将熔化函数应用于多个.txt文件

Question

我有多个.txt文件，每个文件都以以下格式表示某些参数

Parameter1 = structure(list(Year = 1969:1974, Jan = c(16.6, 15.6, 15.8, 16.9, 
    16.2, 15.4), Feb = c(17, 15.2, 16.6, 14.8, 12.9, 17.9), Mar = c(14.2, 
    13.3, 16.9, 14.9, 15.5, 13.4), Apr = c(11.6, 10.7, 10.7, 11.6, 
    10.3, 9.7), May = c(9.9, 9.2, 9.7, 9.6, 8.2, 8.8), Jun = c(7.6, 
    7.2, 7.1, 7.2, 6, 6.9), Jul = c(7, 6.7, 6.7, 6.9, 6.9, 5.2), 
        Aug = c(7, 7.2, 7.2, 6.1, 6.8, 6.5), Sep = c(8.4, 7.6, 8.5, 
        7.3, 6.6, 6.8), Oct = c(10.4, 8.5, 8.5, 9.1, 8.3, 7.7), Nov = c(14, 
        12.2, 12.9, 12.2, 10.8, 10.2), Dec = c(15.5, 16.7, 15.9, 
        15.5, 13.2, 15.4), Annual = c(11.6, 10.8, 11.4, 11, 10.1, 
        10.3), winter = c(16.8, 15.4, 16.2, 15.8, 14.5, 16.6), premonsoon = c(11.9, 
        11.1, 12.4, 12, 11.3, 10.6), monsoon = c(7.5, 7.2, 7.3, 6.8, 
        6.6, 6.3), postmonsoon = c(13.3, 12.5, 12.5, 12.2, 10.7, 
        11.1)), row.names = c(NA, 6L), class = "data.frame")

我想melt这些.txt文件，并将其放入单个文件，例如以下格式

我可以对单个文件执行整形操作，例如

A <- read.delim("Parameter1.txt", sep="\t")

Transpose <- t(A)
colnames(Transpose) = Transpose[1, ] # the first row will be the header
Transpose = Transpose[-1, ]          # removing the first row.
arranged_data <- melt(Transpose) 
melt(A)
head(arranged_data)
Arranged_data <- data.frame(cbind(arranged_data$X2,as.character(arranged_data$X1),arranged_data$value))
colnames(Arranged_data) <- c("Year","Month","Parameter1")
head(Arranged_data)
#Removing the seasonal and annual data
Final <- subset(Arranged_data, !Month %in% c("postmonsoon","monsoon","premonsoon","winter","Annual"))
numMonth<-function(x)c(JAN=1,FEB=2,MAR=3,APR=4,MAY=5,JUN=6,JUL=7,AUG=8,SEP=9,OCT=10,NOV=11,DEC=12)
Final$Month <- numMonth(Final$Month)
write.csv(Final,"arranged_data_TAMILNADU.csv",row.names = F)

现在如何将其应用于多个.txt文件并将输出合并为单个文件。

Answer 1

我建议将融化/重塑功能写入函数并在输入列表中调用它。另外，我使用的是dplyr::gather()而不是reshape2::melt()。希望对您有所帮助！

library(tidyverse)

A = structure(list(Year = 1969:1974, 
                   Jan = c(16.6, 15.6, 15.8, 16.9, 16.2, 15.4), 
                   Feb = c(17, 15.2, 16.6, 14.8, 12.9, 17.9), 
                   Mar = c(14.2, 13.3, 16.9, 14.9, 15.5, 13.4), 
                   Apr = c(11.6, 10.7, 10.7, 11.6, 10.3, 9.7),
                   May = c(9.9, 9.2, 9.7, 9.6, 8.2, 8.8), 
                   Jun = c(7.6, 7.2, 7.1, 7.2, 6, 6.9), 
                   Jul = c(7, 6.7, 6.7, 6.9, 6.9, 5.2), 
                   Aug = c(7, 7.2, 7.2, 6.1, 6.8, 6.5), 
                   Sep = c(8.4, 7.6, 8.5, 7.3, 6.6, 6.8), 
                   Oct = c(10.4, 8.5, 8.5, 9.1, 8.3, 7.7), 
                   Nov = c(14, 12.2, 12.9, 12.2, 10.8, 10.2), 
                   Dec = c(15.5, 16.7, 15.9, 15.5, 13.2, 15.4), 
                   Annual = c(11.6, 10.8, 11.4, 11, 10.1, 10.3), 
                   winter = c(16.8, 15.4, 16.2, 15.8, 14.5, 16.6), 
                   premonsoon = c(11.9, 11.1, 12.4, 12, 11.3, 10.6), 
                   monsoon = c(7.5, 7.2, 7.3, 6.8, 6.6, 6.3), 
                   postmonsoon = c(13.3, 12.5, 12.5, 12.2, 10.7, 11.1)), 
              row.names = c(NA, 6L), 
              class = "data.frame")                                                                                                                                                                                                                                                                                                                                                   11.1)), row.names = c(NA, 6L), class = "data.frame")

B <- A
mylist <- list(A,B)

myfunc <- function (x){
  x %>% 
    gather(key = "Month",
           value = "Value",
            c(format(ISOdatetime(2000,1:12,1,0,0,0),"%b"))) %>% # list of month names
    arrange(Year) %>% # sort dataframe by Year
    select(Year, Month, Value, winter, premonsoon, monsoon, postmonsoon)
}

mylist_melted <- lapply(mylist, myfunc)