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I'm trying to create a cumulative graph as shown here, with another caveat. The steps should be based 2 minute time intervals, whereby an interval may have multiple or even no entries.

I used rowSums to create the column for the value to be used in cumsum, e.g., 

df_so $intraverbal <- rowSums(df_so[-1] == "intraverbal")
df_so$tact <- rowSums(df_so[-1] == "tact")
df_so$mand <- rowSums(df_so[-1] == "mand")
df_so$echoic <- rowSums(df_so[-1] == "echoic")

The graph worked out well enough using plot:

plot(cumsum(df_so$intraverbal), type="s")

A cumulative graph - not by 2 minute intervals.

However, there are a couple ways it falls short. Ideally, the data would be tallied and labeled according to the "time bin". At the very least, the time bins should be on the x-label, but the increments aren't continuous. Hypothetically, I should be using dplyr or lapply to melt and combine them - but I'm not sure how. Perhaps, something as described here.

It would be nice to accomplish this with ggplot, so that the varying cumsums can be on the same graph, e.g., like here, or perhaps with stat_bin as here.

Here's a small working sample of the data:

df_so <- structure(list(time.bin = structure(c(1L, 1L, 1L, 1L, 1L, 1L,1L, 124L, 124L, 124L), .Label = c("0:00:00", "0:02:00", "0:04:00","0:06:00", "0:08:00", "0:10:00", "0:12:00", "0:14:00", "0:16:00","0:18:00",
         "0:20:00", "0:22:00", "0:24:00", "0:26:00", "0:28:00","0:30:00", "0:32:00", "0:34:00", "0:36:00", "0:38:00", "0:40:00","0:42:00", "0:44:00", "0:46:00", "0:48:00", "0:50:00", "0:52:00","0:54:00", "0:56:00", "0:58:00",
         "1:00:00", "1:02:00", "1:04:00","1:06:00", "1:08:00", "1:10:00", "1:12:00", "1:14:00", "1:16:00","1:18:00", "1:20:00", "1:22:00", "1:24:00", "1:26:00", "1:28:00","1:30:00", "1:32:00", "1:34:00", "1:36:00", "1:38:00",
         "1:40:00","1:42:00", "1:44:00", "1:46:00", "1:48:00", "1:50:00", "1:52:00","1:54:00", "1:56:00", "1:58:00", "2:00:00", "2:02:00", "2:04:00","2:06:00", "2:08:00", "2:10:00", "2:12:00", "2:14:00", "2:16:00","2:18:00",
         "2:20:00", "2:22:00", "2:24:00", "2:26:00", "2:28:00","2:30:00", "2:32:00", "2:34:00", "2:36:00", "2:38:00", "2:40:00","2:42:00", "2:44:00", "2:46:00", "2:48:00", "2:50:00", "2:52:00","2:54:00", "2:56:00", "2:58:00",
         "3:00:00", "3:02:00", "3:04:00","3:06:00", "3:08:00", "3:10:00", "3:12:00", "3:14:00", "3:16:00","3:18:00", "3:20:00", "3:22:00", "3:24:00", "3:26:00", "3:28:00","3:30:00", "3:32:00", "3:34:00", "3:36:00", "3:38:00", "3:40:00","3:42:00", "3:44:00", "3:48:00", "3:50:00", "3:52:00", "3:54:00","3:56:00", "3:58:00", "4:00:00", "4:02:00", "4:04:00", "4:06:00","4:08:00"), class = "factor"),
         Primary.VB = structure(c(1L,3L, 1L, 3L, 1L, 3L, 1L, 1L, 1L, 1L), .Label = c("", "echoic","intraverbal", "mand", "tact"), class = "factor"),
         Secondary.VB = structure(c(1L,1L, 1L, 5L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("", "echoic","intraverbal", "mand", "tact"), class = "factor"),
         Tertiary.VB = structure(c(1L,1L, 1L, 3L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("", "intraverbal","mand", "tact"), class = "factor"), intraverbal = c(0, 1, 0,1, 0, 1, 0, 0, 0, 0),
         tact = c(0, 0, 0, 1, 0, 0, 0, 0, 0, 0),mand = c(0, 0, 0, 1, 0, 0, 0, 0, 0, 0),
         echoic = c(0, 0,0, 0, 0, 0, 0, 0, 0, 0)), .Names = c("time.bin", "Primary.VB","Secondary.VB","Tertiary.VB","intraverbal",
         "tact", "mand", "echoic"), row.names = c(1L, 2L,3L, 4L, 5L, 6L, 7L, 1648L, 1649L, 1650L), class = "data.frame")
Community
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d-cubed
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1 Answers1

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Not an answer, just and extended comment that I'll delete. If we ignore for a second that the x axis represents the factor numbers...does it look alright?

tbl_df(df_so) %>% 
  group_by(time.bin) %>% 
  mutate(Csum=cumsum(intraverbal)) %>% 
  summarise(last=last(Csum)) %>% 
  mutate(tCsum=cumsum(last)) %>% 
  mutate(time.bin=as.numeric(time.bin)) %>% 
  ggplot(., aes(time.bin, tCsum))+
  geom_step()
Dambo
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  • I added a picture. It's a cumulative tally so the values should keep going up. – d-cubed Jul 30 '16 at 22:59
  • Looks awesome. I wasn't familiar with some of these functions (tbl_df, group_by). I think it's doing what it's supposed to with the time bins. Since it's ggplot the x label should be straightforward(?). Bonus points for intraverbal and echoic together... – d-cubed Jul 31 '16 at 09:27
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    @Donnied I wouldn't be able to relabel on the fly unless I look into the documentation...but I bet there must be a more efficient way than converting to numeric and relabeling (what I did). Maybe using an ordered factor? – Dambo Jul 31 '16 at 20:55