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作者: 兔子不会武 | 来源:发表于2022-02-18 15:34 被阅读0次

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ggplot2

最近想用ggplot2画一个点、线的图，发现有点超纲，搞了好久才搞明白。

要求如下

点和线的图例分开
点和线都有不同的颜色
点不能有边框
有副坐标轴

注意要点

数据集尽量写成大长表（术语是什么不太清楚），大概就是数据集的结构最好不要是这种：

          DATE  a  b  c
 1: 2021-01-01  1 11 21
 2: 2021-01-02  2 12 20
 3: 2021-01-03  3 13 21
 4: 2021-01-04  4 14 20
 5: 2021-01-05  5 15 21
 6: 2021-01-06  6 16 20
 7: 2021-01-07  7 17 21
 8: 2021-01-08  8 18 20
 9: 2021-01-09  9 19 21
10: 2021-01-10 10 20 20

而要写成这种：

          DATE variable value
 1: 2021-01-01        a     1
 2: 2021-01-02        a     2
 3: 2021-01-03        a     3
 4: 2021-01-04        a     4
 5: 2021-01-05        a     5
 6: 2021-01-06        a     6
 7: 2021-01-07        a     7
 8: 2021-01-08        a     8
 9: 2021-01-09        a     9
10: 2021-01-10        a    10
11: 2021-01-01        b    11
12: 2021-01-02        b    12
13: 2021-01-03        b    13
14: 2021-01-04        b    14
15: 2021-01-05        b    15
16: 2021-01-06        b    16
17: 2021-01-07        b    17
18: 2021-01-08        b    18
19: 2021-01-09        b    19
20: 2021-01-10        b    20
21: 2021-01-01        c    21
22: 2021-01-02        c    20
23: 2021-01-03        c    21
24: 2021-01-04        c    20
25: 2021-01-05        c    21
26: 2021-01-06        c    20
27: 2021-01-07        c    21
28: 2021-01-08        c    20
29: 2021-01-09        c    21
30: 2021-01-10        c    20
          DATE variable value

副坐标轴的加法有点反人类。要把副坐标轴的数据映射到主坐标轴的范围内，然后副坐标轴的设置同样根据主坐标轴映射关系进行调整。如：假设主坐标轴的数据范围在[10, 20]之间，而副坐标轴的范围在[-100， 200]之间，则，找到主副坐标轴的线性关系，即 $y = kx + b$ （其中，x代表副坐标轴的数据， y代表主坐标轴的数据，该例子中 $k = (20 - 10) / (200 - (-100)) = 0.03333$ ， $b = 13.3333$ ），则在画图过程中，用y = kx + b将副坐标轴的数据映射到主坐标轴的范围里，加负坐标轴的时候，用 $x = (y - b) / k$ 公式构建出副坐标轴。
geom_poine和geom_line在都有颜色colour属性时，若要将point和line的图例区分开，需要在geom_point中使用fill参数（而不要用colour，把这个属性留给line用）。这里需要注意的是，geom_point函数的fill参数，只在shape在21-25之间才有效（这点经常忘，导致每次想用fill参数的时候发现都无效）。然而，shape在21-25之间的时候默认是有边框的（即stroke参数控制的属性），如果想去掉边框，网上好多地方说设置stroke = 0，但是发现不好用，而应该是stroke = NA（猜测这个可能和电脑环境 / R的版本等有关系）。
geom_point中stroke的属性体现不在图例中，即我在geom_point(aes(x = DATE, y = VALUE, fill = POINT, stroke = NA))这样写，发现图例里面point还是有黑边（！！！逼死强迫症！！！），这个时候，需要加上这样一条：p <- p +guides(fill = guide_legend(override.aes = list(stroke = NA)))，强制把图例里面的边框去掉！

最后附上代码例子

library(data.table)
library(ggplot2)

