从R中的CSV文件读取时间

Question

I want to read a CSV file separated by ";" which contains four columns, such as:

16/12/2006;17:24:00;0;1
16/12/2006;17:25:00;2;3
16/12/2006;17:26:00;4;5

but I want a dataframe with 3 columns rather than 4 (that is, merge the date and hour of the two first columns into a single one).

So far, I have come up with this portion of code inspired by Specify custom Date format for colClasses argument in read.table/read.csv to read the data. Then, I'd merge the two columns somehow.

setClass("myDate")
setAs("character","myDate", function(from) as.Date(from, format="%d/%m/%Y") )
setClass("myTime")
setAs("character","myTime", function(from) as.Date(from, format="%H:%M:%S") )

data <- read.table(file = "file.csv", header = FALSE, sep = ";", colClasses =  c("myDate", "myTime", "numeric", "numeric"))

However, the resulting data frame does have a column V2 in which the hour is not properly read.

          V1         V2 V3 V4
1 2006-12-16 2016-03-04  0  1
2 2006-12-16 2016-03-04  2  3
3 2006-12-16 2016-03-04  4  5

Is the myTime class badly defined? If so, how should I change it?

Answer 1

Is there a particular reason why you want to do this during the import, and not after? It seems much easier to import the 4 columns, merge the date and time together using paste , and then use the lubridate package and its dmy_hms function to convert to proper date-time:

require(lubridate)
data <- read.table(file = "file.csv", header = FALSE, sep = ";")
data$date_time <- paste(data$V1, data$V2)
data$date_time <- dmy_hms(data$date_time)
data[1:2] <- list(NULL)