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在这种情况下，如何在tidyverse中将数据管道传输到stat_function（）？

doctorate 发表于 Dev
26
博士学位

对于下面的数据集，我想使用dnorm内部函数来绘制与正态分布曲线重叠的直方图stat_function()。

微机

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0.130856852575324, -0.257261454361207, 0.781268129887966, 0.188349618322601, 
-0.411480727522284, -0.451157474464974, -0.289473810164464, -1.61384522197885, 
-1.07648025754191, -1.08683366758667, -1.00806118810575, -1.96103491804365, 
-4.00654026954256, 0.0213791245613211, 2.52869026577227, -0.604681702818922, 
0.142711931394348, -1.88501035846813, 0.790036414060718, -4.00654026954256, 
-0.104275169168235, -0.685768260039533, 0.380328419010124, -0.945871357510961, 
-0.577973901507273, -0.99349940615255, -0.605299870925472, -0.177860837858082, 
0.315610377279169, -1.23378697795298, -0.584227716636569, -1.38709176909219, 
-1.47097512481175, -1.26829326875794, 0.324795321274064, -0.825541248166343, 
-1.41098729684803, -0.186522559173058, -1.79514545176311, -0.153762646771485, 
1.72477747423386, -0.646847099824719, -4.00654026954256, -2.19041294177219, 
0.361907714803453, -1.06413237751191, 0.153299426245554, -1.08784753452048, 
-1.31007738176985, -0.979129327388845, -0.773826249565108, -1.36239979168797, 
-0.521851034767972, -0.531686127246093, -0.773635539601728, -1.2461950014608, 
-1.81279653003212, -1.27751707732076, -0.355737228358993, 0.81406668354316, 
-0.223750301006649, -0.425476061402947, -0.236234048814492, 1.71988538759175, 
2.78897727385525, -1.1063009370049, -1.28238725888469, -0.0604231015948721, 
-0.971107771695997, 0.229371740028129, -1.01332291672405, -0.0661293467445485, 
-0.44297255252896, -0.336008667606201, -0.85231732101295, -0.0742519833703415, 
-0.193719473678246, -0.349414524391744, -4.00654026954256, 0.122502623752731, 
-0.1388904885138, -0.794110687208534, 0.642472620652816, 0.849526344895428, 
-0.169137853616827, -0.568626972840837, -0.142840930422038, -0.505350852565564, 
-0.413932605655479, -1.24205839266656, -2.35540284019113, 0.381229921460069, 
-4.00654026954256, -1.08705046472179, -0.934984680113084, -0.796697155239635, 
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

当使用pivot_longer() 与ggplot代码分开的数据收集数据时，它可以工作。绘制直方图和曲线。但是，正如@ G.Grothendieck所建议的那样dnorm，stat_function()它看不到传递的参数mean和自sd变量，因此我们在所有食品中始终看到相同的曲线，而没有任何变化。

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

在此处输入图片说明

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，它会生成一个带有直方图但没有曲线的图。

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

输出量

在此处输入图片说明

代码方案3：也部分工作

即使使用代字号并将p1$logAmt其显式传递到，曲线也不会显示stat_function()。

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

题：

如何使stat_function()上面的流水线数据接受参数？

阿尔特

首先，我用大括号括起来。然后在第一个调用中显式引用数据，ggplot并在内部再次引用stat_function：

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()
  }

编辑：如果您想要特定于方面的法线，我将在绘制之前生成那些并用于geom_line连接：

library(tidyverse)

mwe %>%
  pivot_longer(cols = colnames(.), names_to = "Food", values_to = "logAmt") %>%
  group_by(Food) %>%
  mutate(
    PredAmt = dnorm(logAmt, mean(logAmt), sd(logAmt))
  ) %>%
  ggplot(aes(x = logAmt)) +
  geom_histogram(aes(y = ..density..), fill= "white", colour = "black", binwidth = 1) +
  geom_line(aes(y = PredAmt), color = 'black', size = 1) +
  labs(x = "log Amt", y = "Density") + 
  facet_wrap(vars(Food)) +
  theme_linedraw()

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