I have a data set of daily value. It spans from Dec-1 2018 to April-1 2020.
The columns are "date" and "value". As shown here:
date <- c("2018-12-01","2000-12-02", "2000-12-03",
...
"2020-03-30","2020-03-31","2020-04-01")
value <- c(1592,1825,1769,1909,2022, .... 2287,2169,2366,2001,2087,2099,2258)
df <- data.frame(date,value)
What I would like to do is the sum the values by week and then calculate week over week change from the current to previous year.
I know that I can sum by week using the following function:
Data_week <- df%>% group_by(category ,week = cut(date, "week")) %>% mutate(summed= sum(value))
My questions are twofold:
1) How do I sum by week and then manipulate the dataframe so that I can calculate week over week change (e.g. week dec.1 2019/ week dec.1 2018).
2) How can I do that above, but using a "customized" week. Let's say I want to define a week as moving 7 days back from the latest date I have data for. Eg. the latest week I would have would be week starting on March 26th (April 1st -7 days).