如何从 R 中的每日时间序列计算每月的变化率? [英] How do I calculate a monthly rate of change from a daily time series in R?

问题描述

我开始接触 R，而且我对时间序列概念是全新的.任何人都可以根据每日数据点指出正确的方向来计算每月的百分比变化吗?我想要每个月的第一个和最后一个数据点之间的变化.例如:

I'm beginning to get my feet wet with R, and I'm brand new to time series concepts. Can anyone point me in the right direction to calculate a monthly % change, based on a daily data point? I want the change between the first and last data points of each month. For example:

t 系列数据:

1/1/2000 10.00
...
1/31/2000 10.10
2/1/2000 10.20
...
2/28/2000 11.00

我正在寻找表单的返回数据框:

I'm looking for a return data frame of the form:

1/31/2000 .01
2/28/2000 .0784

理想情况下，我可以从上个月的端点计算到当月的端点，但我假设按月分区作为起点更容易.我正在查看包 zoo 和 xts，但仍然卡住了.有接班人吗?谢谢...

Ideally, I'd be able to calculate from the endpoint of the prior month to the endpoint of current month, but I'm supposing partitioning by month is easier as a starting point. I'm looking at packages zoo and xts, but am still stuck. Any takers? Thanks...

推荐答案

这是一种使用 plyr 和 ddply 的方法.我按顺序使用 ddply，首先获取每个月的第一行和最后一行，然后再次计算 monthlyReturn.(也许使用 xts 或 zoo 可能更容易，我不确定.)

Here's one way to do it using plyr and ddply. I use ddply sequentially, first to get the first and last rows of each month, and again to calculate the monthlyReturn. (Perhaps using xts or zoo might be easier, I am not sure.)

#Using plyr and the data in df
df$Date <- as.POSIXlt(as.Date(df$Date, "%m/%d/%Y"))
df$Month <- (df$Date$mon + 1) #0 = January

sdf <- df[,-1] #drop the Date Column, ddply doesn't like it

library("plyr")
#this function is called with 2 row data frames
monthlyReturn<- function(df) {
  (df$Value[2] - df$Value[1])/(df$Value[1])  
}

adf <- ddply(sdf, .(Month), function(x) x[c(1, nrow(x)), ]) #get first and last values for each Month   
mon.returns <- ddply(adf, .(Month), monthlyReturn)

这是我用来测试它的数据:

Here's the data I used to test it out:

> df
         Date Value
1    1/1/2000  10.0
2   1/31/2000  10.1
3    2/1/2000  10.2
4   2/28/2000  11.0
5    3/1/2000  10.0
6   3/31/2000  24.1
7   5/10/2000 510.0
8   5/22/2000 522.0
9   6/04/2000 604.0
10  7/03/2000  10.1
11  7/30/2000   7.2
12 12/28/2000  11.0
13 12/30/2000   3.0

> mon.returns
  Month          V1
1     1  0.01000000
2     2  0.07843137
3     3  1.41000000
4     5  0.02352941
5     6  0.00000000
6     7 -0.28712871
7    12 -0.72727273

希望有所帮助.

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