ggplot: how to add multiple legends for plot and vertical lines?

Question

I've created a plot which shows the means of two groups and associated 95% confidence band, as below. For the plot, I've already used different line types, fillings, colors.

The data plot_band is as follows.

dput(plot_band)
structure(list(mean = c(0.0909296772008702, 0.0949102886382386, 
0.0989192140983566, 0.102428753920507, 0.106190021551613, 0.109834234007574, 
0.11282406874623, 0.116443987192088, 0.119646042014149, 0.122877131667032, 
0.125734341129646, 0.129194412319665, 0.131921946416482, 0.13467000293138, 
0.137801823091921, 0.140320771073742, 0.143300871011905, 0.145703574224808, 
0.148502607395268, 0.151216269559201, 0.153957673466713, 0.15642722394871, 
0.159399752204122, 0.16158535629103, 0.163992551285173, 0.166446319141126, 
0.168796463238069, 0.17130024918415, 0.17319290052143, 0.175970079857704, 
0.178037138778032, 0.180359643729028, 0.182563083353043, 0.184882067722455, 
0.186933337196788, 0.18928611634363, 0.19095095692481, 0.193552969255731, 
0.195137836881874, 0.197581990963152, 0.199824696342001, 0.201576167030431, 
0.203292777876833, 0.205785273925517, 0.207611128924057, 0.209067294675698, 
0.211624327477106, 0.213018027996152, 0.215073900329166, 0.21654896049152, 
0.218432328738047, 0.220299232072702, 0.221520169903876, 0.224082916931098, 
0.225373663731495, 0.227623092060467, 0.228971037740905, 0.230665903341562, 
0.232255049713341, 0.233816039663021, 0.236156033603955, 0.237722706454038, 
0.239326639984125, 0.241061288510212, 0.323782287073584, 0.325539303794681, 
0.326575563604555, 0.327932235745535, 0.329326904419804, 0.330270965006864, 
0.331794972975829, 0.332736401387824, 0.333736983920265, 0.334858878358806, 
0.335995344145518, 0.336884010919713, 0.337760950823761, 0.338470035342276, 
0.339694375762279, 0.340590586642847, 0.340934410282471, 0.342186505998774, 
0.342699699846757, 0.343822718137376, 0.344352069575663, 0.345191547743302, 
0.345986783878912, 0.346908459064914, 0.347636673707646, 0.3483601957891, 
0.349017016236978, 0.349393026672962, 0.350215046428817, 0.350578051082168, 
0.351357872622786, 0.351833990930714, 0.352451422717008, 0.352852417773313, 
0.353786047124291, 0.354360144310735, 0.354804607588953, 0.355216156665893, 
0.3556114518015, 0.356570758245453, 0.357097049535425, 0.357671243406622, 
0.35787930232607, 0.358500009058086, 0.359107586207553, 0.359418346394681, 
0.359923090516015, 0.360327770652831, 0.360646653761867, 0.361526704703965, 
0.361860340596181, 0.362284616802613, 0.362408547406209, 0.363068975461424, 
0.363173638916247, 0.363746165222553, 0.364318465554143, 0.364550369183249, 
0.365263491228022, 0.365588246738469, 0.366124420845147, 0.366327320718437, 
0.366730809501062, 0.367298014408034), p2.5 = c(0.00920236578162877, 
0.0111305911426958, 0.0131257550019632, 0.015586474005665, 0.017588259827762, 
0.0195835240844649, 0.021653464115484, 0.0245221378289171, 0.0263028370478539, 
0.0283125178459841, 0.030809139661692, 0.034224299031932, 0.0351514351131448, 
0.0374690177003245, 0.0401208217539481, 0.0416432632702995, 0.0436268495854353, 
0.0455924496480308, 0.0481710615607138, 0.0498487868097217, 0.052013860735697, 
0.0541864115090449, 0.0559355297931858, 0.0582185384506931, 0.0595049507852038, 
0.0617291057747846, 0.0624904066599628, 0.064090526611587, 0.0665855608482458, 
0.0681610015253132, 0.0689510143842853, 0.0714235246023074, 0.0730718365551066, 
0.0733828347805513, 0.0749772653575311, 0.0775677990166739, 0.0782434582066251, 
0.0809696065399504, 0.0800620502625316, 0.0822097262074474, 0.0837314882447324, 
0.0836800886932387, 0.0843305338836378, 0.0862036703259026, 0.0874082656018874, 
0.0881312854081838, 0.0887921830279765, 0.0892805555426737, 0.0901061351380764, 
0.0914750995958728, 0.0913838119125662, 0.0926827936869315, 0.0929511644196126, 
0.0940218350370357, 0.0944327299872979, 0.0953545299910439, 0.0948298565703383, 
