ggplot2 - GGPlot 组合/叠加柱形图和折线图(甘特图)

Question

我想将降雨数据(列)叠加在包含“建议播种窗口”和实际播种日期的甘特图上。从数据集中，我可以单独创建两者，但不能在一张图表上创建。非常感谢任何指点。

## plot Gantt chart with suggested sowing dates and actual sowing dates
sowdate.df$Element <- factor(sowdate.df$Element,levels=c("SOWING DATE","Dart","Spitfire","Suntop","Beckom","Flanker","Lancer","Sunmax","Kittyhawk"))
ggplot(sowdate.df, aes(Date1, Element, Color=Category, group=Item)) +
  geom_line(size = 10) 

## plot rainfall
ggplot(sowdate.df, aes(Date1, rain)) + geom_col()


## combine Gantt and rainfall
ggplot(sowdate.df) + 
  geom_col(aes(Date1, rain), size = 1, color = "darkblue", fill = "white") +
  geom_line(aes(Date1, Element, Color=Category, group=Item), size = 1.5, color="red", group = 1)



      Item     Element    Category Start-End      Date1 rain
1     1      Beckom     Variety     Start 2018-05-07   NA
2     2        Dart     Variety     Start 2018-06-01   NA
3     3     Flanker     Variety     Start 2018-05-01   NA
4     4   Kittyhawk     Variety     Start 2018-04-01   NA
5     5      Lancer     Variety     Start 2018-05-01   NA
6     6 SOWING DATE Sowing date     Start 2018-06-06   NA
7     7 SOWING DATE Sowing date     Start 2018-06-26   NA
8     8 SOWING DATE Sowing date     Start 2018-07-03   NA
9     9 SOWING DATE Sowing date     Start 2018-07-12   NA
10   10    Spitfire     Variety     Start 2018-05-21   NA
11   11      Sunmax     Variety     Start 2018-04-15   NA
12   12      Suntop     Variety     Start 2018-05-07   NA
13    1      Beckom     Variety       End 2018-05-31   NA
14    2        Dart     Variety       End 2018-06-30   NA
15    3     Flanker     Variety       End 2018-05-21   NA
16    4   Kittyhawk     Variety       End 2018-05-07   NA
17    5      Lancer     Variety       End 2018-05-21   NA
18    6 SOWING DATE Sowing date       End 2018-06-07   NA
19    7 SOWING DATE Sowing date       End 2018-06-27   NA
20    8 SOWING DATE Sowing date       End 2018-07-04   NA
21    9 SOWING DATE Sowing date       End 2018-07-13   NA
22   10    Spitfire     Variety       End 2018-06-21   NA
23   11      Sunmax     Variety       End 2018-05-07   NA
24   12      Suntop     Variety       End 2018-06-07   NA
25   13        <NA>    Rainfall      <NA> 2018-04-14  3.0
26   14        <NA>    Rainfall      <NA> 2018-03-30  7.0
27   15        <NA>    Rainfall      <NA> 2018-06-10  3.5
28   16        <NA>    Rainfall      <NA> 2018-06-18  4.0
29   17        <NA>    Rainfall      <NA> 2018-06-28 13.5
30   18        <NA>    Rainfall      <NA> 2018-07-23  3.0
31   19        <NA>    Rainfall      <NA> 2018-08-05  6.0
32   20        <NA>    Rainfall      <NA> 2018-08-25 23.0
33   21        <NA>    Rainfall      <NA> 2018-09-10  5.0

Answer 1

正如您在发布的图像上所看到的 - 显示的图仅覆盖两个图。虽然这也可以用 ggplot2 完成，但我觉得这不是很优雅，而且可能非常棘手，因为您需要找到两个图的确切位置，以便它看起来整洁。

您使用 geom_line 并将因子水平作为 y 值的解决方法很有趣，但我不确定是否如此理想。

无论如何 - 这可能是您问题的核心。您混合了不同的 y 度量 - 并且它们属于不同的类别。一个图的因子水平，另一个图的数字/整数。这是有问题的。我不会努力将它们强制到一个 y 轴，但我宁愿创建两个图并将它们与一个图组合包(例如 patchwork)组合起来。就像这样

我已经重命名了您的列，正在使用 GitHub 用户 @alisdaire47 提供的包来读取您的数据，并且还更改了一些列以实现绘图。关键是使用正确的类:日期作为日期，数字作为数字。

