I am using R and have a long data set as the one outlined below:
Date ID Status
2014-10-01 12 1
2015-04-01 12 1
2015-07-01 12 1
2015-09-01 12 1
2015-11-01 12 0
2016-01-01 12 0
2016-05-01 12 0
2016-08-01 12 1
2017-03-01 12 1
2017-05-01 12 1
2014-10-01 13 1
2015-04-01 13 1
2015-07-01 13 0
2015-11-01 14 0
2016-01-01 14 0
...
My goal is to create a "balanced" data i.e. each ID should occur for each of the 10 dates. The variable "Status" for the initially non-occurring observations should be labeled as N/A. In other words, the outcome should look like this:
Date ID Status
2014-10-01 12 1
2015-04-01 12 1
2015-07-01 12 1
2015-09-01 12 1
2015-11-01 12 0
2016-01-01 12 0
2016-05-01 12 0
2016-08-01 12 1
2017-03-01 12 1
2017-05-01 12 1
2014-10-01 13 1
2015-04-01 13 1
2015-07-01 13 N/A
2015-09-01 13 N/A
2015-11-01 13 N/A
2016-01-01 13 N/A
2016-05-01 13 N/A
2016-08-01 13 N/A
2017-03-01 13 N/A
2017-05-01 13 N/A
2014-10-01 14 N/A
2015-04-01 14 N/A
2015-07-01 14 N/A
2015-09-01 14 N/A
2015-11-01 14 0
2016-01-01 14 0
2016-05-01 14 N/A
2016-08-01 14 N/A
2017-03-01 14 N/A
2017-05-01 14 N/A
...
Thank you for your help!
The following worked for me:
df_b <- data.frame(date = rep(unique(df$date), length(unique(df$id))),
id = rep(unique(df$id), each = length(unique(df$date))))
balanced_data <- left_join(df_b, df)