Function 从R中的数据帧创建多个绘图

我对R比较陌生，有一个.csv格式的数据集，如下所示：

WCF Well    Constit  Date   Value   Unit    Filtered    Flag    Median  Min Max
299-E24-20_Chloroform_N 299-E24-20  Chloroform  12/6/2016   0.15    ug/L    N   J   0.145   0.14    0.19
299-E24-20_Chloroform_N 299-E24-20  Chloroform  3/14/2017   0.14    ug/L    N   J   0.145   0.14    0.19
299-E24-20_Chloroform_N 299-E24-20  Chloroform  6/15/2017   0.14    ug/L    N   J   0.145   0.14    0.19
299-E24-20_Chloroform_N 299-E24-20  Chloroform  9/20/2017   0.19    ug/L    N   J   0.145   0.14    0.19
299-E24-20_Sulfide_N    299-E24-20  Sulfide 12/6/2016   5800    ug/L    N   B   2200    2200    5800
299-E24-22_Sulfide_N    299-E24-22  Sulfide 12/6/2016   1470    ug/L    N   B   33  33  1470
299-E25-2_Sulfide_N 299-E25-2   Sulfide 11/1/2016   3380    ug/L    N   NA  33  33  3380
299-E25-2_Sulfide_N 299-E25-2   Sulfide 12/6/2016   1570    ug/L    N   B   33  33  3380
299-E24-20_Sulfide_N    299-E24-20  Sulfide 3/14/2017   2200    ug/L    N   UO  2200    2200    5800
299-E24-20_Sulfide_N    299-E24-20  Sulfide 6/15/2017   2200    ug/L    N   U   2200    2200    5800
299-E24-20_Sulfide_N    299-E24-20  Sulfide 9/20/2017   2200    ug/L    N   U   2200    2200    5800
299-E24-22_Sulfide_N    299-E24-22  Sulfide 3/13/2017   33  ug/L    N   U   33  33  1470
299-E24-22_Sulfide_N    299-E24-22  Sulfide 6/15/2017   33  ug/L    N   U   33  33  1470
299-E24-22_Sulfide_N    299-E24-22  Sulfide 9/18/2017   33  ug/L    N   U   33  33  1470
299-E25-2_Sulfide_N 299-E25-2   Sulfide 1/25/2017   1.00E+03    ug/L    N   U   33  33  3380
299-E25-2_Sulfide_N 299-E25-2   Sulfide 3/14/2017   33  ug/L    N   U   33  33  3380
299-E25-2_Sulfide_N 299-E25-2   Sulfide 4/19/2017   33  ug/L    N   U   33  33  3380
299-E25-2_Sulfide_N 299-E25-2   Sulfide 6/16/2017   33  ug/L    N   U   33  33  3380
299-E25-2_Sulfide_N 299-E25-2   Sulfide 9/15/2017   33  ug/L    N   U   33  33  3380

我编写了一些代码，试图从数据集中创建多个绘图，并将它们作为.png保存到指定的文件夹中。无论何时运行代码，都不会出现任何错误，但不会生成任何绘图，因为没有任何绘图保存到文件夹位置。代码如下所示。有人能帮我找出为什么我没有得到任何阴谋吗

#call required libraries

library(dplyr)
library(tidyr)
library(readr)
library(ggplot2)
library(magrittr)
library(stringi)
library(lubridate)
library(stats)

#load in datafiles

df <- read_csv ("C:/mypath/_dat.csv", col_names = TRUE)
df %>%
mutate(Date = mdy(Date))

# create graphing function

wcf.plot <- function(df){
  wcf_list <- unique(df$WCF)
  for( i in (wcf_list)){
    plots <- 
      ggplot(data=subset(df, df$WCF==wcf_list[i]), aes(Date, Value, group = WCF)) +
      geom_point(aes(color = Flag)) +
      ggtitle(paste(wcf_list[i])) +
      geom_abline(lm(data = df, Value~Date)) +
      xlab("Sample Date") +
      ylab("Conc ug/L or pCi/L")
      ggsave(plots, file=paste(plots,'C:/Projects/multiplotter/multiplotter/plots_png/', wcf_list[i], ".png",  sep='', scale=2))
      print(plots)
  }
}

