在多列上使用for循環在R ggplot圖形中創建標題

Question

我對ggplot使用循環和函數非常陌生。 我做了一個函數來遍歷數據框中的一列“ HUC14”。 對於HUC14的每個唯一值，它將創建一個子集數據幀以用於ggplot，並且還將該唯一值用作標題。 但是，我想知道是否還可以在數據框中的另一列中循環以添加到繪圖標題以及HUC14號嗎？ 我使用的代碼不會更改繪圖或HUC14，它只會通過名稱循環。不知道我在做什么錯！ 我希望HUC14和名稱與要繪制的兩個參數的給定值匹配！

樣本數據：

structure(list(stdate = structure(c(11359, 16498, 12149, 12437, 
13277, 17536, 16517, 16503, 16134, 16105, 15783, 16470, 14266, 
13566, 14984), class = "Date"), orgid = c("USGS-NJ", "USGS-NJ", 
"USGS-NJ", "21NJDEP1", "21NJDEP1", "USGS-NJ", "NJDEP_BFBM", "NJDEP_BFBM", 
"NJDEP_BFBM", "USGS-NJ", "NJDEP_BFBM", "USGS-NJ", "21NJDEP1", 
"GSWA", "NJDEP_BFBM"), locid = c("USGS-01396030", "USGS-01378560", 
"USGS-01393400", "21NJDEP1-01396030", "21NJDEP1-AN0770", "USGS-01378560", 
"NJDEP_BFBM-01394180", "NJDEP_BFBM-AN0425A", "NJDEP_BFBM-01394180", 
"USGS-01378560", "NJDEP_BFBM-01394180", "USGS-01394500", "21NJDEP1-01379525", 
"GSWA-LB4S", "NJDEP_BFBM-01379525"), sttime = structure(c(34200, 
50400, 80280, 35700, 0, NA, 41400, 45300, 39600, 46800, 40500, 
42300, 34800, 42900, 37380), class = c("hms", "difftime"), units = "secs"), 
    valunit = c("uS/cm @25C", "uS/cm @25C", "uS/cm @25C", "uS/cm @25C", 
    "uS/cm @25C", "uS/cm @25C", "uS/cm @25C", "uS/cm @25C", "uS/cm @25C", 
    "uS/cm @25C", "uS/cm @25C", "uS/cm @25C", "uS/cm @25C", "uS/cm @25C", 
    "uS/cm @25C"), swqs = c("FW2-NT", "FW2-NT", "FW2-NT", "FW2-NT", 
    "FW2-NT", "FW2-NT", "FW2-NT", "FW2-NT", "FW2-NT", "FW2-NT", 
    "FW2-NT", "FW2-NT", "FW2-NT", "FW2-NT", "FW2-NT"), WMA = c(7L, 
    5L, 7L, 7L, 16L, NA, 7L, 9L, 7L, 5L, 7L, 7L, 6L, 6L, 6L), 
    year = c(2001L, 2015L, 2003L, 2004L, 2006L, NA, 2015L, 2015L, 
    2014L, 2014L, 2013L, 2015L, 2009L, 2007L, 2011L), locid2 = c("01396030", 
    "01378560", "01393400", "01396030", "AN0770", "01378560", 
    "01394180", "AN0425A", "01394180", "01378560", "01394180", 
    "01394500", "01379525", "LB4S", "01379525"), HUC14 = c("HUC02030104050090", 
    "HUC02030103180010", "HUC02030104020020", "HUC02030104050090", 
    "HUC02040206230040", "HUC02030103180010", "HUC02030104050040", 
    "HUC02030105120120", "HUC02030104050040", "HUC02030103180010", 
    "HUC02030104050040", "HUC02030104050040", "HUC02030103010190", 
    "HUC02030103010040", "HUC02030103010140"), MonLocName = c("Rahway R S Br in Merrill Park off Fairview Rd in Woodbridge", 
    "Coles Bk at Hackensack", "Elizabeth R at Hillside", "Rahway R S Br in Merrill Park off Fairview Rd in Woodbridge", 
    "Green Ck on Rt 47 in Middle Twp", "Coles Bk at Hackensack", 
    "Rahway R trib at Springfield", "Ambrose Bk at Behmer Rd in Piscataway", 
    "Rahway R trib at Springfield", "Coles Bk at Hackensack", 
    "Rahway R trib at Springfield", "Rahway R near Springfield", 
    "Canoe Bk on Parsonage Hill Rd in Millburn Twp", "Loantaka Bk at Woodland Ave (upstream)", 
    "Canoe Bk on Parsonage Hill Rd in Millburn Twp"), Chloride = structure(c(903, 
    2100, NA, 1409.3, 151, NA, 1340, 52.062, 1170, 1020, 1240, 
    1030, 1220, 209, 1040), na.action = structure(c(1L, 2L, 3L, 
    4L, 7L, 8L, 9L, 10L), class = "omit")), Specific_conductance = structure(c(7450, 
    7190, 6080, 5550, 4680, 4490, 4250, 4090, 3890, 3710, 3710, 
    3580, 3570, 3570, 3380), na.action = structure(5:10, class = "omit")), 
    tds = structure(c(1620, 3630, NA, 3056, 606, NA, 2530, 141, 
    2590, 1840, 2050, 1970, 57, 604, 1870), na.action = structure(1:6, class = "omit"))), .Names = c("stdate", 
"orgid", "locid", "sttime", "valunit", "swqs", "WMA", "year", 
"locid2", "HUC14", "MonLocName", "Chloride", "Specific_conductance", 
"tds"), class = c("data.table", "data.frame"), row.names = c(NA, 
-15L), .internal.selfref = <pointer: 0x00000000028f0788>)

