Question

I have some daily time-series data that i need to extract the ‘week day percent’ relative to the week mean. For example, if the first week has mean = 100 and the Sunday value for this week is 20, then sunday becomes 0.2.

Here’s some random data:

set.seed(0)
y = rnorm(1705)
date = seq(as.Date('2008-01-01'), by = 'day', length = length(y))
data.df = data.frame(y, date)

I need a new column called pecent, which is the value explained above. I tried to add some
columns then use tapply, but failed. Appreciate any help!

Answer 1

First create a week variable using format. Then use ddply and transform.

library(plyr)
data.df$week <- format(data.df$date,'%W %Y') #week begins with Monday
data.df <- ddply(data.df,~week,transform,percent=y/mean(y))
head(data.df)

           y       date    week    percent
1  1.2629543 2008-01-01 00 2008  3.1395415
2 -0.3262334 2008-01-02 00 2008 -0.8109741
3  1.3297993 2008-01-03 00 2008  3.3057095
4  1.2724293 2008-01-04 00 2008  3.1630952
5  0.4146414 2008-01-05 00 2008  1.0307451
6 -1.5399500 2008-01-06 00 2008 -3.8281172

Note that week 00 usually is not a full week as is the last week of the year. Merge last and first weeks of subsequent years if that matters.