Plotting `ggplot` sorted on specific value - r

I have the below results and I am trying to plot using ggplot the columns using the code below but ordered such that the first ranked plot on the legend will correspond to the highest score (taken from the last row in the data). So for example the plots would be ordered in the following way, which on the legend will look like;
train_auc_9 (result = 0.9939489)
train_auc_6 (result = 0.9870544)
train_auc_3 (result = 0.9699427)
train_auc_8 (result = 0.9662169)
train_auc_7 (result = 0.9662169) etc.
Should I sort the columns based on final row value first to make life easier?
ggplot code:
ggplot(result_train_auc, aes(ID)) +
geom_line(aes(y = train_auc_1, colour = "train_auc_1")) +
geom_line(aes(y = train_auc_2, colour = "train_auc_2")) +
geom_line(aes(y = train_auc_3, colour = "train_auc_3")) +
geom_line(aes(y = train_auc_4, colour = "train_auc_4")) +
geom_line(aes(y = train_auc_5, colour = "train_auc_5")) +
geom_line(aes(y = train_auc_6, colour = "train_auc_5")) +
geom_line(aes(y = train_auc_7, colour = "train_auc_6")) +
geom_line(aes(y = train_auc_8, colour = "train_auc_7")) +
geom_line(aes(y = train_auc_8, colour = "train_auc_8")) +
geom_line(aes(y = train_auc_8, colour = "train_auc_9"))
ggtitle("auc curves") +
labs(y="auc result", x = "rounds") +
theme_bw(base_size = 11, base_family = "")
Final row of the data.
0.9177697
0.9309705
0.9699427
0.9431463
0.9544374
0.9870544
0.9538312
0.9662169
0.9939489
100
data called result_train_auc.
structure(list(train_auc_1 = c(0.8713344, 0.8871179, 0.8928057,
0.8964518, 0.8976864, 0.8995532, 0.9001708, 0.9015733, 0.9022265,
0.9027288, 0.9031676, 0.9036361, 0.9040329, 0.9045184, 0.9048802,
0.9053402, 0.9055032, 0.9056735, 0.9061118, 0.9062926, 0.9064719,
0.9067036, 0.9069563, 0.9071833, 0.9074455, 0.907724, 0.907817,
0.9081296, 0.9082689, 0.9084679, 0.9086163, 0.9087718, 0.9091238,
0.9093731, 0.9095402, 0.909702, 0.909771, 0.9099373, 0.9101334,
0.9103078, 0.9104885, 0.9106456, 0.9107819, 0.9108925, 0.9111391,
0.9112471, 0.9114579, 0.9115598, 0.9116752, 0.9117411, 0.9118367,
0.9120177, 0.9121465, 0.9123075, 0.9125142, 0.9125989, 0.9127896,
0.9128665, 0.9129764, 0.9130837, 0.9132152, 0.9133399, 0.9135001,
0.9136408, 0.9137385, 0.9138751, 0.9139981, 0.9140897, 0.914189,
0.9142859, 0.9144037, 0.9145455, 0.9146629, 0.9147381, 0.9148613,
0.9149902, 0.9150876, 0.9151985, 0.9153009, 0.9154068, 0.915529,
0.9156637, 0.9157626, 0.9158646, 0.915995, 0.9161135, 0.9162173,
0.9163324, 0.91642, 0.9165297, 0.9166981, 0.9168092, 0.9169468,
0.9170768, 0.9171896, 0.9173152, 0.9174244, 0.9175383, 0.9176803,
0.9177697), train_auc_2 = c(0.8870459, 0.9021414, 0.9085472,
0.9114717, 0.9136837, 0.9148831, 0.9160633, 0.916577, 0.9175609,
0.918181, 0.9185195, 0.9189418, 0.919285, 0.9195346, 0.9197795,
0.9201756, 0.9205287, 0.9207205, 0.9208646, 0.9210185, 0.9211867,
