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在一個 PDF 中按組繪制多個線圖

[英]Several line plots by group in one PDF

 原文  2022-06-18 10:04:20  9   1    r/ pdf/ plot/ line/ group

問題描述

我想通過測量單位繪制多年來不同資源的價格，每種資源一個圖，一個 PDF 中的所有圖。

我的完整數據集中三個資源的數據如下所示：

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))

（我編輯了示例數據以包含所有數據的 3 個資源，而不是前 50 行，這使得數據非常不完整）

每幅圖應顯示一種資源多年來每次測量 ( standardmeasure ) 的對數價格 ( wb_price_mult )。 最后，我想擁有所有圖表的PDF。

每個圖表應類似於： 資源黃金的完整數據集的示例圖

我用的

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

（使用完整的數據集）

1 個解決方案

解決方案1
 2 已采納  2022-06-18 11:14:28

這是一種方法。

定義兩個函數，以使代碼更具可讀性，以防萬一，更易於調試。

  • 繪制每個資源的函數；
  • 將繪圖保存到 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 包於 2022-06-18 創建 (v2.0.1)

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