我正在使用的代碼：

corr_plots<-function(df,x,y){

  # create list of HUCs in data to loop over 
  HUC_list <- unique(df2$HUC14)
  name_list<-unique(df2$MonLocName)

  for (i in seq_along(HUC_list)) { 
    for(j in seq_along(name_list)){
        x_var <- enquo(x)
        y_var <- enquo(y)

      plot<-ggplot(subset(df2, df2$HUC14==HUC_list[i]),
             aes(x = !!x_var, y = !!y_var))+
      geom_point(size=2,alpha=0.5)+
      geom_smooth(method = "lm", se = FALSE)+ 

      scale_x_continuous(limits = c(0,6200), expand = c(0, 0)) +
      scale_y_continuous(limits = c(0,2000), expand = c(0, 0)) +
        ggtitle(paste(HUC_list[i],as.character(name_list[j])))


      print(plot)

    }
  }
}

沒有循環的工作示例：

corr_plots<-function(df,HUC,x,y){

        x_var <- enquo(x)
        y_var <- enquo(y)

      ggplot(subset(df, HUC14 == HUC),
             aes(x = !!x_var, y = !!y_var))+
      geom_point(size=2,alpha=0.5)+
      geom_smooth(method = "lm", se = FALSE)+ 

      scale_x_continuous(limits = c(0,6200), expand = c(0, 0)) +
      scale_y_continuous(limits = c(0,2000), expand = c(0, 0)) 

  }
corr_plots(df2,"HUC02030104020020",Specific_conductance,Chloride)

Answer 1

您可以通過多種方式進行操作，我發現tidyverse / purrr方法在靈活性和簡潔性之間取得了很好的平衡：

library(tidyverse)

corr_plot <- function(df, x, y, title) {
  x_var <- enquo(x)
  y_var <- enquo(y)

  ggplot(df, aes(x = !!x_var, y = !!y_var)) +
    geom_point(size = 2) +
    geom_smooth(method = "lm", se = FALSE) +
    scale_x_continuous(limits = c(0, 6200), expand = c(0, 0)) +
    scale_y_continuous(limits = c(0, 2000), expand = c(0, 0)) +
    labs(
      title = title,
      subtitle = paste(rlang::quo_text(x_var), "vs.", rlang::quo_text(y_var))
    )
}

nested_by_HUC14 <- 
  df %>%
  group_by(HUC14) %>% 
  nest()

nested_by_HUC14 %>%
  mutate(plot = map2(data, HUC14, ~ corr_plot(.x, Specific_conductance, Chloride, .y))) %>%
  walk(print(.$plot))

如果您不希望將[[1]]...[[2]]...etc打印到控制台，則可以將walk語句更改為pull(plot) %>% walk(print)