首先读取您的数据:

sowdate.df <- read.so::read_so('Item     Element    Category Start_End      Date1 rain
1     1      Beckom     Variety     Start 2018-05-07   NA
2     2        Dart     Variety     Start 2018-06-01   NA
3     3     Flanker     Variety     Start 2018-05-01   NA
4     4   Kittyhawk     Variety     Start 2018-04-01   NA
5     5      Lancer     Variety     Start 2018-05-01   NA
6     6 SOWING DATE Sowing date     Start 2018-06-06   NA
7     7 SOWING DATE Sowing date     Start 2018-06-26   NA
8     8 SOWING DATE Sowing date     Start 2018-07-03   NA
9     9 SOWING DATE Sowing date     Start 2018-07-12   NA
10   10    Spitfire     Variety     Start 2018-05-21   NA
11   11      Sunmax     Variety     Start 2018-04-15   NA
12   12      Suntop     Variety     Start 2018-05-07   NA
13    1      Beckom     Variety       End 2018-05-31   NA
14    2        Dart     Variety       End 2018-06-30   NA
15    3     Flanker     Variety       End 2018-05-21   NA
16    4   Kittyhawk     Variety       End 2018-05-07   NA
17    5      Lancer     Variety       End 2018-05-21   NA
18    6 SOWING DATE Sowing date       End 2018-06-07   NA
19    7 SOWING DATE Sowing date       End 2018-06-27   NA
20    8 SOWING DATE Sowing date       End 2018-07-04   NA
21    9 SOWING DATE Sowing date       End 2018-07-13   NA
22   10    Spitfire     Variety       End 2018-06-21   NA
23   11      Sunmax     Variety       End 2018-05-07   NA
24   12      Suntop     Variety       End 2018-06-07   NA
25   13        <NA>    Rainfall      <NA> 2018-04-14  3.0
26   14        <NA>    Rainfall      <NA> 2018-03-30  7.0
27   15        <NA>    Rainfall      <NA> 2018-06-10  3.5
28   16        <NA>    Rainfall      <NA> 2018-06-18  4.0
29   17        <NA>    Rainfall      <NA> 2018-06-28 13.5
30   18        <NA>    Rainfall      <NA> 2018-07-23  3.0
31   19        <NA>    Rainfall      <NA> 2018-08-05  6.0
32   20        <NA>    Rainfall      <NA> 2018-08-25 23.0
33   21        <NA>    Rainfall      <NA> 2018-09-10  5.0')
#> Warning: 8 parsing failures.
#> row col  expected    actual         file
#>   6  -- 6 columns 8 columns literal data
#>   7  -- 6 columns 8 columns literal data
#>   8  -- 6 columns 8 columns literal data
#>   9  -- 6 columns 8 columns literal data
#>  18  -- 6 columns 8 columns literal data
#> ... ... ......... ......... ............
#> See problems(...) for more details.

现在是情节

library(tidyverse)
library(patchwork)

准备数据(困惑是由于值缩放到因子水平所致)

sowdate <- sowdate.df %>% mutate(element_f = factor(Element,levels=c("SOWING DATE","Dart","Spitfire","Suntop","Beckom","Flanker","Lancer","Sunmax","Kittyhawk")),
                                 date = as.Date(Date1),
                                 rain = as.numeric(rain),
                                 rain_scaled = rain*max(length(levels(element_f))/max(rain, na.rm = TRUE)))
#> Warning: NAs introduced by coercion

方法 1 - 使用拼凑法组合绘图。我推荐这样做，以免将不同的类混合到一个y中。

p1 <- ggplot(sowdate, aes(date, element_f, Color = Category, group = Item)) +
  geom_line(size = 10) +
  theme(axis.title.x = element_blank(),
        axis.text.x = element_blank(),
        axis.ticks.x = element_blank(),
        plot.margin = margin(b = 0))
p2 <- ggplot(sowdate) +
  geom_col(aes(date, rain)) +
  theme(plot.margin = margin(t = 0))
p1 + p2 + plot_layout(nrow = 2, )
#> Warning: Removed 8 rows containing missing values (geom_path).
#> Warning: Removed 24 rows containing missing values (position_stack).

我从第一个图以及下图和上图边距中删除了轴文本、标题和刻度，以使它们更靠近

方法 2 组合不同的变量类(我不建议这样做。这会变得非常困惑，正如您在上面和下面看到的那样)。 您需要将降雨值缩放到因子水平，以便列重叠并且不会变得太长。 现在这需要第二个 y 轴。为此，您必须将因子级别设置为数字，然后为左侧 y 轴创建中断和标签，然后将降雨值重新转换为其实际值，并希望中断能够发挥作用。我不认为第二个 y 轴真的有助于阅读图表。

max_rain <- max(sowdate$rain,na.rm = TRUE)
breaks_ax <- 1:length(levels(sowdate$element_f)) - sum(is.na(levels(sowdate$element_f)))
labels_ax <- as.character(levels(sowdate$element_f)[which(!is.na(levels(sowdate$element_f)))])

ggplot(sowdate, aes(date, as.numeric(element_f), Color = Category, group=Item)) +
  geom_line(size = 10) +
  geom_col(aes(date, rain_scaled)) +
  scale_y_continuous(breaks = breaks_ax, labels = labels_ax, 
                     sec.axis = sec_axis(~ .*max_rain/ max(length(levels(sowdate$element_f))))) +
  labs(y = 'Element')
#> Warning: Removed 24 rows containing missing values (position_stack).
#> Warning: Removed 17 rows containing missing values (geom_path).

^{由reprex package于2020年1月22日创建(v0.3.0)}