Generating ggplot2 density hygrograms as lines
I have a simple table of ratings that I have collected from 3 websites (say OpenTable, Yelp, TripAdvisor). Ratings go from 1 to 5, and therefore Rating is a factor column and Website is another factor column (only 3 values ββare allowed). I only have two columns and all my observations. The structure is a named data frame all
containing the aforementioned columns. Example:
Website Rating
_________________________
Yelp 1
TripAdvisor 2
Yelp 3
OpenTable 2
What I would like to do is have a color density.
My problem looks EXACTLY the same as in this thread: Create a density plot with ggplot2 using a factor
However, this solution doesn't work for me. I tried this by simply replacing the variable names using
ggplot(all, aes(rating, colour=website, group=website)) + geom_density()
but that won't work. Instead of giving me an interpolated curve, this is what I get:
It seems to me that I have the same data structure as the OP in the associated thread: a data frame ( all
) with two columns of factors ( website
and rating
).
> mode(all)
[1] "list"
> head(all$website)
[1] TripAdvisor TripAdvisor TripAdvisor TripAdvisor TripAdvisor TripAdvisor
Levels: TripAdvisor OpenTable Yelp
> head(all$rating)
[1] 1 2 1 4 5 2
Levels: 1 2 3 4 5
My question is, why is my behavior different? And what can I do to get the same plot? As a bonus / other solution, I would also try to interpolate my points with straight lines instead of using more complex kernels, but I need to keep the density as I have many other observations for one website than the other 2 combined.
Sample data:
> dput(all[sample(nrow(all), 200),])
structure(list(website = structure(c(3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
2L, 1L, 3L, 2L, 1L, 3L, 2L, 1L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 1L,
3L, 3L, 1L, 3L, 2L, 3L, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 3L, 3L, 3L,
2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 1L, 3L, 1L, 3L, 2L, 3L, 3L, 3L, 3L, 3L,
2L, 3L, 3L, 3L, 1L, 3L, 1L, 3L, 3L, 2L, 3L, 3L, 3L, 3L, 1L, 3L,
3L, 3L, 3L, 3L, 2L, 3L, 1L, 3L, 3L, 3L, 3L, 3L, 2L, 3L, 1L, 3L,
1L, 3L, 3L, 3L, 3L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 3L, 3L, 3L,
3L, 3L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 2L, 1L, 3L, 3L, 3L,
1L, 3L, 3L, 2L, 3L, 3L, 3L, 3L, 1L, 3L, 3L, 3L, 3L, 1L, 3L, 3L,
3L, 3L, 3L, 3L, 1L, 1L, 3L, 3L, 3L, 3L, 1L, 2L, 3L, 1L, 3L, 3L,
3L, 3L), .Label = c("TripAdvisor", "OpenTable", "Yelp"), class = "factor"),
rating = c(2, 4, 5, 3, 5, 3, 2, 4, 4, 5, 5, 2, 5, 5, 4, 2,
5, 4, 5, 5, 4, 4, 3, 5, 3, 2, 4, 4, 4, 2, 4, 5, 3, 4, 5,
4, 4, 3, 5, 4, 5, 2, 5, 5, 4, 3, 1, 5, 5, 5, 5, 2, 4, 1,
1, 4, 4, 4, 3, 1, 5, 4, 4, 5, 4, 4, 5, 4, 1, 1, 3, 4, 5,
5, 5, 4, 5, 2, 3, 4, 2, 4, 4, 4, 3, 2, 4, 4, 4, 4, 5, 4,
5, 3, 1, 5, 2, 3, 5, 1, 5, 4, 4, 5, 5, 4, 4, 4, 4, 5, 4,
4, 4, 3, 3, 5, 2, 4, 3, 5, 3, 3, 3, 5, 4, 1, 3, 3, 5, 4,
4, 2, 2, 4, 3, 2, 5, 5, 5, 4, 5, 1, 2, 5, 2, 4, 2, 5, 3,
