给定 sd 值将误差线添加到多个 geom_point 变量
Add error bars to multiple geom_point variables given sd values
我想根据每个变量的 SD 值绘制误差线。我尝试了一些东西(见底部),但我相信有一种方法可以为每个变量的每个数据点绘制单独的 sd?
Location = c(1,2,3,4,5,6,7)
A = c(1.23, 0.95,0.65,0.74,0.51,0.34,0.28)
B = c(6.77,7.56,3.88,6.52,4.38,11.94,14.97)
C = c(75.45,86.66,103.36,123.2,107.53,128.9,128.49)
SD_A =c(0.10,0.03,0.01,0.05,0.00,0.01,0.02)
SD_B=c(0.02,1.05,1.97,1.45,0.60,1.88,1.45)
SD_C = c(3.56,7.46,26.1,10,10.8,10,29.03)
data = data.frame(Location, A, B, C)
data_sd = data.frame(Location, A, B, C, SD_A, SD_B, SD_C)
library(ggplot2)
library(tidyr)
library(dplyr)
data %>% pivot_longer(.,-Location, names_to = "var",values_to = "val") %>%
filter(!is.na(val)) %>%
mutate(NewVar = var) %>%
add_row(., Location = c(1,1),
var = c("B","B"),
val = c(0,30),
NewVar = c("Out","Out")) %>%
ggplot(aes(x = Location, y = val, group = NewVar))+
geom_point(aes(Location, val, shape=var), size =2) +
ylab("")+
facet_wrap(.~var, strip.position = "left", ncol = 1, scales = "free_y", labeller = as_labeller(c(A= "A", B= "B", C= "C")))+
theme_bw() + theme(text = element_text(size=15), axis.text.x = element_text(colour = "black"), axis.text.y = element_text(colour = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(), strip.background = element_blank(),
strip.placement = "outside")+
scale_x_continuous(breaks = 1:7) + theme(legend.position = "none") +scale_shape_manual(values=c(19, 0, 15))+
我尝试了以下方法,但我认为问题可能在于重构数据?
geom_errorbar(aes(ymin = var-sd, ymax = var+sd),width = 0.2) # I do not have a sd column
geom_errorbarh(aes(xmin = xmin,xmax = xmax)) # I don't want xmax and xmin since the sd are provided already
- 注意我已经创建了一个仅包含数据的 df 和一个包含数据+sd
data_sd
的 df,这是我们想要使用的。
一种方法是改变您使用的方式 pivot_longer
:
data_sd %>%
rename_with(.cols = A:C,~str_c("Data_",.) ) %>%
pivot_longer(-Location, names_sep = "_", names_to = c(".value","Var"))
# A tibble: 21 x 4
Location Var Data SD
<dbl> <chr> <dbl> <dbl>
1 1 A 1.23 0.1
2 1 B 6.77 0.02
3 1 C 75.4 3.56
4 2 A 0.95 0.03
5 2 B 7.56 1.05
6 2 C 86.7 7.46
7 3 A 0.65 0.01
8 3 B 3.88 1.97
9 3 C 103. 26.1
10 4 A 0.74 0.05
# … with 11 more rows
现在数据值和 SD 在同一行。
data_sd %>%
rename_with(.cols = A:C,~str_c("Data_",.) ) %>%
pivot_longer(-Location, names_sep = "_", names_to = c(".value","Var")) %>%
filter(!is.na(Var)) %>%
mutate(NewVar = Var) %>%
add_row(Location = c(1,1),
Var = c("B","B"),
Data = c(0,30),
NewVar = c("Out","Out")) %>%
ggplot(aes(x = Location, y = Data, group = NewVar))+
geom_point(aes(Location, Data, shape=Var), size =2) +
ylab("")+
facet_wrap(.~Var, strip.position = "left", ncol = 1, scales = "free_y", labeller = as_labeller(c(A= "A", B= "B", C= "C")))+
theme_bw() + theme(text = element_text(size=15), axis.text.x = element_text(colour = "black"), axis.text.y = element_text(colour = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(), strip.background = element_blank(),
strip.placement = "outside")+
scale_x_continuous(breaks = 1:7) + theme(legend.position = "none") +scale_shape_manual(values=c(19, 0, 15)) +
geom_errorbar(aes(ymin = Data-SD, ymax = Data+SD),width = 0.2)
如果您想单独更改 y 轴限制,您可以使用 facetscales
包。
#remotes::install_github("zeehio/facetscales")
library(facetscales)
data_sd %>%
rename_with(.cols = A:C,~str_c("Data_",.) ) %>%
pivot_longer(-Location, names_sep = "_", names_to = c(".value","Var")) %>%
filter(!is.na(Var)) %>%
mutate(NewVar = Var) %>%
ggplot(aes(x = Location, y = Data, group = NewVar))+
geom_point(aes(Location, Data, shape=Var), size =2) +
facet_grid_sc(rows = vars(Var), switch = "y",
scales = list(y = list(A = scale_y_continuous(),
B = scale_y_continuous(limits = c(0,30)),
C = scale_y_continuous()))) +
theme_bw() + theme(text = element_text(size=15), axis.text.x = element_text(colour = "black"), axis.text.y = element_text(colour = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(), strip.background = element_blank(),
strip.placement = "outside")+
scale_x_continuous(breaks = 1:7) + theme(legend.position = "none") + scale_shape_manual(values=c(19, 0, 15)) +
geom_errorbar(aes(ymin = Data-SD, ymax = Data+SD),width = 0.2)
我想根据每个变量的 SD 值绘制误差线。我尝试了一些东西(见底部),但我相信有一种方法可以为每个变量的每个数据点绘制单独的 sd?