#调用所需的库
图书馆（dplyr）
图书馆（tidyr）
图书馆（readr）
图书馆（GG2）
图书馆（magrittr）
图书馆（stringi）
图书馆（lubridate）
图书馆（统计）
#加载数据文件
df%
突变（日期=mdy（日期））
#创建图形功能
wcf.plot类似的内容（答案底部的数据）

另见。另外，使用
facet\u grid（）
绘制奖励图，因为它可以很好地了解一个图中的数据

ggplot(tbl, aes(Date, Value)) +
      geom_point(aes(color = Flag)) +
      geom_smooth(method = "lm", se = FALSE) + 
      labs(x = "Sample Date", y = "Conc ug/L or pCi/L") + facet_grid(. ~ WCF)


df%arrange（WCF）%%>%group_by（WCF）%%>%as_tible（）
谢谢！刻面将有助于更好的情节展示。
ggplot(tbl, aes(Date, Value)) +
      geom_point(aes(color = Flag)) +
      geom_smooth(method = "lm", se = FALSE) + 
      labs(x = "Sample Date", y = "Conc ug/L or pCi/L") + facet_grid(. ~ WCF)

df <- structure(list(WCF = structure(c(1L, 1L, 1L, 1L, 2L, 3L, 4L, 
4L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L), .Label = c("299-E24-20_Chloroform_N", 
"299-E24-20_Sulfide_N", "299-E24-22_Sulfide_N", "299-E25-2_Sulfide_N"
), class = "factor"), Well = structure(c(1L, 1L, 1L, 1L, 1L, 
2L, 3L, 3L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L), .Label = c("299-E24-20", 
"299-E24-22", "299-E25-2"), class = "factor"), Constit = structure(c(1L, 
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L), .Label = c("Chloroform", "Sulfide"), class = "factor"), 
    Date = structure(c(3L, 5L, 7L, 11L, 3L, 3L, 2L, 3L, 5L, 7L, 
    11L, 4L, 7L, 10L, 1L, 5L, 6L, 8L, 9L), .Label = c("1/25/2017", 
    "11/1/2016", "12/6/2016", "3/13/2017", "3/14/2017", "4/19/2017", 
    "6/15/2017", "6/16/2017", "9/15/2017", "9/18/2017", "9/20/2017"
    ), class = "factor"), Value = c(0.15, 0.14, 0.14, 0.19, 5800, 
    1470, 3380, 1570, 2200, 2200, 2200, 33, 33, 33, 1000, 33, 
    33, 33, 33), Unit = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = "ug/L", class = "factor"), 
    Filtered = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = "N", class = "factor"), 
    Flag = structure(c(2L, 2L, 2L, 2L, 1L, 1L, NA, 1L, 4L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("B", "J", 
    "U", "UO"), class = "factor"), Median = c(0.145, 0.145, 0.145, 
    0.145, 2200, 33, 33, 33, 2200, 2200, 2200, 33, 33, 33, 33, 
    33, 33, 33, 33), Min = c(0.14, 0.14, 0.14, 0.14, 2200, 33, 
    33, 33, 2200, 2200, 2200, 33, 33, 33, 33, 33, 33, 33, 33), 
    Max = c(0.19, 0.19, 0.19, 0.19, 5800, 1470, 3380, 3380, 5800, 
    5800, 5800, 1470, 1470, 1470, 3380, 3380, 3380, 3380, 3380
    )), .Names = c("WCF", "Well", "Constit", "Date", "Value", 
"Unit", "Filtered", "Flag", "Median", "Min", "Max"),
 class = "data.frame", row.names = c(NA, -19L))

tbl <- df %>% mutate(Date = mdy(Date)) %>% arrange(WCF) %>% group_by(WCF) %>% as_tibble()