis.text.x=element_text(angle=45, vjust=0.5),
plot.title = element_text (size = 16),
plot.title.position = "plot",
axis.line.x = element_line(),
axis.line.y = element_line(),
axis.title.y = element_text(size =10.5, vjust = 1),
axis.title.x = element_text(size =10.5, vjust = 1),
#strip.background = element_blank(),
strip.text.y = element_text(size =9.5),
strip.text.x= element_text(size =9.5, margin = margin (0,0,5,0)),
panel.spacing.x = unit(0.5,"lines"),
# panel.grid=element_blank())
#modifies just the vertical graphs (space between top and bottom)
panel.margin.y=unit (0.4, "lines"),
panel.grid.minor.y = element_line(color = "lightgrey"))
我的数据集示例
merged_data_date<-structure(
list(
oak = c(
"Live",
"Red",
"Shin",
"Red",
"Live",
"Shin",
"Red",
"Shin",
"Red",
"Shin",
"Shin",
"Shin",
"Shin",
"Live",
NA,
"Shin",
"Red",
"Red",
"Red",
"Red",
"Red",
"Red",
"Live",
"Red",
"Red",
"Shin",
"Live",
"Red",
"Live",
"Live",
"Live",
"Live",
"Shin",
"Red",
"Red",
"Red",
"Shin",
"Live",
"Shin",
"Live",
"Live",
"Shin",
NA,
NA,
"Shin",
"Live",
"Red",
"Red",
"Red",
NA
),
plot = c(
"CS",
"C",
"C",
"O",
"O",
"C",
"O",
"W",
"O",
"C",
"CS",
"C",
"CS",
"W",
NA,
"O",
"W",
"CS",
"O",
"CS",
"CS",
"O",
"C",
"W",
"O",
"O",
"W",
"C",
"O",
"C",
"C",
"O",
"W",
"O",
"O",
"CS",
"O",
"C",
"CS",
"CS",
"O",
"CS",
NA,
NA,
"C",
"O",
"W",
"W",
"C",
NA
),
date = structure(
c(
18475,
18048,
18109,
18506,
18048,
18078,
18170,
18109,
18048,
18170,
18475,
18506,
18048,
18109,
18017,
18506,
18078,
18048,
18475,
17956,
18506,
18109,
18170,
18078,
18506,
18506,
18078,
18475,
18170,
18475,
18048,
18506,
18078,
17956,
18170,
18475,
18078,
18078,
18078,
18048,
18048,
18109,
18322,
18353,
17956,
17956,
18475,
17956,
18048,
18414
),
class = "Date"
),
site = c(
"Cortana",
"JJT",
"Cortana",
"JJT",
"JJT",
"JJT",
"JJT",
"JJT",
"Cortana",
"Cortana",
"Cortana",
"Cortana",
"JJT",
"Cortana",
NA,
"Cortana",
"JJT",
"JJT",
"Cortana",
"JJT",
"JJT",
"JJT",
"JJT",
"Cortana",
"Cortana",
"JJT",
"Cortana",
"JJT",
"JJT",
"Cortana",
"Cortana",
"JJT",
"JJT",
"Cortana",
"Cortana",
"Cortana",
"JJT",
"JJT",
"JJT",
"JJT",
"Cortana",
"JJT",
NA,
NA,
"JJT",
"JJT",
"JJT",
"Cortana",
"Cortana",
NA
),
mean = c(
8.6,
17.2,
10.8,
0,
8,
14.2,
0,
6,
15.2,
10.4,
3.6,
2.8,
18.8,
4.2,
NA,
3.6,
16.8,
22.4,
0,
14.2,
18.6,
17.4,
0,
9.6,
0,
0,
4.8,
0,
0,
0.4,
6.8,
0,
6.2,
7.8,
15.6,
7,
15.6,
10.6,
19,
9.8,
7,
19.2,
NA,
NA,
2.4,
1,
5.6,
5.6,
16.4,
NA
),
sd = c(
1.69115345252878,
1.59373774505092,
1.82756668824971,
0,
0.447213595499958,
1.2,
0,
3.09838667696593,
1.46287388383278,
2.22710574513201,
0.92736184954957,
1.35646599662505,
1.39283882771841,
1.24096736459909,
NA,
1.6,
1.98494332412792,
1.20830459735946,
0,
2.24499443206436,
2.11187120819429,
0.6,
0,
3.85486705347928,
0,
0,
1.31909059582729,
0,
0,
0.4,
0.374165738677394,
0,
3.18433666561813,
1.15758369027902,
1.4,
1.92353840616713,
0.509901951359279,
0.748331477354788,
1.09544511501033,
1.49666295470958,
1.30384048104053,
1.01980390271856,
NA,
NA,
0.678232998312527,
0.632455532033676,
2.92574776766556,
1.69115345252878,
1.80554700852678,
NA
),
max = c(
10.2911534525288,
18.7937377450509,
12.6275666882497,
0,
8.44721359549996,
15.4,
0,
9.09838667696593,
16.6628738838328,
12.627105745132,
4.52736184954957,
4.15646599662505,
20.1928388277184,