4, 4, 3, 4, 5, 3, 3, 5, 4, 2, 4, 5, 4, 1, 4, 5, 1, 5, 1,
2, 5, 3, 3, 4, 5, 4, 4, 3, 3, 4, 4, 3, 3, 4, 3, 4, 3, 4,
5, 3, 2, 5, 3, 4, 4, 1, 5, 4, 3, 5, 3)), .Names = c("website",
"rating"), row.names = c(2736944L, 3701156L, 4217688L, 5350640L,
3600261L, 2944052L, 3522393L, 5443298L, 3965562L, 490821L, 4706825L,
1694078L, 3395609L, 2220568L, 2886121L, 4329867L, 3414341L, 4911507L,
2629607L, 2547491L, 5254750L, 5089579L, 922864L, 643065L, 1797579L,
782480L, 686194L, 5035633L, 998745L, 553929L, 888404L, 730158L,
4357257L, 1824206L, 4941425L, 2910113L, 2006209L, 643302L, 1534660L,
3489947L, 202175L, 2483374L, 820339L, 3411547L, 4792406L, 1379214L,
3900503L, 1000939L, 3823518L, 5340233L, 1330743L, 5333146L, 3638755L,
2445636L, 1057389L, 5092709L, 5092040L, 3841598L, 3739264L, 1482807L,
1314908L, 2522682L, 1757427L, 723017L, 4809829L, 4636027L, 1728575L,
2974897L, 3485658L, 2592565L, 3207974L, 2721825L, 4295506L, 4953206L,
3325724L, 4706765L, 455090L, 5386094L, 612504L, 3483673L, 881132L,
1715784L, 4478951L, 1995026L, 1640553L, 4213693L, 925338L, 4541407L,
3602299L, 5233082L, 727017L, 4954392L, 270757L, 3436121L, 3793314L,
824985L, 1558576L, 3659425L, 2131835L, 1721671L, 32696L, 3405602L,
2736827L, 4403647L, 2171731L, 2954043L, 976434L, 3680791L, 30799L,
4833704L, 3895171L, 4469617L, 2517017L, 4236947L, 733711L, 1480361L,
255671L, 4847331L, 355851L, 2933805L, 5470569L, 3045714L, 3423394L,
475428L, 4460007L, 4668961L, 1560070L, 3314368L, 2150067L, 4480758L,
781676L, 3659111L, 4799721L, 3509779L, 5320687L, 5179115L, 852931L,
4141898L, 4768793L, 1356381L, 3881247L, 1685112L, 2232222L, 315374L,
1721551L, 1464571L, 2472040L, 3198238L, 4719488L, 2763751L, 2999152L,
2042160L, 1374928L, 1703496L, 1805583L, 5192311L, 3558389L, 925026L,
5497787L, 2464617L, 1850617L, 1047932L, 186007L, 3168546L, 1433736L,
1548105L, 5450L, 5288180L, 2476807L, 997242L, 4693332L, 5107109L,
3338800L, 2722363L, 58422L, 3408902L, 4537803L, 2780976L, 2129998L,
376274L, 1773109L, 5138810L, 2364642L, 1087043L, 3318862L, 1567254L,
418564L, 726387L, 4128160L, 4669905L, 1194602L, 2315020L, 211234L,
818018L, 3378122L, 462827L, 1516313L, 3120210L, 4257323L, 5214034L
), class = "data.frame")
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As @joran pointed out in his comment, it all looks like bandwidth. If I draw your low bandwidth data samples it looks like the image you provided:
ggplot(all, aes(rating, colour=website, group=website)) + geom_density(adjust=0.1)
But with high bandwidth it looks very different:
ggplot(all, aes(rating, colour=website, group=website)) + geom_density(adjust=2)
If you just want to plot your relative frequencies associated with the lines, I think you should calculate them beforehand. For example:
all.prop <- data.frame(prop.table(table(website=all$website, rating=all$rating),1))
ggplot(all.prop, aes(x=rating, y=Freq)) + geom_line(aes(group=website, color=website))
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