r - 2d density plot for categories -

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i'm trying make 2d density plot density displayed each category. example, in image below, have density plot each day, , daily densities combined coloured plots. these types of plots common in scientific literature on atmospheric sciences , aerosol pollution studies.

enter image description here

so far i've got this

ggplot(dat, aes(y = `dn/dlogdp`, x = date)) +   stat_density2d(geom="tile", aes(fill = ..density..), contour = false) +   scale_fill_gradient(low="blue", high="red") +   geom_point(alpha = 0.1)   +   theme_bw()

enter image description here

but want facet day, , i'm not sure start.

here example data:

structure(list(date = structure(c(1359244800, 1359245400, 1359246000,  1359246600, 1359247200, 1359247800, 1359248400, 1359249000, 1359249600,  1359250200, 1359250800, 1359251400, 1359252000, 1359252600, 1359253200,  1359253800, 1359254400, 1359255000, 1359255600, 1359256200, 1359256800,  1359257400, 1359258000, 1359258600, 1359259200, 1359259800, 1359260400,  1359261000, 1359261600, 1359262200, 1359262800, 1359263400, 1359264000,  1359264600, 1359265200, 1359265800, 1359266400, 1359267000, 1359267600,  1359268200, 1359268800, 1359269400, 1359270000, 1359270600, 1359271200,  1359271800, 1359272400, 1359273000, 1359273600, 1359274200, 1359274800,  1359275400, 1359276000, 1359276600, 1359277200, 1359277800, 1359278400,  1359279000, 1359279600, 1359280200, 1359280800, 1359281400, 1359282000,  1359282600, 1359283200, 1359283800, 1359284400, 1359285000, 1359285600,  1359286200, 1359286800, 1359287400, 1359288000, 1359288600, 1359289200,  1359289800, 1359290400, 1359291000, 1359291600, 1359292200, 1359292800,  1359293400, 1359294000, 1359294600, 1359295200, 1359295800, 1359296400,  1359297000, 1359297600, 1359298200, 1359298800, 1359299400, 1359300000,  1359300600, 1359301200, 1359301800, 1359302400, 1359303000, 1359303600,  1359304200), class = c("posixct", "posixt"), tzone = "utc"),      `dn/dlogdp` = c(49.8, 49.275, 47.4, 47.975, 48.625, 51.725,      50.7, 47.55, 45.975, 45.35, 45.4, 47.75, 49.625, 48.225,      47.65, 47.3, 48.75, 50.075, 34.725, 42.025, 48.825, 52.25,      54.05, 49.15, 34.6, 34.375, 42.85, 30.325, 43.15, 36.875,      32.85, 36.85, 35.725, 39.8, 38.65, 40.1, 42.675, 38.5, 37.2,      34.425, 25.2, 14.725, 22.675, 14.875, 37.45, 46.025, 49.275,      35.425, 30, 38.9, 28.6, 41.675, 46.05, 48.6, 62.425, 62.65,      61.7, 49.5, 70.05, 71.875, 59.4, 38.525, 36.85, 25.625, 14.675,      14.7, 14.6, 14.725, 15.6, 15, 14.6, 14.75, 15.05, 14.975,      15.425, 15.1, 15.95, 14.95, 15, 14.6, 14.725, 14.85, 15.175,      28.95, 14.975, 14.725, 16.6, 18.925, 53.225, 60.2, 56.425,      54.55, 41.4, 19.025, 19.825, 31.875, 14.85, 16.375, 16.65,      34.325), diameter = c(14.6, 15.1, 15.7, 16.3, 16.8, 17.5,      18.1, 18.8, 19.5, 20.2, 20.9, 21.7, 22.5, 23.3, 24.1, 25,      25.9, 26.9, 27.9, 28.9, 30, 31.1, 32.2, 33.4, 34.6, 35.9,      37.2, 38.5, 40, 41.4, 42.9, 44.5, 46.1, 47.8, 49.6, 51.4,      53.3, 55.2, 57.3, 59.4, 61.5, 63.8, 66.1, 68.5, 71, 73.7,      76.4, 79.1, 82, 85.1, 88.2, 91.4, 94.7, 98.2, 101.8, 105.5,      109.4, 113.4, 117.6, 121.9, 126.3, 131, 135.8, 140.7, 145.9,      151.2, 156.8, 162.5, 168.5, 174.7, 181.1, 187.7, 194.6, 201.7,      209.1, 216.7, 224.7, 232.9, 241.4, 250.3, 259.5, 269, 278.8,      289, 299.6, 310.6, 322, 333.8, 346, 358.7, 371.8, 385.4,      399.5, 414.2, 429.4, 445.1, 461.4, 478.3, 495.8, 514)), .names = c("date",  "dn/dlogdp", "diameter"), row.names = c(na, 100l), class = c("tbl_df",  "tbl", "data.frame"))

update question misguided , think using categories isn't relevant recreating plot. these other questions more closely related task of recreating plot:

and after asked question have been keeping updated gist of r code combines details answers these questions, , replicates these plots (example output included in gist). gist here: https://gist.github.com/benmarwick/9a54cbd325149a8ff405

the key steps strip away of decoration in panels, , use scale_*_continuous(expand = c(0,0)) make density plot fill entire panel. here's example of how put together: 

# day , hour use facet panels dat$day <- as.date(dat$date) dat$hour <- as.numeric(format(dat$date, "%h"))  library(ggplot2) library(viridis)  # theme suppress many details squeeze_grid_theme <- theme_bw() + theme(axis.title = element_blank(),                              axis.ticks = element_blank(),                              axis.text = element_blank(),                              strip.text = element_blank(),                              strip.background = element_blank(),                              panel.margin.y = unit(0, "lines"),                              panel.margin.x = unit(-1,"lines"),                             panel.border = element_blank(),                              panel.grid = element_blank(),                              axis.text.x = element_text(margin=margin(0,0,0,0,"pt")),                             axis.text.y = element_text(margin=margin(0,0,0,0,"pt")))  p <- ggplot(dat, aes(z = diameter, y = `dn/dlogdp`, x = date)) +   stat_density2d(geom="tile", aes(fill = ..density..), contour = false) +   scale_fill_viridis() +   geom_point(alpha = 0.1)   +   facet_grid(~hour) +   scale_y_continuous(expand = c(0,0)) +    scale_x_datetime(expand = c(0,0)) +   squeeze_grid_theme  p

enter image description here

then separate density plot each hour, tightly squeezed example plot in question.


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