在一個PDF中按組繪制多個線圖-有解無憂

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。

我的完整資料集中三個資源的資料如下所示：

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 = ".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 = ".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 = ".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 = ".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))

（我編輯了示例資料以包含所有資料的 3 個資源，而不是前 50 行，這使得資料非常不完整）

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

每個圖表應類似于：在一個 PDF 中按組繪制多個線圖

我用的

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

（使用完整的資料集）

uj5u.com熱心網友回復：

這是一種方法。

定義兩個函式，以使代碼更具可讀性，以防萬一，更易于除錯。

繪制每個資源的函式；
將繪圖保存到 PDF 檔案的功能。

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 創建(v2.0.1)}

轉載請註明出處，本文鏈接：https://www.uj5u.com/gongcheng/493624.html

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