3

用 读入大型数据集后read.csv.ffdf，其中一列是时间。例如2014-10-18 00:01:02，对于该列中的 100 万行。该列是一个因素。如何将其转换为POSIXct受支持ff？只需使用as.POSIXct()将值转换为NA

或者当我一开始读入数据集时，我可以将该列指定为POSIXct吗？

我的目标是获得月份和日期（甚至小时）。因此，除了转换为POSIXct.

例如，我们有 9 x 2 表，

test <- read.csv.ffdf(file="test.csv", header=T, first.rows=-1)

两列是 ID（数值类）和时间（因子类）

这是输入

structure(list(virtual = structure(list(VirtualVmode = c("integer", 
"integer"), AsIs = c(FALSE, FALSE), VirtualIsMatrix = c(FALSE, 
FALSE), PhysicalIsMatrix = c(FALSE, FALSE), PhysicalElementNo = 1:2, 
    PhysicalFirstCol = c(1L, 1L), PhysicalLastCol = c(1L, 1L)), .Names = c("VirtualVmode", 
"AsIs", "VirtualIsMatrix", "PhysicalIsMatrix", "PhysicalElementNo", 
"PhysicalFirstCol", "PhysicalLastCol"), row.names = c("ID", "time"
), class = "data.frame", Dim = c(9L, 2L), Dimorder = 1:2), physical = structure(list(
    ID = structure(list(), physical = <pointer: 0x000000000821ab20>, virtual = structure(list(), Length = 9L, Symmetric = FALSE), class = c("ff_vector", 
    "ff")), time = structure(list(), physical = <pointer: 0x000000000821abb0>, virtual = structure(list(), Length = 9L, Symmetric = FALSE, Levels = c("10/17/2003 0:01", 
    "12/5/1999 0:02", "2/1/2000 0:01", "3/23/1998 0:01", "3/24/2013 0:00", 
    "5/29/2004 0:00", "5/9/1985 0:01", "6/14/2010 0:01", "6/25/2008 0:02"
    ), ramclass = "factor"), class = c("ff_vector", "ff"))), .Names = c("ID", 
"time")), row.names = NULL), .Names = c("virtual", "physical", 
"row.names"), class = "ffdf")
4

2 回答 2

1

您可以使用 from package ffbase 如下所示的玩具示例。最好的。

require(ff)
x <- data.frame(id = 1:100000, timepoint = seq(from = Sys.time(), by = "sec", length.out = 100000))
x$timepoint <- as.factor(x$timepoint)

xff <- as.ffdf(x)
class(xff)
require(ffbase)
xff$time <- with(xff, as.POSIXct(as.character(timepoint)), by = 10000)
ramclass(xff$time)
[1] "POSIXct" "POSIXt" 
str(xff[1:10, ])
'data.frame':   10 obs. of  3 variables:
 $ id       : int  1 2 3 4 5 6 7 8 9 10
 $ timepoint: Factor w/ 100000 levels "2014-10-20 09:14:10",..: 1 2 3 4 5 6 7 8 9 10
 $ time     : POSIXct, format: "2014-10-20 09:14:10" "2014-10-20 09:14:11" "2014-10-20 09:14:12" "2014-10-20 09:14:13" ...
于 2014-10-20T07:18:08.610 回答
0

colClasses读入数据时使用。例如，您的两列示例：（ID数字类）和time（因子类）：

test <- read.csv.ffdf(file="test.csv", header=T, first.rows=-1,colClasses = c("integer","POSIXct"))
于 2015-08-10T11:24:56.300 回答