0.0957001873318579, 0.0961251564147676, 0.0971098251546806, 0.0974911491380601, 
0.0986598120212823, 0.0982370236835561, 0.0987719638365328, 0.114148199394403, 
0.125138552629865, 0.133069438084806, 0.140931059768343, 0.147647282172844, 
0.155831735418124, 0.163154010787227, 0.16809087346053, 0.173413948644787, 
0.178336300631342, 0.183561163161725, 0.189552221591194, 0.192350001446747, 
0.19547327255232, 0.19824967633061, 0.202611107184988, 0.205071997319457, 
0.206232495037667, 0.208471493073236, 0.209717390943683, 0.211692880593303, 
0.213829033311537, 0.215383413348152, 0.216370831366554, 0.216980537940184, 
0.217670415960084, 0.218147500129008, 0.219104770868165, 0.220215949003459, 
0.219501167154474, 0.219635297722562, 0.220565169003312, 0.218821371303922, 
0.218910618214851, 0.219518190869959, 0.219204079206471, 0.219448334243776, 
0.219174641398391, 0.217619259716122, 0.217993716481521, 0.218343413130982, 
0.217141573568049, 0.216438618727695, 0.215672180354215, 0.214841486865522, 
0.214092486614703, 0.216084004877199, 0.213891621307228, 0.213397326450924, 
0.212530621813324, 0.212650230928244, 0.211323326285971, 0.211512467761759, 
0.209879967307571, 0.208388878793908, 0.209257043929222, 0.207665115418059, 
0.207413292377895, 0.204980142991601, 0.206053394727878, 0.205039712521127, 
0.203155679138143, 0.202289445844638, 0.201779149557556), p97.5 = c(0.240681337890249, 
0.239988615023241, 0.239222274397932, 0.23882694927308, 0.239567463457127, 
0.240035884370459, 0.239971640602537, 0.242348644629734, 0.244241554912481, 
0.246794068956881, 0.248869825514075, 0.252843804762058, 0.254595507587193, 
0.257498240756364, 0.26074636531938, 0.263991307688752, 0.268222101449506, 
0.270245299020079, 0.278955701793892, 0.280366963871541, 0.286253886155709, 
0.290942761721134, 0.29709853936211, 0.300641051539586, 0.307350564223005, 
0.314475951046524, 0.31757563389217, 0.324250050938626, 0.326645521042049, 
0.334746718583917, 0.341297900171566, 0.347056902406046, 0.352412986039391, 
0.356409285744598, 0.364329251893085, 0.36882469705109, 0.373595444661095, 
0.379308956442793, 0.388012909521406, 0.393418480355642, 0.399407258087214, 
0.403270925317011, 0.407517084163824, 0.413742327029277, 0.42089783652825, 
0.422996679448412, 0.430738094720356, 0.433915405828653, 0.438263395419797, 
0.442376801773873, 0.450664409546504, 0.453854917168461, 0.455755257192578, 
0.463879371708031, 0.470262095557133, 0.478816677993115, 0.478998770025097, 
0.485204929246363, 0.490588733478761, 0.49747652543363, 0.498792119487052, 
0.508008619470507, 0.51314092048762, 0.518568532547669, 0.579810955268174, 
0.563256045407579, 0.55093710586083, 0.541241619905278, 0.532667775608687, 
0.523824194956849, 0.518816497858615, 0.512618467188886, 0.506452368044292, 
0.501653171003674, 0.499276681561068, 0.496002704329641, 0.494256887981196, 
0.49200837587611, 0.490570113245846, 0.491077058931435, 0.487352049845066, 
0.487927727831147, 0.487928022062059, 0.488900063808496, 0.488866145012628, 
0.489808465409391, 0.491100206396406, 0.492044173457154, 0.494346147046575, 
0.494980820850837, 0.49616843086841, 0.497216550345458, 0.499201695431901, 
0.501160614633382, 0.502598288902507, 0.504203085629905, 0.50530488873578, 
0.508449115699177, 0.508914783054669, 0.51306711977087, 0.51479783743171, 
0.51648055644086, 0.518549503653961, 0.522859455223989, 0.522598786005884, 
0.52736459871623, 0.527054294078792, 0.532359397607223, 0.532643025946804, 
0.533817320437782, 0.535862852499484, 0.539613602346564, 0.54138065631686, 
0.544340213112881, 0.545596882887723, 0.549029532028693, 0.546769636775625, 
0.551728290583129, 0.552996735997194, 0.555676593069663, 0.559580922687426, 
0.561700216317917, 0.562726465369815, 0.563527127546323, 0.567715046522725, 
0.568850181180136, 0.56965258128659, 0.571847219713553), outcome = structure(c(1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("DLT", 
"CB"), class = "factor"), exp_X_post = c(721.595263503532, 794.40305777437, 
