Question

时间序列的产出类似于数据框架:

ts(rnorm(12*5, 17, 8), start=c(1981,1), frequency = 12)

       Jan       Feb       Mar       Apr       May       Jun       Jul     ...
1981 14.064085 21.664250 14.800249 -5.773095 16.477470  1.129674 16.747669 ...
1982 23.973620 17.851890 21.387944 28.451552 24.177141 25.212271 19.123179 ...
1983 19.801210 11.523906  8.103132  9.382778  4.614325 21.751529  9.540851 ...
1984 15.394517 21.021790 23.115453 12.685093 -2.209352 28.318686 10.159940 ...
1985 20.708447 13.095117 32.815273  9.393895 19.551045 24.847337 18.703991 ...

把它变成一个包含Jan、Feb、Mar...和1981、1982、......和随后的段落的数据框架是多余的。这样做的最合法方式是什么?

Answer 1

这里有两个途径。第一种方式为即将创建的矩阵设定了名称,然后将数据细分为矩阵,将其转换成数据基。第二种方法是按年份和月变量列出清单,并在随后转换为数据框架和增加姓名时使用。

# create test data
set.seed(123)
tt <- ts(rnorm(12*5, 17, 8), start=c(1981,1), frequency = 12)

1) matrix. This solution requires that we have whole consecutive years

dmn <- list(month.abb, unique(floor(time(tt))))
as.data.frame(t(matrix(tt, 12, dimnames = dmn)))

如果我们不关注冰名,它只是as.data.frame(t(matrix(tt,12))。

可以用@thelatemail s comment取代dmn<-行,行文如下:

dmn <- dimnames(.preformat.ts(tt))

<>2>tapply。采用<代码>tapply的更为一般性的解决办法如下:

Month <-  factor(cycle(tt), levels = 1:12, labels = month.abb)
tapply(tt, list(year = floor(time(tt)), month = Month), c)

<>说明: 以上任何解决办法都是照搬这一代号X。随后尝试:

ts(c(t(X)), start = 1981, freq = 12)

Update

Improvement motivated by comments of @latemail below.

Answer 2

Example with the AirPassengers dataset:

Make the data available and check its type:

data(AirPassengers)
class(AirPassengers)

Convert Time-Series into a data frame:

df <- data.frame(AirPassengers, year = trunc(time(AirPassengers)), 
month = month.abb[cycle(AirPassengers)])

重新确定时间系列目标:

tsData = ts(df$AirPassengers, start = c(1949,1), end = c(1960,12), frequency = 12)

分配成果以确保正确执行:

components.ts = decompose(tsData)
plot(components.ts)

Answer 3

处理一揽子“盒式”

ts = ts(rnorm(12*5, 17, 8), start=c(1981,1), frequency = 12) df = ts_df(ts) str(df)

data.frame: 60 obs. of 2 variables: time : Date, format: "1981-01-01" "1981-02-01" value: num 23.15 22.77 5.1 1.05 13.87

Update

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