0.9213273, 0.9214634, 0.9217073, 0.921851, 0.9220127, 0.9221905,
0.9224531, 0.9227193, 0.9228104, 0.9229566, 0.9231306, 0.9233425,
0.9234565, 0.9235739, 0.9237399, 0.9239113, 0.9240052, 0.9242447,
0.9243938, 0.9245815, 0.9247349, 0.92491, 0.9250047, 0.9251303,
0.9252628, 0.925474, 0.9256335, 0.9257628, 0.9258756, 0.9259525,
0.9260501, 0.9261603, 0.9262516, 0.926404, 0.9264811, 0.9266122,
0.9267074, 0.9268346, 0.9269162, 0.9270102, 0.9271369, 0.9272119,
0.9273092, 0.9274163, 0.9275176, 0.9276396, 0.9277829, 0.9278664,
0.927978, 0.928066, 0.9281753, 0.9283186, 0.928417, 0.9285194,
0.9286077, 0.9286985, 0.9287818, 0.9288713, 0.9289982, 0.9290624,
0.9291517, 0.929267, 0.9293397, 0.9294468, 0.9295616, 0.9296748,
0.9297741, 0.9298962, 0.929982, 0.9300875, 0.9301889, 0.9302799,
0.9303726, 0.9304612, 0.930582, 0.9306869, 0.9307636, 0.9308679,
0.9309705), train_auc_3 = c(0.920364, 0.9396713, 0.9477804, 0.9511932,
0.9533659, 0.9548309, 0.9560987, 0.9569889, 0.9577224, 0.9580906,
0.9585115, 0.9590348, 0.9592664, 0.9596969, 0.9600961, 0.9603775,
0.9605959, 0.9608837, 0.9611088, 0.9612673, 0.9614595, 0.9616898,
0.9618144, 0.961986, 0.9621864, 0.9623498, 0.9624878, 0.9626525,
0.9627835, 0.9628886, 0.9629866, 0.9631557, 0.9632875, 0.9634212,
0.9635417, 0.9636695, 0.9637814, 0.9638905, 0.9639689, 0.9640757,
0.964196, 0.9643034, 0.9644215, 0.9645278, 0.9646416, 0.9647334,
0.9648655, 0.9649719, 0.9650779, 0.9651884, 0.9653068, 0.9654192,
0.9655179, 0.9656188, 0.9657627, 0.965861, 0.9659789, 0.966077,
0.9661733, 0.966301, 0.9664198, 0.9664838, 0.9665656, 0.9666834,
0.9667807, 0.9668807, 0.9669509, 0.9670521, 0.9671343, 0.9672346,
0.967336, 0.9674322, 0.9675225, 0.9676096, 0.9677119, 0.9678031,
0.967893, 0.9679848, 0.9680899, 0.968179, 0.9682643, 0.9683379,
0.9684383, 0.9685187, 0.9686161, 0.9687164, 0.9688037, 0.9688999,
0.9689951, 0.9690893, 0.9691872, 0.9692667, 0.9693624, 0.9694321,
0.9695126, 0.9695981, 0.9696739, 0.9697611, 0.9698583, 0.9699427
), train_auc_4 = c(0.8719551, 0.8896184, 0.8948779, 0.898766,
0.9027315, 0.9049762, 0.9062427, 0.9073199, 0.9081683, 0.9092019,
0.9100824, 0.9109981, 0.9116318, 0.9123474, 0.9131612, 0.9138763,
0.9145007, 0.9152897, 0.9158685, 0.9166697, 0.9172174, 0.9179825,
0.9186526, 0.9193314, 0.9199804, 0.9205763, 0.9212371, 0.921792,
0.9223935, 0.9229936, 0.9234932, 0.9240162, 0.9245426, 0.9250783,
0.9256483, 0.9262044, 0.9267231, 0.9271653, 0.9276435, 0.9280976,
0.9284953, 0.9289266, 0.9293313, 0.9297668, 0.9301079, 0.9305796,
0.9309791, 0.9314001, 0.9317514, 0.932084, 0.9323953, 0.9326925,
0.9330121, 0.933329, 0.9335974, 0.9339083, 0.934189, 0.9344819,
0.934775, 0.9350779, 0.9353696, 0.9356319, 0.9358907, 0.9361598,
0.9364136, 0.936647, 0.9368967, 0.9370801, 0.9373547, 0.9375985,
0.9378257, 0.9380637, 0.9382862, 0.9385131, 0.9387194, 0.9389419,
0.9391624, 0.9393709, 0.939553, 0.9397668, 0.9399806, 0.9401861,
