R有没有办法做相当于geom_jitter但密度ggplot？答案

【问题标题】：R is there a way to do the equivalent of geom_jitter but for a density ggplot?R有没有办法做相当于geom_jitter但密度ggplot？
【发布时间】：2021-08-03 13:56:59
【问题描述】：

我有以下数据框，我用它来创建一个 ggplot，它是我使用 facet_wrap 安排的一组密度图。

structure(list(date = c("2021-07-25", "2021-07-25", "2021-07-25", 
"2021-07-25", "2021-07-25", "2021-07-25", "2021-07-25", "2021-07-25", 
"2021-07-25", "2021-07-25", "2021-07-26", "2021-07-26", "2021-07-26", 
"2021-07-26", "2021-07-26", "2021-07-26", "2021-07-26", "2021-07-26", 
"2021-07-26", "2021-07-26", "2021-07-27", "2021-07-27", "2021-07-27", 
"2021-07-27", "2021-07-27", "2021-07-27", "2021-07-27", "2021-07-27", 
"2021-07-27", "2021-07-27", "2021-07-28", "2021-07-28", "2021-07-28", 
"2021-07-28", "2021-07-28", "2021-07-28", "2021-07-28", "2021-07-28", 
"2021-07-28", "2021-07-28", "2021-07-29", "2021-07-29", "2021-07-29", 
"2021-07-29", "2021-07-29", "2021-07-29", "2021-07-29", "2021-07-29", 
"2021-07-29", "2021-07-29", "2021-07-30", "2021-07-30", "2021-07-30", 
"2021-07-30", "2021-07-30", "2021-07-30", "2021-07-30", "2021-07-30", 
"2021-07-30", "2021-07-30", "2021-07-31", "2021-07-31", "2021-07-31", 
"2021-07-31", "2021-07-31", "2021-07-31", "2021-07-31", "2021-07-31", 
"2021-07-31", "2021-07-31"), Order_Type = structure(c(1L, 1L, 
2L, 2L, 3L, 3L, 8L, 8L, 9L, 9L, 1L, 1L, 2L, 2L, 3L, 3L, 8L, 8L, 
9L, 9L, 1L, 1L, 2L, 2L, 3L, 3L, 8L, 8L, 9L, 9L, 1L, 1L, 2L, 2L, 
3L, 3L, 8L, 8L, 9L, 9L, 1L, 1L, 2L, 2L, 3L, 3L, 8L, 8L, 9L, 9L, 
1L, 1L, 2L, 2L, 3L, 3L, 8L, 8L, 9L, 9L, 1L, 1L, 2L, 2L, 3L, 3L, 
8L, 8L, 9L, 9L), .Label = c("group1", "group2", "group3", 
"group4", "group5", "group6", 
"group7", "group8", "group9"), class = "factor"), 
    ntf_normalized = c(1, 1, 1, 1, 1, 1, 0.5, 0.5, 0.8372252453, 
    0.8372252453, 0.3275361961, 0.3275361961, 1, 1, 1, 1, 0.3275361961, 
    0.3275361961, 0.1840258965, 0.1840258965, 1, 1, 1, 1, 1, 
    1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
    1, 1, 0.1603545867, 0.1603545867, 0.4950785714, 0.4950785714, 
    0.7142857145, 0.7142857145, 1, 1, 1, 1, 1, 1, 1, 1, 0.5526912352, 
    0.5526912352, 1, 1, 1, 1, 0, 0, 1, 1), ntf_first_touch = c(1, 
    1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
    1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
    1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
    1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1), spend = c(25.99294208, 
    25.99294208, 308.2773075, 308.2773075, 206.28925744, 206.28925744, 
    0.00398, 0.00398, 304.77034136, 304.77034136, 410.2332538, 
    410.2332538, 185.819275, 185.819275, 213.72726668, 213.72726668, 
    414.61074958, 414.61074958, 323.66596883, 323.66596883, 570.88491388, 
    570.88491388, 115.2426355, 115.2426355, 234.28878223, 234.28878223, 
    846.78931866, 846.78931866, 336.60236658, 336.60236658, 803.26558903, 
    803.26558903, 258.157645, 258.157645, 214.85833223, 214.85833223, 
    1157.49991513, 1157.49991513, 321.93666812, 321.93666812, 
    523.59701611, 523.59701611, 122.06332, 122.06332, 137.31790493, 
    137.31790493, 724.54289394, 724.54289394, 213.9509169, 213.9509169, 
    393.06862193, 393.06862193, 161.8394165, 161.8394165, 88.23073883, 
    88.23073883, 342.05106384, 342.05106384, 117.82164784, 117.82164784, 
    388.23691524, 388.23691524, 97.247412, 97.247412, 99.12069722, 
    99.12069722, 0, 0, 91.27114294, 91.27114294), names = c("cac_normalized", 
    "cac_first_touch", "cac_normalized", "cac_first_touch", "cac_normalized", 
    "cac_first_touch", "cac_normalized", "cac_first_touch", "cac_normalized", 
    "cac_first_touch", "cac_normalized", "cac_first_touch", "cac_normalized", 
    "cac_first_touch", "cac_normalized", "cac_first_touch", "cac_normalized", 
    "cac_first_touch", "cac_normalized", "cac_first_touch", "cac_normalized", 
    "cac_first_touch", "cac_normalized", "cac_first_touch", "cac_normalized", 
    "cac_first_touch", "cac_normalized", "cac_first_touch", "cac_normalized", 
    "cac_first_touch", "cac_normalized", "cac_first_touch", "cac_normalized", 
    "cac_first_touch", "cac_normalized", "cac_first_touch", "cac_normalized", 
    "cac_first_touch", "cac_normalized", "cac_first_touch", "cac_normalized", 
    "cac_first_touch", "cac_normalized", "cac_first_touch", "cac_normalized", 
    "cac_first_touch", "cac_normalized", "cac_first_touch", "cac_normalized", 
    "cac_first_touch", "cac_normalized", "cac_first_touch", "cac_normalized", 
    "cac_first_touch", "cac_normalized", "cac_first_touch", "cac_normalized", 
    "cac_first_touch", "cac_normalized", "cac_first_touch", "cac_normalized", 
    "cac_first_touch", "cac_normalized", "cac_first_touch", "cac_normalized", 
    "cac_first_touch", "cac_normalized", "cac_first_touch", "cac_normalized", 
    "cac_first_touch"), values = c(25.99294208, 25.99294208, 
    308.2773075, 308.2773075, 206.28925744, 206.28925744, 0.00796, 
    0.00398, 364.024308954985, 152.38517068, 1252.4821948984, 
    410.2332538, 185.819275, 185.819275, 213.72726668, 213.72726668, 
    1265.84711710279, 414.61074958, 1758.80664072733, 323.66596883, 
    570.88491388, 570.88491388, 115.2426355, 115.2426355, 234.28878223, 
    234.28878223, 846.78931866, 846.78931866, 336.60236658, 336.60236658, 
    803.26558903, 803.26558903, 258.157645, 258.157645, 214.85833223, 
    214.85833223, 1157.49991513, 1157.49991513, 321.93666812, 
    321.93666812, 523.59701611, 523.59701611, 122.06332, 122.06332, 
    137.31790493, 137.31790493, 4518.37960391812, 724.54289394, 
    432.155478462706, 213.9509169, 550.296070536911, 393.06862193, 
    161.8394165, 161.8394165, 88.23073883, 88.23073883, 342.05106384, 
    342.05106384, 117.82164784, 117.82164784, 702.448113003837, 
    388.23691524, 97.247412, 97.247412, 99.12069722, 99.12069722, 
    0, 0, 91.27114294, 91.27114294)), row.names = c(NA, -70L), groups = structure(list(
    date = c("2021-07-25", "2021-07-26", "2021-07-27", "2021-07-28", 
    "2021-07-29", "2021-07-30", "2021-07-31"), .rows = structure(list(
        1:10, 11:20, 21:30, 31:40, 41:50, 51:60, 61:70), ptype = integer(0), class = c("vctrs_list_of", 
    "vctrs_vctr", "list"))), row.names = c(NA, -7L), class = c("tbl_df", 
"tbl", "data.frame"), .drop = TRUE), class = c("grouped_df", 
"tbl_df", "tbl", "data.frame"))



