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在一个 PDF 中按组绘制多个线图

[英]Several line plots by group in one PDF

 原文  2022-06-18 10:04:20  5   1    r/ pdf/ plot/ line/ group

问题描述

我想通过测量单位绘制多年来不同资源的价格，每种资源一个图，一个 PDF 中的所有图。

我的完整数据集中三个资源的数据如下所示：

structure(list(year = structure(c(1994, 1996, 1996, 1997, 1997, 
1998, 1998, 1998, 1998, 1999, 1999, 2000, 2001, 2001, 2002, 2002, 
2002, 2003, 2003, 2003, 2004, 2004, 2004, 2004, 2005, 2005, 2005, 
2005, 2005, 2006, 2006, 2006, 2006, 2006, 2007, 2007, 2007, 2007, 
2007, 2007, 2008, 2008, 2008, 2008, 2008, 2009, 2009, 2009, 2009, 
2009, 2010, 2010, 2010, 2010, 2010, 2011, 2011, 2011, 2011, 2011, 
2012, 2012, 2012, 2012, 2012, 2013, 2013, 2013, 2013, 2014, 2014, 
2014, 2014, 2014, 2014, 2015, 2015, 2015, 2015, 2015, 2015), label = "year", format.stata = "%10.0g"), 
    standardmeasure = structure(c("kilograms", "million 42-gallon barrels", 
    "million cubic meters", "million 42-gallon barrels", "million cubic meters", 
    "kilograms", "metric tons", "million 42-gallon barrels", 
    "million cubic meters", "kilograms", "million cubic meters", 
    "kilograms", "kilograms", "million cubic meters", "kilograms", 
    "metric tons", "million cubic meters", "carats", "kilograms", 
    "million cubic meters", "carats", "kilograms", "metric tons", 
    "million cubic meters", "carats", "kilograms", "metric tons", 
    "million cubic meters", "thousand metric tons", "kilograms", 
    "metric tons", "metric tons", "million cubic meters", "thousand metric tons", 
    "carats", "kilograms", "metric tons", "metric tons", "million cubic meters", 
    "thousand metric tons", "kilograms", "metric tons", "metric tons", 
    "million cubic meters", "thousand metric tons", "kilograms", 
    "metric tons", "metric tons", "million cubic meters", "thousand metric tons", 
    "kilograms", "metric tons", "metric tons", "million cubic meters", 
    "thousand metric tons", "kilograms", "metric tons", "metric tons", 
    "million cubic meters", "thousand metric tons", "kilograms", 
    "metric tons", "metric tons", "million cubic meters", "thousand metric tons", 
    "kilograms", "metric tons", "metric tons", "million cubic meters", 
    "cubic meters", "kilograms", "metric tons", "metric tons", 
    "metric tons", "million cubic meters", "cubic meters", "kilograms", 
    "metric tons", "metric tons", "metric tons", "million cubic meters"
    ), label = "original unit of measurement from USGS", format.stata = "%-9s"), 
    wb_price_mult = structure(c(16937.037109375, NA, NA, NA, 
    NA, 12139.4326171875, NA, NA, NA, 11330.81640625, NA, 11089.18359375, 
    10529.6015625, NA, 11862.212890625, 11862213, NA, 2.72781133651733, 
    13639.052734375, NA, 2.9885892868042, 14942.9423828125, 14942942, 
    NA, 3.147536277771, 15737.6767578125, 15737677, NA, 15737677824, 
    20742.962890625, 20742964, NA, NA, 20742965248, 4.65880012512207, 
    23293.994140625, 23293994, NA, NA, 23293997056, 28583.76953125, 
    28583770, NA, NA, 28583772160, 31663.6328125, 31663634, NA, 
    NA, 31663636480, 39373.86328125, 39373864, NA, NA, 39373864960, 
    49430.73046875, 49430732, NA, NA, 49430736896, 51639.21484375, 
    51639216, NA, NA, NA, 42957.16015625, 42957160, NA, NA, NA, 
    37894.74609375, 37894748, NA, NA, NA, NA, 34408.5234375, 
    34408524, NA, NA, NA), label = "WB price in multiplier in original USGS output unit", format.stata = "%10.0g"), 
    resource = structure(c("gold", "natural gas", "natural gas", 
    "natural gas", "natural gas", "gold", "lithium", "natural gas", 
    "natural gas", "gold", "natural gas", "gold", "gold", "natural gas", 
    "gold", "gold", "natural gas", "gold", "gold", "natural gas", 
    "gold", "gold", "gold", "natural gas", "gold", "gold", "gold", 
    "natural gas", "gold", "gold", "gold", "lithium", "natural gas", 
    "gold", "gold", "gold", "gold", "lithium", "natural gas", 
    "gold", "gold", "gold", "lithium", "natural gas", "gold", 
    "gold", "gold", "lithium", "natural gas", "gold", "gold", 
    "gold", "lithium", "natural gas", "gold", "gold", "gold", 
    "lithium", "natural gas", "gold", "gold", "gold", "lithium", 
    "natural gas", "natural gas", "gold", "gold", "lithium", 
    "natural gas", "natural gas", "gold", "gold", "lithium", 
    "natural gas", "natural gas", "natural gas", "gold", "gold", 
    "lithium", "natural gas", "natural gas"), label = "resource", format.stata = "%-9s")), class = c("grouped_df", 
"tbl_df", "tbl", "data.frame"), row.names = c(NA, -81L), groups = structure(list(
    year = structure(c(1994, 1996, 1996, 1997, 1997, 1998, 1998, 
    1998, 1998, 1999, 1999, 2000, 2001, 2001, 2002, 2002, 2002, 
    2003, 2003, 2003, 2004, 2004, 2004, 2004, 2005, 2005, 2005, 
    2005, 2005, 2006, 2006, 2006, 2006, 2006, 2007, 2007, 2007, 
    2007, 2007, 2007, 2008, 2008, 2008, 2008, 2008, 2009, 2009, 
    2009, 2009, 2009, 2010, 2010, 2010, 2010, 2010, 2011, 2011, 
    2011, 2011, 2011, 2012, 2012, 2012, 2012, 2012, 2013, 2013, 
    2013, 2013, 2014, 2014, 2014, 2014, 2014, 2015, 2015, 2015, 
    2015, 2015), label = "year", format.stata = "%10.0g"), standardmeasure = structure(c("kilograms", 
    "million 42-gallon barrels", "million cubic meters", "million 42-gallon barrels", 
    "million cubic meters", "kilograms", "metric tons", "million 42-gallon barrels", 
    "million cubic meters", "kilograms", "million cubic meters", 
    "kilograms", "kilograms", "million cubic meters", "kilograms", 
    "metric tons", "million cubic meters", "carats", "kilograms", 
    "million cubic meters", "carats", "kilograms", "metric tons", 
    "million cubic meters", "carats", "kilograms", "metric tons", 
    "million cubic meters", "thousand metric tons", "kilograms", 
    "metric tons", "metric tons", "million cubic meters", "thousand metric tons", 
    "carats", "kilograms", "metric tons", "metric tons", "million cubic meters", 
    "thousand metric tons", "kilograms", "metric tons", "metric tons", 
    "million cubic meters", "thousand metric tons", "kilograms", 
    "metric tons", "metric tons", "million cubic meters", "thousand metric tons", 
    "kilograms", "metric tons", "metric tons", "million cubic meters", 
    "thousand metric tons", "kilograms", "metric tons", "metric tons", 
    "million cubic meters", "thousand metric tons", "kilograms", 
    "metric tons", "metric tons", "million cubic meters", "thousand metric tons", 
    "kilograms", "metric tons", "metric tons", "million cubic meters", 
    "cubic meters", "kilograms", "metric tons", "metric tons", 
    "million cubic meters", "cubic meters", "kilograms", "metric tons", 
    "metric tons", "million cubic meters"), label = "original unit of measurement from USGS", format.stata = "%-9s"), 
    wb_price_mult = structure(c(16937.037109375, NA, NA, NA, 
    NA, 12139.4326171875, NA, NA, NA, 11330.81640625, NA, 11089.18359375, 
    10529.6015625, NA, 11862.212890625, 11862213, NA, 2.72781133651733, 
    13639.052734375, NA, 2.9885892868042, 14942.9423828125, 14942942, 
    NA, 3.147536277771, 15737.6767578125, 15737677, NA, 15737677824, 
    20742.962890625, 20742964, NA, NA, 20742965248, 4.65880012512207, 
    23293.994140625, 23293994, NA, NA, 23293997056, 28583.76953125, 
    28583770, NA, NA, 28583772160, 31663.6328125, 31663634, NA, 
    NA, 31663636480, 39373.86328125, 39373864, NA, NA, 39373864960, 
    49430.73046875, 49430732, NA, NA, 49430736896, 51639.21484375, 
    51639216, NA, NA, NA, 42957.16015625, 42957160, NA, NA, NA, 
    37894.74609375, 37894748, NA, NA, NA, 34408.5234375, 34408524, 
    NA, NA), label = "WB price in multiplier in original USGS output unit", format.stata = "%10.0g"), 
    .rows = structure(list(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 
        10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 
        21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 
        32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 
        43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 
        54L, 55L, 56L, 57L, 58L, 59L, 60L, 61L, 62L, 63L, 64L, 
        65L, 66L, 67L, 68L, 69L, 70L, 71L, 72L, 73:74, 75L, 76L, 
        77L, 78L, 79:80, 81L), ptype = integer(0), class = c("vctrs_list_of", 
    "vctrs_vctr", "list"))), class = c("tbl_df", "tbl", "data.frame"
), row.names = c(NA, -79L), .drop = TRUE))

