来自单个数据帧的多个或多个时间序列图输出 [英] Several or multiple timeseries plot outputs from a single data frame

问题描述

我已经为这个问题苦苦挣扎了一段时间，如果有人能帮助我，我将不胜感激.

I have been struggling with this problem for a while now and anyone who can help me out I would greatly appreciate it.

首先，我正在处理包含多个时间序列的单个数据框中的时间序列数据.太多，无法单独输出到图表中.我已经尝试通过 ddply() 传递 qplot() 但是 r 告诉我它 qplot 不是一个函数，因此它不会工作.

First off, I am working with time series data in a single data frame containing multiple time series. Too many to output individually into graphs. I have tried passing qplot() through ddply() however r tells me it qplot is not a function and therefore it will not work.

我的数据结构是这样的……

the structure of my data is like this...

goodlocs <- 
 Loc    Year    dir
Artesia 1983    1490
Artesia 1984    1575
Artesia 1986    1567
Artesia 1987    1630
Artesia 1990    1680
Bogota  1983    1525
Bogota  1984    1610
Bogota  1985    1602
Bogota  1986    1665
Bogota  1990    1715
Carlsbad    1983    1560
Carlsbad    1985    1645
Carlsbad    1986    1637
Carlsbad    1987    1700
Carlsbad    1990    1750
Carlsbad    1992    1595
Datil   1987    1680
Datil   1990    1672
Datil   1991    1735
Datil   1992    1785

我有大约 250 个位置 (Locs)，希望能够在如下图所示的图表上查看每个站点的数据，这样我就可以直观地检查我的所有数据.

I have about 250 Locations(Locs) and would like to be able to go over each stations data on a graph like the following one so I can inspect all of my data visually.

Artesia <- goodlocs[goodlocs$Loc == "Artesia",]

qplot(YEAR, dir, data = Artesia, geom = c("point", "line"), xlab = "Year", 
  ylab = "DIR", main = "Artesia DIR Over Record Period") + 
  geom_smooth(method=lm)

我知道 Par() 应该有助于做到这一点，但我一生都无法弄清楚.非常感谢任何帮助.

I understand that Par() is supposed to help do this but I can not figure it out for the life of me. Any help is greatly appreciated.

谢谢，

-齐亚

编辑-

正如 Arun 指出的那样，我正在尝试保存一个 .pdf，其中包含我的 goodlocs df 的 250 个不同图表，按Loc"分割，并带有用于数据审查的点和线几何......

as Arun pointed out, I am trying to save a .pdf of 250 different graphs of my goodlocs df split by "Loc", with point and line geometry for data review....

我还尝试通过 qplot 将我的 df 的 ddply 作为数据传递，但它也不起作用，我并没有真正期待它，但我不得不尝试.

I also tried passing a ddply of my df through qplot as the data but it did not work either, I was not really expecting it to but i had to try.

推荐答案

这个怎么样?

require(ggplot2)
require(plyr)
require(gridExtra)
pl <- dlply(df, .(Loc), function(dat) {
    ggplot(data = dat, aes(x = Year, y = dir)) + geom_line() + 
    geom_point() + xlab("x-label") + ylab("y-label") + 
    geom_smooth(method = "lm")
})

ml <- do.call(marrangeGrob, c(pl, list(nrow = 2, ncol = 2)))
ggsave("my_plots.pdf", ml, height = 7, width = 13, units = "in")

<小时>

思路:首先按Loc分割数据，并为每个子集创建图.拆分部分是使用 plyr 函数 dlply 完成的，该函数基本上以 data.frame 作为输入并提供 list作为输出.绘图元素存储在与子集对应的列表的每个元素中.然后，我们使用 gridExtra 包的 marrangeGrob 函数来排列多个绘图(其中还有非常有用的 nrow 和 ncol参数来设置参数).然后，您可以使用 ggplot2 中的 ggsave 保存它.

---

The idea: First split the data by Loc and create the plot for each subset. The splitting part is done using plyr function dlply that basically takes a data.frame as input and provides a list as output. The plot element is stored in each element of the list corresponding to the subset. Then, we use gridExtra package's marrangeGrob function to arrange multiple plots (which also has the very useful nrow and ncol arguments to set the argument). Then, you can save it using ggsave from ggplot2.

我会留给您可能需要的任何其他调整.

I'll leave you to any additional tweaks you may require.

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