我有一个包含以下列的data.frame:Month,Store和Demand。
Month Store Demand
Jan A 100
Feb A 150
Mar A 120
Jan B 200
Feb B 230
Mar B 320
我需要转动它来制作一个新的data.frame或数组,每个月都有列,例如:
Store Jan Feb Mar
A 100 150 120
B 200 230 320
非常感谢任何帮助。我刚开始用R。
答案 0 :(得分:9)
> df <- read.table(textConnection("Month Store Demand
+ Jan A 100
+ Feb A 150
+ Mar A 120
+ Jan B 200
+ Feb B 230
+ Mar B 320"), header=TRUE)
因此,您的月份列很可能是按字母顺序排序的因子列 (编辑:)
> df$Month <- factor(df$Month, levels= month.abb[1:3])
# Just changing levels was not correct way to handle the problem.
# Need to use within a factor(...) call.
> xtabs(Demand ~ Store+Month, df)
Month
Store Jan Feb Mar
A 100 150 120
B 200 230 320
一种稍微不那么明显的方法(因为'I'函数返回其参数):
> with(df, tapply(Demand, list(Store, Month) , I) )
Jan Feb Mar
A 100 150 120
B 200 230 320
答案 1 :(得分:5)
欢迎来到R.
通常有很多方法可以使用R来达到同一目的。另一种方法是使用Hadley的重塑包。
# create the data as explained by @Dwin
df <- read.table(textConnection("Month Store Demand
Jan A 100
Feb A 150
Mar A 120
Jan B 200
Feb B 230
Mar B 320"),
header=TRUE)
# load the reshape package from Hadley -- he has created GREAT packages
library(reshape)
# reshape the data from long to wide
cast(df, Store ~ Month)
作为参考,你应该看看这个很棒的教程。 http://www.jstatsoft.org/v21/i12/paper
答案 2 :(得分:4)
如果数据在dat
(并且级别设置为日历顺序),则另一个基本R解决方案是使用(令人难以置信的不直观)reshape()
函数:
reshape(dat, v.names = "Demand", idvar = "Store", timevar = "Month",
direction = "wide")
对于数据片段给出:
> reshape(dat, v.names = "Demand", idvar = "Store", timevar = "Month",
+ direction = "wide")
Store Demand.Jan Demand.Feb Demand.Mar
1 A 100 150 120
4 B 200 230 320
如果您愿意,可以轻松清理名称:
> out <- reshape(dat, v.names = "Demand", idvar = "Store", timevar = "Month",
+ direction = "wide")
> names(out)[-1] <- month.abb[1:3]
> out
Store Jan Feb Mar
1 A 100 150 120
4 B 200 230 320
(为了得到上面的输出,我以与@ DWin的答案中显示的方式类似的方式读取数据,然后执行以下操作:
dat <- transform(dat, Month = factor(Month, levels = month.abb[1:3]))
其中dat
就是我所说的数据)