865.319646465533, 933.669956578678, 999.728550839186, 1062.12810757171, 
1121.92986212885, 1186.37187215809, 1246.1267376175, 1305.33376392859, 
1359.36602305224, 1421.23758898206, 1472.44041133326, 1520.62395309786, 
1584.09764621781, 1634.01654454251, 1685.34860459111, 1735.26374323406, 
1785.87871337346, 1840.42999799797, 1888.32905203148, 1937.38674685726, 
1990.74583676908, 2041.61942276328, 2083.76909363497, 2134.07414000003, 
2177.97560514382, 2227.25787768033, 2269.76501622686, 2319.50659548171, 
2360.78992430352, 2404.37623851091, 2449.36656617313, 2500.80748523146, 
2540.71467060956, 2588.5685157055, 2630.93535458068, 2675.04099554242, 
2709.53185769419, 2763.12669881888, 2807.24737149465, 2849.03542063784, 
2887.16961904492, 2927.78459960731, 2973.91123171086, 3006.0197134382, 
3056.06581532434, 3089.41001229951, 3132.29020081068, 3177.35838641843, 
3212.66669292569, 3256.19625640177, 3284.73766167032, 3330.28770837953, 
3368.28973519186, 3409.05190043795, 3449.93435443996, 3485.59367731521, 
3524.70884576068, 3557.60265444533, 3615.06476720162, 3648.55074883409, 
3688.13510762386, 3727.38208940522, 721.595263503532, 794.40305777437, 
865.319646465533, 933.669956578678, 999.728550839186, 1062.12810757171, 
1121.92986212885, 1186.37187215809, 1246.1267376175, 1305.33376392859, 
1359.36602305224, 1421.23758898206, 1472.44041133326, 1520.62395309786, 
1584.09764621781, 1634.01654454251, 1685.34860459111, 1735.26374323406, 
1785.87871337346, 1840.42999799797, 1888.32905203148, 1937.38674685726, 
1990.74583676908, 2041.61942276328, 2083.76909363497, 2134.07414000003, 
2177.97560514382, 2227.25787768033, 2269.76501622686, 2319.50659548171, 
2360.78992430352, 2404.37623851091, 2449.36656617313, 2500.80748523146, 
2540.71467060956, 2588.5685157055, 2630.93535458068, 2675.04099554242, 
2709.53185769419, 2763.12669881888, 2807.24737149465, 2849.03542063784, 
2887.16961904492, 2927.78459960731, 2973.91123171086, 3006.0197134382, 
3056.06581532434, 3089.41001229951, 3132.29020081068, 3177.35838641843, 
3212.66669292569, 3256.19625640177, 3284.73766167032, 3330.28770837953, 
3368.28973519186, 3409.05190043795, 3449.93435443996, 3485.59367731521, 
3524.70884576068, 3557.60265444533, 3615.06476720162, 3648.55074883409, 
3688.13510762386, 3727.38208940522)), .Names = c("mean", "p2.5", 
"p97.5", "outcome", "exp_X_post"), row.names = c("pi_A[1]", "pi_A[2]", 
"pi_A[3]", "pi_A[4]", "pi_A[5]", "pi_A[6]", "pi_A[7]", "pi_A[8]", 
"pi_A[9]", "pi_A[10]", "pi_A[11]", "pi_A[12]", "pi_A[13]", "pi_A[14]", 
"pi_A[15]", "pi_A[16]", "pi_A[17]", "pi_A[18]", "pi_A[19]", "pi_A[20]", 
"pi_A[21]", "pi_A[22]", "pi_A[23]", "pi_A[24]", "pi_A[25]", "pi_A[26]", 
"pi_A[27]", "pi_A[28]", "pi_A[29]", "pi_A[30]", "pi_A[31]", "pi_A[32]", 
"pi_A[33]", "pi_A[34]", "pi_A[35]", "pi_A[36]", "pi_A[37]", "pi_A[38]", 
"pi_A[39]", "pi_A[40]", "pi_A[41]", "pi_A[42]", "pi_A[43]", "pi_A[44]", 
"pi_A[45]", "pi_A[46]", "pi_A[47]", "pi_A[48]", "pi_A[49]", "pi_A[50]", 
"pi_A[51]", "pi_A[52]", "pi_A[53]", "pi_A[54]", "pi_A[55]", "pi_A[56]", 
"pi_A[57]", "pi_A[58]", "pi_A[59]", "pi_A[60]", "pi_A[61]", "pi_A[62]", 
"pi_A[63]", "pi_A[64]", "qi_A[1]", "qi_A[2]", "qi_A[3]", "qi_A[4]", 
"qi_A[5]", "qi_A[6]", "qi_A[7]", "qi_A[8]", "qi_A[9]", "qi_A[10]", 
"qi_A[11]", "qi_A[12]", "qi_A[13]", "qi_A[14]", "qi_A[15]", "qi_A[16]", 
"qi_A[17]", "qi_A[18]", "qi_A[19]", "qi_A[20]", "qi_A[21]", "qi_A[22]", 
"qi_A[23]", "qi_A[24]", "qi_A[25]", "qi_A[26]", "qi_A[27]", "qi_A[28]", 
"qi_A[29]", "qi_A[30]", "qi_A[31]", "qi_A[32]", "qi_A[33]", "qi_A[34]", 
"qi_A[35]", "qi_A[36]", "qi_A[37]", "qi_A[38]", "qi_A[39]", "qi_A[40]", 
"qi_A[41]", "qi_A[42]", "qi_A[43]", "qi_A[44]", "qi_A[45]", "qi_A[46]", 
"qi_A[47]", "qi_A[48]", "qi_A[49]", "qi_A[50]", "qi_A[51]", "qi_A[52]", 
"qi_A[53]", "qi_A[54]", "qi_A[55]", "qi_A[56]", "qi_A[57]", "qi_A[58]", 
"qi_A[59]", "qi_A[60]", "qi_A[61]", "qi_A[62]", "qi_A[63]", "qi_A[64]"
), class = "data.frame")

