I have a data frame with three variables: a grouping variable (Group) and categorical variables indicating if the group is new (New) and if its entry is delinquent (Delinquent).
Here are sample data:
df <- structure(list(Group = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 5L, 6L, 7L), .Label = c("A", "B", "C", "D", "E", "F", "G"), class = "factor"), New = c(FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, TRUE, FALSE), Delinquent = c(FALSE, TRUE, TRUE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE)), .Names = c("Group", "New", "Delinquent"), class = "data.frame", row.names = c(NA, -14L))
#df
I'm trying to count the number of delinquent groups, by whether they're new or not. To do this, I've wrapped table around aggregate on a simple data frame:
yo <- table(aggregate(Delinquent ~ Group + New, data = df, FUN = max))
which produces the rather odd output, an object of class "table"
yo
#, , Delinquent = 0
#
# New
#Group FALSE TRUE
# A 0 0
# B 0 0
# C 1 0
# D 0 1
# E 1 0
# F 0 1
# G 0 0
#
#, , Delinquent = 1
#
# New
#Group FALSE TRUE
# A 1 0
# B 0 1
# C 0 0
# D 0 0
# E 0 0
# F 0 0
# G 1 0
The output seems to be what I need to tally the number of delinquent groups by their status as new or not. Normally, I convert tables to data frames to interact with the data directly. However, in this case, I can't interact with the outputted table object or convert it successfully. I've tried converting it to a data frame via as.data.frame and as.data.frame.matrix and as a list via as.list and as.data.frame.list, but the converted output does not seem to be right. Using as.data.frame.array is the best I could come up with, but I was expecting a list of two separate data frames, one for each delinquency status. Any suggestions?
as.data.frame.array(yo)
# FALSE.0 TRUE.0 FALSE.1 TRUE.1
# A 0 0 1 0
# B 0 0 0 1
# C 1 0 0 0
# D 0 1 0 0
# E 1 0 0 0
# F 0 1 0 0
# G 0 0 1 0
You should use as.data.frame.table.
If you want to put everything into one data.frame:
as.data.frame.table(yo)
Group New Delinquent Freq
1 A FALSE 0 0
2 B FALSE 0 0
3 C FALSE 0 1
4 D FALSE 0 0
5 E FALSE 0 1
...
If like you said you want a list of data.frames:
(yolist <- apply(yo, 3, as.data.frame.table))
$`0`
Group New Freq
1 A FALSE 0
2 B FALSE 0
3 C FALSE 1
4 D FALSE 0
5 E FALSE 1
...
$`1`
Group New Freq
1 A FALSE 1
2 B FALSE 0
3 C FALSE 0
4 D FALSE 0
5 E FALSE 0
...
sapply(yolist, class)
0 1
"data.frame" "data.frame"
This works because your table is 3-dimensional array. The line above constructs a data.frame from a table sliced by appropriate index.