Lets say I have a dataset where rows keep falling out as I go through the days, and I want to add these rows in again.
Example with missing rows:
Fruits <- c(rep(c("apples","oranges","pears","kiwis"),3),
"bananas","oranges","pears","kiwis","bananas","pears","kiwis","bananas")
Days <- c(rep("Monday",4),rep("Tuesday",4),rep("Wednesday",5),
rep("Thursday",4),rep("Friday",3))
Amounts <- c(10,15,20,20,10,15,20,20,10,15,20,20,25,15,20,20,25,20,20,25)
dfmissing <- data.frame(Fruits,Days,Amounts)
And I want it to fill new rows on Thursday and Friday when "apples" and "oranges" drop out as such.
Note that "bananas" appears for the first time on Wednesday, which complicates matters a little.
The completed table should look like the following
Fruits <- c(rep(c("apples","oranges","pears","kiwis"),2),
rep(c("apples","oranges","pears","kiwis","bananas"),3))
Days <- c(rep("Monday",4),rep("Tuesday",4),
rep("Wednesday",5),rep("Thursday",5),rep("Friday",5))
Amounts <- c(rep(c("10","15","20","20"),2),rep(c("10","15","20","20","25"),3))
dfcomplete <- data.frame(Fruits,Days,Amounts)
Comparing the two tables
dfmissing
dfcomplete
Assume there is only one week of data so "Monday" never gets repeated etc - the column "Days" is a list of unique factors.
Thanks in advance.