Location = c(1,2,3,4,5,6,7)
A = c(1.23, 0.95,0.65,0.74,0.51,0.34,0.28)
B = c(6.77,7.56,3.88,6.52,4.38,11.94,14.97)
C = c(75.45,86.66,103.36,123.2,107.53,128.9,128.49)
SD_A =c(0.10,0.03,0.01,0.05,0.00,0.01,0.02)
SD_B=c(0.02,1.05,1.97,1.45,0.60,1.88,1.45)
SD_C = c(3.56,7.46,26.1,10,10.8,10,29.03)
data = data.frame(Location, A, B, C)
data_sd = data.frame(Location, A, B, C, SD_A, SD_B, SD_C)
library(ggplot2)
library(tidyr)
library(dplyr)
data %>% pivot_longer(.,-Location, names_to = "var",values_to = "val") %>%
filter(!is.na(val)) %>%
mutate(NewVar = var) %>%
add_row(., Location = c(1,1),
var = c("B","B"),
val = c(0,30),
NewVar = c("Out","Out")) %>%
ggplot(aes(x = Location, y = val, group = NewVar))+
geom_point(aes(Location, val, shape=var), size =2) +
ylab("")+
facet_wrap(.~var, strip.position = "left", ncol = 1, scales = "free_y", labeller = as_labeller(c(A= "A", B= "B", C= "C")))+
theme_bw() + theme(text = element_text(size=15), axis.text.x = element_text(colour = "black"), axis.text.y = element_text(colour = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(), strip.background = element_blank(),
strip.placement = "outside")+
scale_x_continuous(breaks = 1:7) + theme(legend.position = "none") +scale_shape_manual(values=c(19, 0, 15))+
我尝试了以下方法,但我认为问题可能在于重构数据?
geom_errorbar(aes(ymin = var-sd, ymax = var+sd),width = 0.2) # I do not have a sd column
geom_errorbarh(aes(xmin = xmin,xmax = xmax)) # I don't want xmax and xmin since the sd are provided already
- 注意我已经创建了一个仅包含数据的 df 和一个包含数据+sd
data_sd
的 df,这是我们想要使用的。
一种方法是改变您使用的方式 pivot_longer
:
data_sd %>%
rename_with(.cols = A:C,~str_c("Data_",.) ) %>%
pivot_longer(-Location, names_sep = "_", names_to = c(".value","Var"))
# A tibble: 21 x 4
Location Var Data SD
<dbl> <chr> <dbl> <dbl>
1 1 A 1.23 0.1
2 1 B 6.77 0.02
3 1 C 75.4 3.56
4 2 A 0.95 0.03
5 2 B 7.56 1.05
6 2 C 86.7 7.46
7 3 A 0.65 0.01
8 3 B 3.88 1.97
9 3 C 103. 26.1
10 4 A 0.74 0.05
# … with 11 more rows
现在数据值和 SD 在同一行。
data_sd %>%
rename_with(.cols = A:C,~str_c("Data_",.) ) %>%
pivot_longer(-Location, names_sep = "_", names_to = c(".value","Var")) %>%
filter(!is.na(Var)) %>%
mutate(NewVar = Var) %>%
add_row(Location = c(1,1),
Var = c("B","B"),
Data = c(0,30),
NewVar = c("Out","Out")) %>%
ggplot(aes(x = Location, y = Data, group = NewVar))+
geom_point(aes(Location, Data, shape=Var), size =2) +
ylab("")+
facet_wrap(.~Var, strip.position = "left", ncol = 1, scales = "free_y", labeller = as_labeller(c(A= "A", B= "B", C= "C")))+
theme_bw() + theme(text = element_text(size=15), axis.text.x = element_text(colour = "black"), axis.text.y = element_text(colour = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(), strip.background = element_blank(),
strip.placement = "outside")+
scale_x_continuous(breaks = 1:7) + theme(legend.position = "none") +scale_shape_manual(values=c(19, 0, 15)) +
geom_errorbar(aes(ymin = Data-SD, ymax = Data+SD),width = 0.2)
如果您想单独更改 y 轴限制,您可以使用 facetscales
包。
#remotes::install_github("zeehio/facetscales")
library(facetscales)
data_sd %>%
rename_with(.cols = A:C,~str_c("Data_",.) ) %>%
pivot_longer(-Location, names_sep = "_", names_to = c(".value","Var")) %>%
filter(!is.na(Var)) %>%
mutate(NewVar = Var) %>%
ggplot(aes(x = Location, y = Data, group = NewVar))+
geom_point(aes(Location, Data, shape=Var), size =2) +
facet_grid_sc(rows = vars(Var), switch = "y",
scales = list(y = list(A = scale_y_continuous(),
B = scale_y_continuous(limits = c(0,30)),
C = scale_y_continuous()))) +
theme_bw() + theme(text = element_text(size=15), axis.text.x = element_text(colour = "black"), axis.text.y = element_text(colour = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(), strip.background = element_blank(),
strip.placement = "outside")+
scale_x_continuous(breaks = 1:7) + theme(legend.position = "none") + scale_shape_manual(values=c(19, 0, 15)) +
geom_errorbar(aes(ymin = Data-SD, ymax = Data+SD),width = 0.2)