Boxplot有两个级别和多个data.frames

时间：2015-07-06 22:50:45

标签： r ggplot2 boxplot

我有4个data.frames，每个data.frame有两个因子级别。 df1转载如下。请复制df1以生成df2 ... df4。

如何使用ggplot2生成箱形图，这样我的最终数字看起来与下图非常相似？图中的季节表示数据帧名称，而现在和将来表示级别名称，图例表示此处复制的数据中的重，重，重。

忽略虚线水平红线。

enter image description here 

df1= structure(list(id = 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, 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("NN", "SS"), class = "factor"), 
        heavy = c(0.136230125, 0.136281211, 0.136038018, 0.135392862, 
        0.137088902, 0.136028293, 0.13640057, 0.135317058, 0.13688615, 
        0.136448994, 0.137089424, 0.136810847, 0.135865471, 0.136130096, 
        0.136361327, 0.137796714, 0.136052839, 0.135892646, 0.13544437, 
        0.136452363, 0.135367421, 0.135617509, 0.138202559, 0.135396942, 
        0.135930092, 0.135661805, 0.135666, 0.135860128, 0.137648687, 
        0.136057353, 0.136057731, 0.135162399, 0.136080113, 0.135285036, 
        0.136204839, 0.138058091, 0.137215664, 0.135696637, 0.135863902, 
        0.135733243, 0.138274445, 0.136632122, 0.137787919, 0.135033093, 
        0.136926798, 0.136766413, 0.13690947, 0.135203152, 0.138370968, 
        0.136862356, 0.136083112, 0.138212845, 0.135964773, 0.13583601, 
        0.134923731, 0.135828965, 0.136272539, 0.138127602, 0.137028323, 
        0.136526836, 0.136407397, 0.137025373, 0.138358757, 0.137858521, 
        0.135464076, 0.136302506, 0.135528362, 0.137540677, 0.136455865, 
        0.138470144, 0.137227895, 0.136296955, 0.136792631, 0.135875782, 
        0.13815733, 0.136383864, 0.136696618, 0.13857652, 0.136700903, 
        0.136743873, 0.136033619, 0.135970522, 0.135816385, 0.136003984, 
        0.136583925, 0.136768202, 0.136292002, 0.136316737, 0.136540075, 
        0.136051218, 0.135924119, 0.136736303, 0.136946894, 0.136266073, 
        0.136263692, 0.136399301, 0.13611577, 0.135857095, 0.136769488, 
        0.136072466, 0.135564224, 0.136496131, 0.137659507, 0.136704681, 
        0.136542173, 0.136777403, 0.135771538, 0.13665463, 0.136984748, 
        0.137717859, 0.138195237, 0.136232227, 0.135956814), heavier = c(0.227332679, 
        0.227200132, 0.227299118, 0.227289816, 0.22724478, 0.227082442, 
        0.227861315, 0.227055561, 0.227112284, 0.228651438, 0.228158412, 
        0.228789678, 0.227188949, 0.228850198, 0.227246991, 0.227359368, 
        0.227359531, 0.227310607, 0.229490445, 0.227295226, 0.227958185, 
        0.228104958, 0.227254823, 0.22715392, 0.228062515, 0.227509559, 
        0.227143662, 0.230048719, 0.227860836, 0.228467792, 0.227263728, 
        0.227222794, 0.227165592, 0.227140611, 0.228424335, 0.227356425, 
        0.227243374, 0.228936267, 0.227320467, 0.22738371, 0.227694891, 
        0.227270428, 0.227751798, 0.228803279, 0.227330453, 0.229679261, 
        0.228999206, 0.227227604, 0.227247085, 0.227198567, 0.229234921, 
        0.227211613, 0.23007234, 0.226793036, 0.226474338, 0.226654333, 
        0.229964991, 0.22880328, 0.22700099, 0.226640822, 0.227522393, 
        0.227463578, 0.227832692, 0.227293936, 0.230154101, 0.229813709, 
        0.22761097, 0.227445308, 0.228669159, 0.22660539, 0.229017398, 
        0.230421347, 0.227041103, 0.227583471, 0.229547568, 0.22676335, 
        0.226737661, 0.229922588, 0.226907188, 0.227102239, 0.226469073, 
        0.230680908, 0.227763879, 0.226882448, 0.226741993, 0.226693024, 
        0.22671415, 0.226773662, 0.227795194, 0.226983096, 0.226647946, 
        0.226799552, 0.226759218, 0.22692942, 0.226601519, 0.227098192, 
        0.226886889, 0.226959012, 0.226552119, 0.226809761, 0.226786285, 
        0.226709252, 0.226834015, 0.228033943, 0.226693494, 0.22748613, 
        0.227608804, 0.22685023, 0.226586619, 0.227718907, 0.228890098, 
        0.226701909, 0.230919944), heaviest = c(0.316870607, 0.316772978, 
        0.316851707, 0.317017543, 0.316673994, 0.317224709, 0.319234458, 
        0.31861305, 0.319804304, 0.318605816, 0.316930034, 0.31688398, 
        0.316789552, 0.320783976, 0.317094325, 0.31809319, 0.317134565, 
        0.318173976, 0.317213167, 0.317084404, 0.321712205, 0.317128056, 
        0.316866913, 0.3170489, 0.31712423, 0.31684494, 0.319497635, 
        0.316932301, 0.316864646, 0.317279005, 0.316887692, 0.317134437, 
        0.316792589, 0.320894499, 0.319883014, 0.316924639, 0.316575642, 
        0.31686389, 0.316985994, 0.321566256, 0.316683995, 0.320299883, 
        0.317308965, 0.318151948, 0.316479828, 0.319857732, 0.317171909, 
        0.322137849, 0.316526917, 0.316870364, 0.322205784, 0.317055758, 
        0.320329144, 0.318015397, 0.318719989, 0.317910658, 0.317292016, 
        0.321348723, 0.319915048, 0.317160762, 0.318773245, 0.319627925, 
        0.31869767, 0.322422407, 0.32082693, 0.318034899, 0.318760783, 
        0.318325502, 0.320739086, 0.317216142, 0.32284544, 0.319466593, 
        0.318740499, 0.317489944, 0.319064923, 0.322014928, 0.317353897, 
        0.318904583, 0.317931141, 0.323295254, 0.318924712, 0.318965677, 
        0.317700019, 0.31793468, 0.317699508, 0.317168657, 0.318903983, 
        0.317493401, 0.317511406, 0.317483897, 0.31748495, 0.317776804, 
        0.318893431, 0.317663608, 0.316978585, 0.317473467, 0.317500429, 
        0.317144259, 0.317330826, 0.317610353, 0.317881476, 0.31707787, 
        0.317728374, 0.317452137, 0.31938939, 0.317199373, 0.31898747, 
        0.318878952, 0.317987024, 0.318951952, 0.318419561, 0.319568088, 
        0.321165413)), .Names = c("id", "heavy", "heavier", "heaviest"
    ), class = "data.frame", row.names = c(NA, -113L))