5.44096736459909,
NA,
5.2,
18.7849433241279,
23.6083045973595,
0,
16.4449944320644,
20.7118712081943,
18,
0,
13.4548670534793,
0,
0,
6.11909059582729,
0,
0,
0.8,
7.17416573867739,
0,
9.38433666561813,
8.95758369027902,
17,
8.92353840616713,
16.1099019513593,
11.3483314773548,
20.0954451150103,
11.2966629547096,
8.30384048104053,
20.2198039027186,
NA,
NA,
3.07823299831253,
1.63245553203368,
8.52574776766556,
7.29115345252878,
18.2055470085268,
NA
),
min = c(
6.90884654747122,
15.6062622549491,
8.97243331175029,
0,
7.55278640450004,
13,
0,
2.90161332303407,
13.7371261161672,
8.17289425486799,
2.67263815045043,
1.44353400337495,
17.4071611722816,
2.95903263540091,
NA,
2,
14.8150566758721,
21.1916954026405,
0,
11.9550055679356,
16.4881287918057,
16.8,
0,
5.74513294652072,
0,
0,
3.48090940417271,
0,
0,
5.55111512312578e-17,
6.42583426132261,
0,
3.01566333438187,
6.64241630972098,
14.2,
5.07646159383287,
15.0900980486407,
9.85166852264521,
17.9045548849897,
8.30333704529042,
5.69615951895947,
18.1801960972814,
NA,
NA,
1.72176700168747,
0.367544467966324,
2.67425223233444,
3.90884654747122,
14.5944529914732,
NA
),
monthprcp = c(
0.0496551724137931,
0.1475,
0.0316071428571429,
0.221166666666667,
0.1475,
0.0404838709677419,
0.140645161290323,
0.0316071428571429,
0.1475,
0.140645161290323,
0.0496551724137931,
0.221166666666667,
0.1475,
0.0316071428571429,
0.207692307692308,
0.221166666666667,
0.0404838709677419,
0.1475,
0.0496551724137931,
0.0323214285714286,
0.221166666666667,
0.0316071428571429,
0.140645161290323,
0.0404838709677419,
0.221166666666667,
0.221166666666667,
0.0404838709677419,
0.0496551724137931,
0.140645161290323,
0.0496551724137931,
0.1475,
0.221166666666667,
0.0404838709677419,
0.0323214285714286,
0.140645161290323,
0.0496551724137931,
0.0404838709677419,
0.0404838709677419,
0.0404838709677419,
0.1475,
0.1475,
0.0316071428571429,
0.0920967741935484,
0.0646551724137931,
0.0323214285714286,
0.0323214285714286,
0.0496551724137931,
0.0323214285714286,
0.1475,
0.069
)
),
row.names = c(NA,-50L),
class = c("tbl_df",
"tbl", "data.frame")
)
我尝试过滤 NA，这给了我一个没有 NA 行或 NA 列的图表，但也删除了我的完整日期数据集
merged_data<-full_join(final_survprcp1, finalprcp, by = "date") %>%
mutate(date=as.yearmon(date)) %>%
mutate(date=as.Date(date)) %>%
filter(!is.na(site)) %>%
filter(!is.na(plot)) %>%
filter(!is.na(oak)) %>%
mutate(monthprcp_tr=monthprcp*80)
我还希望我的网站名称被剥离放置在外面，不知道为什么该代码不起作用。 我还尝试将图中的 prcp 线更改为蓝色，但线条颜色没有改变。
希望这是有道理的。
1个回答
0
投票
投票
如果我理解你的问题，我认为让两个不同的数据集保持不同可能会更容易。如果这样做，那么您可以独立于生存数据点绘制降水数据线。
输出
首先，我将把两个数据集分开。
library(dplyr)
library(ggplot2)
library(tidyr)
precip_data <- merged_data_date %>%
group_by(date) %>%
summarise(monthprcp = first(monthprcp))
surv_data <- merged_data_date %>%
dplyr::select(-monthprcp) %>%
na.omit()
为了使其按您的预期工作，您需要复制所有级别
siteoakprecip_data <- expand_grid(oak = c("Live", "Red", "Shin"),
site = c("Cortana", "JJT"),
date = precip_data$date) %>%
left_join(precip_data)
然后你就可以制作情节了。请注意，在使用降水数据进行绘图时，我使用
inherit.aes=FALSEprecip_dataggplot()pd<-position_dodge(0.2)
ggplot(data = surv_data,
aes( x=date, y=mean, ymin=min, ymax=max, color = plot)) +
geom_line(data = precip_data, aes(x=date, y=monthprcp*80), color="black", inherit.aes = FALSE) +
geom_line(show.legend = TRUE,
linewidth=.75,
position =pd)+