ggplot(df1, aes(x = values, fill = names)) +
  geom_density(alpha = 0.3) +
  labs(title = "Advertising", subtitle = "CAC Distribution") +
  theme(plot.title = element_text(hjust = 0.5, face = "bold")) +
  theme(plot.subtitle = element_text(hjust = 0.5)) +
  xlab("CAC") +
  ylab("density") +
  facet_wrap(~Order_Type, scales = 'free')

问题是，我发现 group2 和 group3 中发生的事情有点难以解释。这有点像一个错误。事实证明，group2 和 group3 的数字完全相同，因此其中一条线被删除了。看起来只有一个名称的数据（cac_normalized 但没有 cac_first_touch）。有没有办法稍微改变线路以便看到这两个事件？我知道 geom_point 可以因为这个确切的原因变成 geom_jitter 。如果我将 geom_jitter 放入我的 ggplot 中，我会收到错误消息。如果我更改 geom_density 中的 alpha，它不会做任何事情。有人知道吗？

【问题讨论】：

标签： r ggplot2 density-plot

【解决方案1】：

您可以使用after_stat() 函数对每个后续组进行轻微推动。

library(ggplot2)

ggplot(df1, aes(x = values, fill = names)) +
  geom_density(
    alpha = 0.3,
    aes(y = after_stat(density + 0.0001 * group))
  ) +
  labs(title = "Advertising", subtitle = "CAC Distribution") +
  theme(plot.title = element_text(hjust = 0.5, face = "bold")) +
  theme(plot.subtitle = element_text(hjust = 0.5)) +
  xlab("CAC") +
  ylab("density") +
  facet_wrap(~Order_Type, scales = 'free')

【讨论】：

这是一个很酷的答案。我什至不知道是否有可能以这种方式转变。超级有用