2 个答案:

答案 0 :(得分：3)

这样的东西？

df1$season<- 'winter'
df2$season<- 'spring'
df3$season<- 'summer'
df4$season<- 'fall'
df1.m <- melt(df1, id.vars=c('id', 'season'), variable.name='weight', value.name='weight')
df2.m <- melt(df2, id.vars=c('id', 'season'), variable.name='weight', value.name='weight')
df3.m <- melt(df3, id.vars=c('id', 'season'), variable.name='weight', value.name='weight')
df4.m <- melt(df4, id.vars=c('id', 'season'), variable.name='weight', value.name='weight')
df.all <- rbind(df1.m, df2.m, df3.m, df4.m)

ggplot(df.all, aes(x=id, y=weight, fill=weightCat)) + geom_boxplot() + facet_grid(. ~ season)

答案 1 :(得分：3)

## create some data.frames: this results in a list of four dfs
createDF <- quote(data.frame(id=sample(c("NN", "SS"), 100, rep=T),
                             heavy=runif(100),
                             heavier=runif(100),
                             heaviest=runif(100)))
dfs <- lapply(1:4, function(i) eval(createDF))

## join and shape them
library(reshape2)
dat <- do.call(rbind, dfs)
dat$dfid <- paste("df", rep(1:4, times=sapply(dfs, nrow)))
dat <- melt(dat, id.vars=c("id", "dfid"))

ggplot(dat, aes(id, value, group=interaction(variable, id), fill=variable)) +
  geom_boxplot() +
  facet_grid(~dfid)

enter image description here

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