I have a large data set that spanned a month in time with the data stamped in a column called txn_date like the below. (this is a toy reproduction of it)
dat1 <- read.table(text = "var1 txn_date
5 2020-10-25
1 2020-10-25
3 2020-10-26
4 2020-10-27
1 2020-10-27
3 2020-10-31
3 2020-11-01
8 2020-11-02 ", header = TRUE)
Ideally I would like to get a column in my data frame for each date in the data which I think could be done by first getting a single column that is 1 for the first date that appears and then so on.
So something like this
dat1 <- read.table(text = "var1 txn_date day
5 2020-10-25 1
1 2020-10-25 1
3 2020-10-26 2
4 2020-10-27 3
1 2020-10-27 3
3 2020-10-31 7
3 2020-11-01 8
8 2020-11-12 9 ", header = TRUE
I'm not quite sure how to get this. The txn_date column is as.Date in my actual data frame. I think if I could get the single day column like is listed above (then convert it to a factor) then I could always one hot encode the actual levels of that column if I need to. Ultimately I need to use the day of the experiment as a regressor in a regression I'm going to run.
Something along the lines of y ~ x + day_1 + day_2 +...+ error