0.9403382, 0.9404968, 0.9406843, 0.9408617, 0.9410371, 0.9412126,
0.9413865, 0.9415654, 0.9417246, 0.9418873, 0.9420531, 0.9422337,
0.9423998, 0.9425335, 0.9426956, 0.9428642, 0.9429921, 0.9431463
), train_auc_5 = c(0.8894875, 0.9047447, 0.9105668, 0.9144695,
0.9172043, 0.9185459, 0.919896, 0.9209646, 0.9220889, 0.9229307,
0.923797, 0.9245408, 0.9252745, 0.9258488, 0.9264725, 0.9270811,
0.927705, 0.9283463, 0.9288456, 0.9293815, 0.9299636, 0.9305526,
0.9311112, 0.9317484, 0.9323305, 0.9328307, 0.9332667, 0.9338263,
0.9343498, 0.9348398, 0.9353667, 0.9358599, 0.9362733, 0.9367398,
0.9371676, 0.9376035, 0.9380137, 0.93843, 0.9388201, 0.9392386,
0.9396649, 0.9400335, 0.940358, 0.940702, 0.9410648, 0.9414072,
0.9417623, 0.9421251, 0.9424502, 0.9428179, 0.9431571, 0.9434742,
0.9438279, 0.9441624, 0.9444683, 0.944784, 0.9450568, 0.9453451,
0.9456379, 0.9459065, 0.9462062, 0.9464493, 0.9467355, 0.9469841,
0.9472465, 0.9475116, 0.9477762, 0.948027, 0.9482639, 0.9485123,
0.9487707, 0.9489929, 0.9492213, 0.9494459, 0.9497089, 0.9499556,
0.9501546, 0.9503753, 0.9505703, 0.9507616, 0.9509694, 0.9511743,
0.9513489, 0.9515396, 0.9517049, 0.9518854, 0.9520863, 0.9522618,
0.9524513, 0.9526601, 0.9528238, 0.9530262, 0.953238, 0.9534353,
0.9535989, 0.9537715, 0.953945, 0.9541034, 0.9542643, 0.9544374
), train_auc_6 = c(0.921898, 0.9414678, 0.9480329, 0.9519876,
0.9548386, 0.9567495, 0.9580347, 0.959306, 0.9603841, 0.9614684,
0.9623793, 0.9630147, 0.9637751, 0.964326, 0.9648042, 0.9653413,
0.9658432, 0.9664368, 0.9670508, 0.9675288, 0.9681021, 0.9685874,
0.969052, 0.9695682, 0.9699854, 0.9704805, 0.9708863, 0.97131,
0.9717166, 0.9721004, 0.9724803, 0.9728962, 0.9732809, 0.9736517,
0.9740503, 0.9744405, 0.974781, 0.9751438, 0.9754958, 0.9758019,
0.9761391, 0.9764902, 0.9768141, 0.9771417, 0.9774458, 0.9777964,
0.9780874, 0.9783719, 0.9786893, 0.9789502, 0.9792233, 0.9794795,
0.979716, 0.9799766, 0.9802053, 0.9804437, 0.9806533, 0.9808698,
0.9810933, 0.9813374, 0.9815627, 0.9817506, 0.9819429, 0.9821263,
0.9823146, 0.9824981, 0.9826867, 0.9828871, 0.9830589, 0.9832092,
0.9833926, 0.983539, 0.983694, 0.9838324, 0.9839557, 0.9841259,
0.9843032, 0.9844521, 0.9845934, 0.9847127, 0.9848563, 0.9849894,
0.9851023, 0.9852643, 0.9853757, 0.9854869, 0.9856046, 0.9857333,
0.9858394, 0.9859424, 0.9860531, 0.9861587, 0.986294, 0.9864175,
0.9865295, 0.9866261, 0.9867294, 0.986843, 0.9869372, 0.9870544
), train_auc_7 = c(0.8714998, 0.8904612, 0.8996561, 0.9041253,
0.9066398, 0.9086743, 0.910345, 0.9116165, 0.9130665, 0.914957,
0.9166201, 0.9180005, 0.9195517, 0.9207296, 0.9218763, 0.9230211,
0.9241087, 0.9252396, 0.9262592, 0.9271692, 0.9280938, 0.9289803,
0.9297884, 0.9305648, 0.9311738, 0.9317921, 0.9323804, 0.9329845,
0.933683, 0.9341942, 0.9347607, 0.9352553, 0.9357764, 0.9363214,
0.9367976, 0.9372965, 0.9377839, 0.9382045, 0.9386436, 0.9391153,