geom_hline(yintercept=0, color="#333333", linewidth =0.005)+
geom_point(size =2, position =pd)+
facet_grid(site~oak,
switch ="y",
scales="free",
labeller = as_labeller(c("Cortana" = "CT", "JJT" = "JT",
"Live" = "Live", "Red" = "Red", "Shin"= "Shin"))) +
scale_x_date(date_breaks="4 month", date_labels = "%b %Y")+
# scale_y_continuous (limits =c(0, 24), breaks = seq(0,24, by = 4))+
scale_y_continuous(name = "Mean survival", sec.axis =sec_axis (trans=~./80, name = "Precipitation"))+
scale_color_manual(name =NULL,
breaks =c("C", "CS", "O", "W", "ligthblue"),
values=c( "#C16622FF", "#225EA8","#FECC5C", "#006D2C", "lightblue"),
labels =c ("Cage + No shade", "Cage + Shade", "No cage + No shade", "Wooded", "Precipitation"))+
labs (x="Time",
y="Mean seedling survival per subplot",
# title="Seedling survival over time",
title=NULL,
# subtitle = "Seedling survival on the Cortana and JJT site. Seedlings were counted between fall
# 2019 to fall 2020.",
size = 16)+
# facet_wrap(site~oak, ncol=3, drop = T)+
theme_minimal()+
theme (
legend.justification = "center",
legend.position = "top",
strip.placement = "outside",
# axis.text.x=element_text(angle=45, vjust=0.5),
plot.title = element_text (size = 16),
plot.title.position = "plot",
axis.line.x = element_line(),
axis.line.y = element_line(),
axis.title.y = element_text(size =10.5, vjust = 1),
axis.title.x = element_text(size =10.5, vjust = 1),
#strip.background = element_blank(),
strip.text.y = element_text(size =9.5),
strip.text.x= element_text(size =9.5, margin = margin (0,0,5,0)),
panel.spacing.x = unit(0.5,"lines"),
# panel.grid=element_blank())
#modifies just the vertical graphs (space between top and bottom)
panel.margin.y=unit (0.4, "lines"),
panel.grid.minor.y = element_line(color = "lightgrey"))
创建于 2024-01-16，使用 reprex v2.0.2
输入
merged_data_date<-structure(list(oak = c("Live", "Red", "Shin", "Red", "Live",
"Shin", "Red", "Shin", "Red", "Shin", "Shin", "Shin", "Shin",
"Live", NA, "Shin", "Red", "Red", "Red", "Red", "Red", "Red",
"Live", "Red", "Red", "Shin", "Live", "Red", "Live", "Live",
"Live", "Live", "Shin", "Red", "Red", "Red", "Shin", "Live",
"Shin", "Live", "Live", "Shin", NA, NA, "Shin", "Live", "Red",
"Red", "Red", NA), plot = c("CS", "C", "C", "O", "O", "C", "O",
"W", "O", "C", "CS", "C", "CS", "W", NA, "O", "W", "CS", "O",
"CS", "CS", "O", "C", "W", "O", "O", "W", "C", "O", "C", "C",
"O", "W", "O", "O", "CS", "O", "C", "CS", "CS", "O", "CS", NA,
NA, "C", "O", "W", "W", "C", NA), date = structure(c(18475, 18048,
18109, 18506, 18048, 18078, 18170, 18109, 18048, 18170, 18475,
18506, 18048, 18109, 18017, 18506, 18078, 18048, 18475, 17956,
18506, 18109, 18170, 18078, 18506, 18506, 18078, 18475, 18170,
18475, 18048, 18506, 18078, 17956, 18170, 18475, 18078, 18078,
18078, 18048, 18048, 18109, 18322, 18353, 17956, 17956, 18475,
17956, 18048, 18414), class = "Date"), site = c("Cortana", "JJT",
"Cortana", "JJT", "JJT", "JJT", "JJT", "JJT", "Cortana", "Cortana",
"Cortana", "Cortana", "JJT", "Cortana", NA, "Cortana", "JJT",
"JJT", "Cortana", "JJT", "JJT", "JJT", "JJT", "Cortana", "Cortana",
"JJT", "Cortana", "JJT", "JJT", "Cortana", "Cortana", "JJT",
"JJT", "Cortana", "Cortana", "Cortana", "JJT", "JJT", "JJT",
"JJT", "Cortana", "JJT", NA, NA, "JJT", "JJT", "JJT", "Cortana",
