R：循环在 R 中创建新数据帧

Question

我正在尝试创建一个循环，为 VCS 站创建许多文件，这些文件根据其站名命名。 下面是为一个站执行此操作的代码，我试图将其变成一个循环，以便可以为 68 个站执行此操作。 （即，如果我正在复制和粘贴，我将用不同的电台名称替换 P205187，例如 P205200）。 我在名为 VCS.Sites 的 dataframe 中有各个站名（例如 P205187）。 谁能指出我正确的方向？ 新的 R 用户在这里，我被卡住了！

P205187 <- VCSrawdata[VCSrawdata$Network_ID=="P205187",]  #create a file for VCS station P205187
  #clean up after subset
  P205187$Network_ID <- factor(P205187$Network_ID)


# create annual file for VCS station P205187
P205187_annual <- group_by(P205187,Year,DESCRIPTION)
P205187_annual <- summarise(P205187_annual,Sum_Annual = sum(Value), Mean_Annual = mean(Value), CountDays=n())

# create monthly file for VCS station P205187
P205187_monthly <- group_by(P205187,Year, Month,DESCRIPTION)
P205187_monthly <- summarise(P205187_monthly,Sum_Monthly = sum(Value),Mean_monthly = mean(Value),CountDays=n())

Answer 1

你可以用一个 lapply 循环做得很好。 像这样的东西：

list_of_ids <- c("List be here")

monthly <- function(id){
  P205187 <- VCSrawdata[VCSrawdata$Network_ID==id,]  #create a file for VCS station P205187
  #clean up after subset
  P205187$Network_ID <- factor(P205187$Network_ID)
  
  
  # create annual file for VCS station P205187
  P205187_annual <- group_by(P205187,Year,DESCRIPTION)
  P205187_annual <- summarise(P205187_annual,Sum_Annual = sum(Value), Mean_Annual = mean(Value), CountDays=n())
  
  # create monthly file for VCS station P205187
  P205187_monthly <- group_by(P205187,Year, Month,DESCRIPTION)
  P205187_monthly <- summarise(P205187_monthly,Sum_Monthly = sum(Value),Mean_monthly = mean(Value),CountDays=n())
  
  return(P205187_monthly)
}

monthlies <- lapply(list_of_ids, monthly)

Answer 2

听起来这是为了写 csvs。 我们可以使用group_map中的group_map循环遍历所有站点并写入 csv。

library(dplyr)

VCSrawdata %>%
    group_by(Network_ID) %>%
    group_walk(~ {
        .x%>%
            group_by(Year, DESCRIPTION) %>%
            summarize(sum_annual = sum(Value),
                      mean_annual = mean(Value),
                      countDays = n())%>%
            write.csv(file = paste0(.y$Network_ID, "_annual_csv"))
        
        .x%>%
            group_by(Year, Month, DESCRIPTION) %>%
            summarize(sum_month = sum(Value),
                      mean_month = mean(Value),
                      countDays = n())%>%
            write.csv(file = paste0(.y$Network_ID, "_month_csv")) 
    }
    )

注意事项：

1. .x指的是由Network_ID拆分的分组 tibble
2. .y指的是分组。 在这种情况下，我们只有Network_ID 。

Answer 3

只需在定义的方法中概括您的过程，然后在循环中将站点名称作为参数传递或应用function 来迭代站点。 使用这种方法，您可以避免许多单独的对象淹没全局环境，而是使用许多底层元素的单个命名列表来更好地序列化和组织。

summarize_stations <- function(station_name) { 

   tmp_df <- VCSrawdata[VCSrawdata$Network_ID==station_name,] 
   tmp_df$Network_ID <- factor(tmp_df$Network_ID) 

   # create annual file for VCS station
   tmp_annual <- summarise(group_by(tmp,Year,DESCRIPTION),
                           Sum_Annual = sum(Value), 
                           Mean_Annual = mean(Value), 
                           CountDays=n()) 

   # create monthly file for VCS station
   tmp_monthly <- summarise(group_by(tmp, Year, Month,DESCRIPTION),
                            Sum_Annual = sum(Value), 
                            Mean_Annual = mean(Value), 
                            CountDays=n())

   # RETURN NAMED LIST OF BOTH AGGREGATIONS
   return(list(annual=tmp_annual, monthly=tmp_monthly))
}

station_list <- sapply(VCS.Sites$station_names, summarize_stations, simplify=FALSE)


# ACCESS UNDERLYING ELEMENTS
station_list$P205187$annual
station_list$P205187$monthly
...

---

您甚至可以使用by （面向对象的包装器tapply ）按Network_ID对VCSrawdata进行子集（假设它包括您需要的所有站点）。 为此，稍微调整 function 以接收数据帧作为允许您跳过子集行的参数。

summarize_stations <- function(tmp_df) { 

  # REMOVE SUBSET LINE
  # tmp_df <- VCSrawdata[VCSrawdata$Network_ID=="P205187",] 
  
  ...keep same code as above    
}

station_list <- by(VCSrawdata, VCSrawdata$Network_ID, FUN=summarize_stations)


# ACCESS UNDERLYING ELEMENTS
station_list$P205187$annual
station_list$P205187$monthly
...