（我编辑了示例数据以包含所有数据的 3 个资源，而不是前 50 行，这使得数据非常不完整）

每幅图应显示一种资源多年来每次测量 ( standardmeasure ) 的对数价格 ( wb_price_mult )。 最后，我想拥有所有图表的PDF。

每个图表应类似于： 资源黄金的完整数据集的示例图

我用的

ggplot(example_data %>% filter(resource == "gold"), aes(x = year, y = log(wb_price_mult), color = standardmeasure)) + geom_line() + labs(title="gold")

（使用完整的数据集）

1 个解决方案

解决方案1
 2 已采纳  2022-06-18 11:14:28

这是一种方法。

定义两个函数，以使代码更具可读性，以防万一，更易于调试。

  • 绘制每个资源的函数；
  • 将绘图保存到 PDF 文件的功能。
suppressPackageStartupMessages({
  library(tidyverse)
})

plot_resource <- function(X) {
  title <- X$resource[1]
  ggplot(X, aes(year, log(wb_price_mult), colour = standardmeasure)) +
    geom_line() +
    ggtitle(label = title)
}

plot_save <- function(x, filename) {
  pdf(filename, onefile = TRUE)
  lapply(x, print)
  dev.off()
}

prices %>%
  ungroup() %>%
  group_split(resource) %>%
  map(plot_resource) %>%
  plot_save("resources.pdf")
#> Warning: Removed 11 row(s) containing missing values (geom_path).
#> Warning: Removed 27 row(s) containing missing values (geom_path).
#> png 
#>   2

由reprex 包于 2022-06-18 创建 (v2.0.1)

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