"Cortana", NA), mean = c(8.6, 17.2, 10.8, 0, 8, 14.2, 0, 6, 15.2,
10.4, 3.6, 2.8, 18.8, 4.2, NA, 3.6, 16.8, 22.4, 0, 14.2, 18.6,
17.4, 0, 9.6, 0, 0, 4.8, 0, 0, 0.4, 6.8, 0, 6.2, 7.8, 15.6, 7,
15.6, 10.6, 19, 9.8, 7, 19.2, NA, NA, 2.4, 1, 5.6, 5.6, 16.4,
NA), sd = c(1.69115345252878, 1.59373774505092, 1.82756668824971,
0, 0.447213595499958, 1.2, 0, 3.09838667696593, 1.46287388383278,
2.22710574513201, 0.92736184954957, 1.35646599662505, 1.39283882771841,
1.24096736459909, NA, 1.6, 1.98494332412792, 1.20830459735946,
0, 2.24499443206436, 2.11187120819429, 0.6, 0, 3.85486705347928,
0, 0, 1.31909059582729, 0, 0, 0.4, 0.374165738677394, 0, 3.18433666561813,
1.15758369027902, 1.4, 1.92353840616713, 0.509901951359279, 0.748331477354788,
1.09544511501033, 1.49666295470958, 1.30384048104053, 1.01980390271856,
NA, NA, 0.678232998312527, 0.632455532033676, 2.92574776766556,
1.69115345252878, 1.80554700852678, NA), max = c(10.2911534525288,
18.7937377450509, 12.6275666882497, 0, 8.44721359549996, 15.4,
0, 9.09838667696593, 16.6628738838328, 12.627105745132, 4.52736184954957,
4.15646599662505, 20.1928388277184, 5.44096736459909, NA, 5.2,
18.7849433241279, 23.6083045973595, 0, 16.4449944320644, 20.7118712081943,
18, 0, 13.4548670534793, 0, 0, 6.11909059582729, 0, 0, 0.8, 7.17416573867739,
0, 9.38433666561813, 8.95758369027902, 17, 8.92353840616713,
16.1099019513593, 11.3483314773548, 20.0954451150103, 11.2966629547096,
8.30384048104053, 20.2198039027186, NA, NA, 3.07823299831253,
1.63245553203368, 8.52574776766556, 7.29115345252878, 18.2055470085268,
NA), min = c(6.90884654747122, 15.6062622549491, 8.97243331175029,
0, 7.55278640450004, 13, 0, 2.90161332303407, 13.7371261161672,
8.17289425486799, 2.67263815045043, 1.44353400337495, 17.4071611722816,
2.95903263540091, NA, 2, 14.8150566758721, 21.1916954026405,
0, 11.9550055679356, 16.4881287918057, 16.8, 0, 5.74513294652072,
0, 0, 3.48090940417271, 0, 0, 5.55111512312578e-17, 6.42583426132261,
0, 3.01566333438187, 6.64241630972098, 14.2, 5.07646159383287,
15.0900980486407, 9.85166852264521, 17.9045548849897, 8.30333704529042,
5.69615951895947, 18.1801960972814, NA, NA, 1.72176700168747,
0.367544467966324, 2.67425223233444, 3.90884654747122, 14.5944529914732,
NA), monthprcp = c(0.0496551724137931, 0.1475, 0.0316071428571429,
0.221166666666667, 0.1475, 0.0404838709677419, 0.140645161290323,
0.0316071428571429, 0.1475, 0.140645161290323, 0.0496551724137931,
0.221166666666667, 0.1475, 0.0316071428571429, 0.207692307692308,
0.221166666666667, 0.0404838709677419, 0.1475, 0.0496551724137931,
0.0323214285714286, 0.221166666666667, 0.0316071428571429, 0.140645161290323,
0.0404838709677419, 0.221166666666667, 0.221166666666667, 0.0404838709677419,
0.0496551724137931, 0.140645161290323, 0.0496551724137931, 0.1475,
0.221166666666667, 0.0404838709677419, 0.0323214285714286, 0.140645161290323,
0.0496551724137931, 0.0404838709677419, 0.0404838709677419, 0.0404838709677419,
0.1475, 0.1475, 0.0316071428571429, 0.0920967741935484, 0.0646551724137931,
0.0323214285714286, 0.0323214285714286, 0.0496551724137931, 0.0323214285714286,
0.1475, 0.069)), row.names = c(NA, -50L), class = c("tbl_df",
"tbl", "data.frame"))
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