在这种情况下，如何在tidyverse中将数据管道传输到stat_function（）？
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篇首语：本文由小常识网(cha138.com)小编为大家整理，主要介绍了在这种情况下，如何在tidyverse中将数据管道传输到stat_function（）？相关的知识，希望对你有一定的参考价值。
对于下面的数据集，我想使用dnorm中的stat_function()函数绘制与正态分布曲线重叠的直方图。
MWE
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1.30050102424142, -0.546206094377298, -0.386648415040902)), class = c("tbl_df",
"tbl", "data.frame"), row.names = c(NA, -218L))
代码方案1：有效
当从ggplot代码中使用pivot_longer() 单独地收集数据时，它起作用了。绘制直方图和曲线。
p1 <- MWE %>%
dplyr::select(Carrot, Nuts, Potato, Cabbage) %>%
tidyr::pivot_longer(cols = colnames(.), names_to = "Food", values_to = "logAmt")
p2 <- ggplot(p1, aes(logAmt)) +
geom_histogram(aes(y = ..density..), fill= "white", colour = "black", binwidth = 1) +
labs(x = "log Amt", y = "Density") +
stat_function(fun=dnorm, args=list(mean= mean(p$logAmt, na.rm = TRUE), sd = sd(p$logAmt, na.rm = TRUE)), colour = "black",size=1) +
facet_wrap(vars(Food)) +
theme_linedraw()
p2
直方图+分布曲线
代码方案2：部分工作
[将用于数据收集和ggplot的两个代码片段合并为一个，并使用波浪号~时，它会形成带有直方图的图，但没有曲线。
p1 <- MWE %>%
dplyr::select(Carrot, Nuts, Potato, Cabbage) %>%
tidyr::pivot_longer(cols = colnames(.), names_to = "Food", values_to = "logAmt") %>%
ggplot(aes(logAmt)) +
geom_histogram(aes(y = ..density..), fill= "white", colour = "black", binwidth = 1) +
labs(x = "log Amt", y = "Density") +
stat_function(fun=dnorm, args=list(mean= ~ mean(logAmt, na.rm = TRUE), sd = ~ sd(logAmt, na.rm = TRUE)), colour = "black",size=1) +
facet_wrap(vars(Food)) +
theme_linedraw()
p1
输出
代码方案3：也部分起作用
即使使用波浪号并且将p1$logAmt显式传递到stat_function()中，曲线也不会出现。
p1 <- MWE %>%
dplyr::select(Carrot, Nuts, Potato, Cabbage) %>%
tidyr::pivot_longer(cols = colnames(.), names_to = "Food", values_to = "logAmt") %>%
ggplot(aes(logAmt)) +
geom_histogram(aes(y = ..density..), fill= "white", colour = "black", binwidth = 1) +
labs(x = "log Amt", y = "Density") +
stat_function(fun=dnorm, args=list(mean= ~mean(p1$logAmt, na.rm = TRUE), sd = ~sd(p1$logAmt, na.rm = TRUE)), colour = "black",size=1) +
facet_wrap(vars(Food)) +
theme_linedraw()
p1
问题：
如何使stat_function()接受上述管道数据的参数？
答案
首先，我将图用大括号括起来。然后，在第一次调用ggplot并再次在stat_function内部时显式引用数据：
mwe %>%
dplyr::select(Carrot, Nuts, Potato, Cabbage) %>%
tidyr::pivot_longer(cols = colnames(.), names_to = "Food", values_to = "logAmt") %>%
ggplot(data =., aes(logAmt)) +
geom_histogram(aes(y = ..density..), fill= "white", colour = "black", binwidth = 1) +
labs(x = "log Amt", y = "Density") +
stat_function(fun=dnorm,
args=list(mean= mean(.$logAmt, na.rm = TRUE),
sd = sd(.$logAmt, na.rm = TRUE)),
colour = "black",size=1) +
facet_wrap(vars(Food)) +
theme_linedraw()
另一答案
stat_function将始终在每个构面上绘制相同的曲线，因此，如果您打算在每个构面上使用不同的法线曲线，则问题中显示的整个方法将不起作用。建议您只使用ggformula软件包。另请注意，使用dplyr::select无效，因为您仍然需要dplyr才能访问%>%。
library(dplyr)
library(tidyr)
library(ggformula)
MWE %>%
select(Carrot, Nuts, Potato, Cabbage) %>%
pivot_longer(cols = colnames(.), names_to = "Food", values_to = "logAmt") %>%
gf_dhistogram( ~ logAmt | Food, data = .) %>%
gf_fitdistr(dist = "dnorm")
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