sec_dt <- data.table::data.table(
  DATE = c("2021/10/11","2021/10/12","2021/10/13",
           "2021/10/14","2021/10/15","2021/10/18","2021/10/19",
           "2021/10/20","2021/10/21","2021/10/22","2021/10/25","2021/10/26",
           "2021/10/27","2021/10/28","2021/10/29","2021/10/31",
           "2021/11/1","2021/11/2","2021/11/3","2021/11/4","2021/11/5",
           "2021/11/8","2021/10/11","2021/10/12","2021/10/13","2021/10/14",
           "2021/10/15","2021/10/18","2021/10/19","2021/10/20",
           "2021/10/21","2021/10/22","2021/10/25","2021/10/26","2021/10/27",
           "2021/10/28","2021/10/29","2021/10/31","2021/11/1",
           "2021/11/2","2021/11/3","2021/11/4","2021/11/5","2021/11/8",
           "2021/10/11","2021/10/12","2021/10/13","2021/10/14","2021/10/15",
           "2021/10/18","2021/10/19","2021/10/20","2021/10/21",
           "2021/10/22","2021/10/25","2021/10/26","2021/10/27","2021/10/28",
           "2021/10/29","2021/10/31","2021/11/1","2021/11/2",
           "2021/11/3","2021/11/4","2021/11/5","2021/11/8","2021/10/11",
           "2021/10/12","2021/10/13","2021/10/14","2021/10/15","2021/10/18",
           "2021/10/19","2021/10/20","2021/10/21","2021/10/22",
           "2021/10/25","2021/10/26","2021/10/27","2021/10/28","2021/10/29",
           "2021/10/31","2021/11/1","2021/11/2","2021/11/3",
           "2021/11/4","2021/11/5","2021/11/8"),
  LINE = c("QUANTITY","QUANTITY","QUANTITY",
           "QUANTITY","QUANTITY","QUANTITY","QUANTITY","QUANTITY","QUANTITY",
           "QUANTITY","QUANTITY","QUANTITY","QUANTITY","QUANTITY",
           "QUANTITY","QUANTITY","QUANTITY","QUANTITY","QUANTITY",
           "QUANTITY","QUANTITY","QUANTITY","PRICE","PRICE","PRICE",
           "PRICE","PRICE","PRICE","PRICE","PRICE","PRICE","PRICE",
           "PRICE","PRICE","PRICE","PRICE","PRICE","PRICE","PRICE",
           "PRICE","PRICE","PRICE","PRICE","PRICE","BUY_POINT",
           "BUY_POINT","BUY_POINT","BUY_POINT","BUY_POINT","BUY_POINT",
           "BUY_POINT","BUY_POINT","BUY_POINT","BUY_POINT","BUY_POINT",
           "BUY_POINT","BUY_POINT","BUY_POINT","BUY_POINT","BUY_POINT",
           "BUY_POINT","BUY_POINT","BUY_POINT","BUY_POINT","BUY_POINT",
           "BUY_POINT","SELL_POINT","SELL_POINT","SELL_POINT",
           "SELL_POINT","SELL_POINT","SELL_POINT","SELL_POINT","SELL_POINT",
           "SELL_POINT","SELL_POINT","SELL_POINT","SELL_POINT",
           "SELL_POINT","SELL_POINT","SELL_POINT","SELL_POINT","SELL_POINT",
           "SELL_POINT","SELL_POINT","SELL_POINT","SELL_POINT",
           "SELL_POINT"),
  POINT = c("QUANTITY","QUANTITY","QUANTITY",
            "QUANTITY","QUANTITY","QUANTITY","QUANTITY","QUANTITY","QUANTITY",
            "QUANTITY","QUANTITY","QUANTITY","QUANTITY","QUANTITY",
            "QUANTITY","QUANTITY","QUANTITY","QUANTITY","QUANTITY",
            "QUANTITY","QUANTITY","QUANTITY","PRICE","PRICE","PRICE",
            "PRICE","PRICE","PRICE","PRICE","PRICE","PRICE","PRICE",
            "PRICE","PRICE","PRICE","PRICE","PRICE","PRICE","PRICE",
            "PRICE","PRICE","PRICE","PRICE","PRICE","BUY_POINT",
            "BUY_POINT","BUY_POINT","BUY_POINT","BUY_POINT","BUY_POINT",
            "BUY_POINT","BUY_POINT","BUY_POINT","BUY_POINT","BUY_POINT",
            "BUY_POINT","BUY_POINT","BUY_POINT","BUY_POINT","BUY_POINT",
            "BUY_POINT","BUY_POINT","BUY_POINT","BUY_POINT","BUY_POINT",
            "BUY_POINT","SELL_POINT","SELL_POINT","SELL_POINT",
            "SELL_POINT","SELL_POINT","SELL_POINT","SELL_POINT","SELL_POINT",
            "SELL_POINT","SELL_POINT","SELL_POINT","SELL_POINT",
            "SELL_POINT","SELL_POINT","SELL_POINT","SELL_POINT","SELL_POINT",
            "SELL_POINT","SELL_POINT","SELL_POINT","SELL_POINT",
            "SELL_POINT"),
  VALUE = c(12500,12500,12500,12500,12500,12500,
            12500,12500,12500,12500,10100,10100,10100,10100,10100,
            10100,10100,10100,10100,10100,10100,0,49.63,50.36,50.06,
            52.8,52.5,50.9,50.99,50.91,50.71,50.06,49.71,50.8,
            51.09,51.27,52.8,52.8,51.07,50.35,50.25,49.24,49.03,
            52.91,49.63,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,
            NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,
            NA,NA,49.71,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,52.91)
)