Now I want to add some vertical dashed lines. I wish to use different color for each vertical line and have legend for those lines as well. The information for those vertical lines are in another data frame observed_mean:

dput(observed_mean)
structure(list(TRT = structure(1:9, .Label = c("A", "B", "C", 
"D", "E", "F", "G", "H", "I"), class = "factor"), gmcmin = c(967.117632548, 
1306.76729845833, 2394.519441584, 2404.73065902857, 3047.48745766364, 
2550.12866139, 1863.6505272925, 3569.57489109, 3660.40695204)), .Names = c("TRT", 
"gmcmin"), row.names = c(NA, -9L), class = "data.frame")

Here is the code to generate the plot:

range <- range(plot_band$exp_X_post)
range <- c(floor(range[1]), ceiling(range[2]))
step <- floor((range[2] - range[1]) / 10)

ggplot(plot_band, aes(x = exp_X_post, y = mean, 
                              color = outcome, linetype = outcome)) + 
    geom_ribbon(aes(ymin = p2.5, ymax = p97.5, linetype = NA,
                    fill = outcome), 
                alpha = 0.4) +
    geom_line(size = 1.5) + 
    xlab("Exposure") +
    ylab("Proability of CB/DLT") +
    scale_x_continuous(limits = range,
                       breaks = seq(range[1], range[2], by = step)
                       ) +
    geom_vline(xintercept = observed_mean$gmcmin,
               linetype = 'longdash') +
    theme_bw() +
    theme(legend.position = 'top',
          plot.margin = unit(c(1, 1, 3, 1), "lines"),
          legend.title = element_text(size = 15),
          axis.title.y = element_text(margin = margin(0, 15, 0, 0))) +
    scale_color_discrete(name = "Probability (95% CI)") +
    scale_fill_discrete(name = "Probability (95% CI)") +
    scale_linetype_discrete(name = "Probability (95% CI)")

Note: the last three lines are used to change the legend title from variable name outcome to "Probability (95% CI)". NOT sure whether that's the right way though.

