在多列上使用 for 循环在 r ggplot 图中创建标题

Question

我对在 ggplot 中使用循环和函数非常陌生。我创建了一个函数来遍历我的数据框中名为“HUC14”的列。对于 HUC14 的每个唯一值，它会创建一个要在 ggplot 中使用的子集数据框，并且它还使用该唯一值作为标题。但是，我想知道是否还可以遍历数据框中的另一列以添加到绘图标题以及 HUC14 编号？我使用的代码不会改变情节或 HUC14 它只循环名称..不确定我做错了什么！我希望 HUC14 和 Name 与我要绘制的两个参数的给定值匹配！

样本数据：

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>)

我正在使用的代码：

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)

    }
  }
}

没有循环的工作示例：

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

您可以通过多种方式做到这一点，我发现tidyverse / purrr 方法在灵活性和简洁性之间取得了很好的平衡：

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))

如果您不想将[[1]]...[[2]]...etc 打印到控制台，可以将walk 语句更改为pull(plot) %>% walk(print)