sec_dt <- sec_dt[, DATE := lubridate::ymd(DATE)]
x1 <- max(sec_dt[LINE == 'QUANTITY', VALUE]) * 2
y1 <- max(sec_dt[LINE == 'PRICE', VALUE])
x2 <- min(sec_dt[LINE == 'QUANTITY', VALUE])
y2 <- min(sec_dt[LINE == 'PRICE', VALUE])

k <- (y2 - y1) / (x2 - x1)
b <- y1 - k*x1
stopifnot(!is.na(k),  !is.na(b))

p <- ggplot(sec_dt, aes(x = DATE)) +
  geom_point(
    aes(y = VALUE, size = POINT, fill = POINT, shape = POINT, stroke = NA),
    data = sec_dt[POINT %in% c('BUY_POINT', 'SELL_POINT')], na.rm = TRUE
  ) +
  geom_line(aes(y = VALUE, linetype = LINE, colour = LINE), data = sec_dt[LINE %in% c('PRICE')]) +
  geom_line(aes(y = VALUE * k + b, linetype = LINE, colour = LINE), data = sec_dt[LINE %in% c('QUANTITY')]) +
  scale_linetype_manual('', values = c('PRICE' = 'solid', 'QUANTITY' = 'dashed')) +
  scale_size_manual('', values = c('BUY_POINT' = 3, 'SELL_POINT' = 3)) +
  scale_fill_manual('', values = c('BUY_POINT' = '#FF0000', 'SELL_POINT' = '#99FF66')) +
  scale_colour_manual('', values = c('PRICE' = '#000000', 'QUANTITY' = '#CC0000')) +
  scale_shape_manual('', values = c('BUY_POINT' = 21, 'SELL_POINT' = 21)) +
  scale_y_continuous(
    name = 'price', limits = c(min(sec_dt[LINE == 'PRICE', VALUE]), max(sec_dt[LINE == 'PRICE', VALUE])),
    sec.axis = sec_axis(~ (. - b) / k , name = "quantity")
  ) +
  guides(
    fill = guide_legend(override.aes = list(stroke = NA))
  ) +
  labs(x = NULL, y = NULL) +
  theme_minimal() +
  theme(
    plot.title = element_text(hjust = 0.5),
    panel.grid.minor = element_blank(),
    panel.border = element_blank(),
    axis.title.x = element_text(size = 12),
    axis.title.y = element_text(size = 12),
    legend.text = element_text(size = 8),
    legend.position = "top"
  )
p

结果如下图

image.png

echarts4r

用法

在使用R的echarts4r包的过程中，发现里面有些函数挺反人类的，比如加双x轴，搞了好久都没搞出来，严重怀疑是这个包的bug。但是，全包最NB的函数就是e_list()，所有JSON option能实现的，用这个函数全可以实现！所以，如果在使用的过程中，对于某些特殊的画图需求，发现包里自带的函数难以实现，直接上e_list。比如在echarts4r的官网里的这个例子：

N <- 20 # data points

opts <- list(
  xAxis = list(
    type = "category",
    data = LETTERS[1:N]
  ),
  yAxis = list(
    type = "value"
  ),
  series = list(
    list(
      type = "line",
      data = round(runif(N, 5, 20))
    )
  )
)

p <- e_charts() |> 
  e_list(opts)

另外一个好用的函数为e_inspect，这个函数就是返回图的JSON options的源码，如果画的图有错误，可以通过源码来检查哪里写的有问题，接上面的例子：

library(magrittr)

json <- p %>%
  e_inspect(
    json = TRUE,
    pretty = TRUE
  )
json

综上所述，搭配使用e_inspect和e_list函数，可以解决几乎所有的画图问题。

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ggplot2

要求如下

注意要点

最后附上代码例子

结果如下图

echarts4r

相关网址

用法

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