Questions:

I wish to put the current legend to the right, then below that I'd like to put the legend for vertical lines. Could anyone give me some clues how to do that?
As shown in the plot, there are two identical (not same color though) legends on top. The one below comes out if I change the order of the factor outcome with following code. I am not sure why that happens. How could I get rid of that?

plot_band$outcome <- factor(plot_band$outcome, levels = c("DLT", "CB"))

Thanks a lot for any comments/suggestions!!

Instead of including the output of str(plot_band), it is better and more convenient to include the output of dput(plot_band). — Jaap

Mark Peterson Mark Peterson · Accepted Answer · 2016-06-22T20:19:25

The extra legend box is showing up because of the linetype = NA in the aes() of geom_ribbon moving the linetype out of the mapping will take care of that.

For the line labeling, you can perhaps just put the labels on the plot using geom_text

Here is a full plot that does something like that (now with ggrepel to place the labels more sensibly -- can't believe I didn't start there)

# install.packages("devtools")
# devtools::install_github("slowkow/ggrepel")
library(ggrepel)


ggplot(plot_band, aes(x = exp_X_post, y = mean, 
                      color = outcome, linetype = outcome)) + 
  geom_ribbon(aes(ymin = p2.5, ymax = p97.5,
                  fill = outcome), 
              alpha = 0.4
              , linetype = "blank") +
  geom_line(size = 1.5) + 
  xlab("Exposure") +
  ylab("Proability of CB/DLT") +
  scale_x_continuous(limits = range,
                     breaks = seq(range[1], range[2], by = step)
  ) +
  geom_vline(xintercept = observed_mean$gmcmin
             , linetype = 'longdash') +
  geom_text_repel(
     mapping = aes(
        x = gmcmin
        , y = 0
        , label = TRT
        , color = NA
        , linetype = NA)
     , data = observed_mean
     , show.legend = FALSE) +
  theme_bw() +
  theme(legend.position = 'top',
        plot.margin = unit(c(1, 1, 3, 1), "lines"),
        legend.title = element_text(size = 15),
        axis.title.y = element_text(margin = margin(0, 15, 0, 0))) +
  scale_color_discrete(name = "Probability (95% CI)") +
  scale_fill_discrete(name = "Probability (95% CI)") +
  scale_linetype_discrete(name = "Probability (95% CI)")

(Note: the mean labels overlap, so you may need to more careful position those, e.g., by adding another column to observed_mean giving the position where you want them plotted).

If you need the labels to be in a legend instead, you can use this code:

ggplot(plot_band, aes(x = exp_X_post, y = mean, 
                      color = outcome)) + 
  geom_ribbon(aes(ymin = p2.5, ymax = p97.5,
                  fill = outcome), 
              alpha = 0.4
              , linetype = "blank") +
  geom_line(#aes(linetype = outcome)
            #,
              size = 1.5
            # , show.legend = FALSE
            ) + 
  xlab("Exposure") +
  ylab("Proability of CB/DLT") +
  scale_x_continuous(breaks = pretty(range)) +
  geom_vline(
    mapping = aes(xintercept = gmcmin
                  , linetype = TRT)
    , data = observed_mean) +
  theme_bw() +
  theme(legend.position = 'right',
        plot.margin = unit(c(1, 1, 3, 1), "lines"),
        legend.title = element_text(size = 15),
        axis.title.y = element_text(margin = margin(0, 15, 0, 0))) +
  scale_color_discrete(name = "Probability (95% CI)") +
  scale_fill_discrete(name = "Probability (95% CI)") +
  scale_linetype_discrete(name = "Treatment")

Note, that I removed the linetype from the main lines, as it was causing some weirdness with the vertical line. You can add it back by uncommenting the parts in geom_line() but note that it then shows up in the list with the treatments. There is probably a way to fix that if you absolutely need it, but my quick tries aren't working. I will note, however, that the linetypes are a bit hard to pick out.

Example plot with both the legend and the labels

ggplot: how to add multiple legends for plot and vertical lines?

1 Answers