0.939509, 0.9399301, 0.9402878, 0.9405964, 0.9409411, 0.9413296,
0.9416693, 0.9419742, 0.9423106, 0.9426316, 0.9428824, 0.94322,
0.9435017, 0.9438152, 0.9440885, 0.9443691, 0.9446256, 0.9449214,
0.9451091, 0.945326, 0.9456083, 0.9458252, 0.9460603, 0.94633,
0.946581, 0.9468279, 0.9470671, 0.9473089, 0.9474984, 0.9477469,
0.9479721, 0.9482038, 0.9484291, 0.9486507, 0.9488756, 0.9490827,
0.9492949, 0.9494745, 0.9497085, 0.9499118, 0.9501382, 0.9503468,
0.9505637, 0.9507583, 0.9509843, 0.9512342, 0.9514627, 0.9516457,
0.9518377, 0.9520731, 0.9522473, 0.9524432, 0.9526339, 0.9528058,
0.9529749, 0.9531575, 0.9533158, 0.953497, 0.953663, 0.9538312
), train_auc_8 = c(0.8894918, 0.906573, 0.9133049, 0.9168864,
0.9194233, 0.9219299, 0.9237789, 0.9252068, 0.9265656, 0.9281103,
0.929274, 0.9307909, 0.9317895, 0.9328411, 0.933978, 0.9349498,
0.9358906, 0.936782, 0.9376891, 0.9385461, 0.9393091, 0.9401118,
0.940883, 0.941568, 0.9421953, 0.9427495, 0.9434112, 0.9439894,
0.944666, 0.9452999, 0.9457854, 0.9463698, 0.9468706, 0.9473643,
0.947829, 0.9482811, 0.9487576, 0.9492046, 0.9496415, 0.9500149,
0.9504884, 0.9509045, 0.9512969, 0.951719, 0.95214, 0.9525265,
0.9528557, 0.9531854, 0.9535102, 0.9537721, 0.9541137, 0.9544496,
0.9548184, 0.9551027, 0.955434, 0.9557073, 0.955989, 0.9563086,
0.9565974, 0.9569073, 0.9571664, 0.9574366, 0.9577329, 0.9580357,
0.9582985, 0.9585633, 0.9587903, 0.9590735, 0.9593316, 0.9596137,
0.9598677, 0.9600993, 0.9602947, 0.9605253, 0.9607954, 0.9610258,
0.9612257, 0.9614929, 0.9617122, 0.9619397, 0.9622056, 0.9624263,
0.9626628, 0.9628691, 0.9631282, 0.9633603, 0.9635655, 0.9638023,
0.9640161, 0.9642836, 0.9644966, 0.9646435, 0.9648045, 0.964987,
0.9652297, 0.9654192, 0.9655976, 0.9657743, 0.965976, 0.9662169
), train_auc_9 = c(0.9195993, 0.9417172, 0.949147, 0.9537538,
0.9565765, 0.9589093, 0.9607099, 0.962332, 0.9639256, 0.9652906,
0.9664848, 0.9675891, 0.9685598, 0.9695702, 0.9705377, 0.9713772,
0.9722889, 0.9730441, 0.9738743, 0.9745701, 0.9752537, 0.9759395,
0.9765657, 0.9772191, 0.9778215, 0.9783909, 0.9789667, 0.979504,
0.9799884, 0.9804533, 0.9808872, 0.9813206, 0.981738, 0.982081,
0.9824229, 0.9827401, 0.983044, 0.9833385, 0.9836874, 0.9840525,
0.9843545, 0.9845821, 0.984868, 0.985124, 0.9853725, 0.9855741,
0.9857704, 0.9860043, 0.986215, 0.9864325, 0.9865974, 0.9867876,
0.9870471, 0.9872346, 0.987455, 0.9877028, 0.9879157, 0.9880718,
0.9882622, 0.9884967, 0.9886666, 0.9888404, 0.9890087, 0.9891979,
0.9893628, 0.9895276, 0.9896856, 0.989821, 0.9899959, 0.9901792,
0.9903423, 0.9905105, 0.9906635, 0.9908151, 0.99095, 0.991091,
0.9912231, 0.9913755, 0.9914875, 0.9916226, 0.991765, 0.9919017,
0.9920161, 0.9921698, 0.9923023, 0.9924097, 0.9925314, 0.9926483,
0.9927896, 0.992922, 0.9930381, 0.9931279, 0.9932223, 0.9933255,
0.9934563, 0.99354, 0.9936327, 0.9937486, 0.9938403, 0.9939489
), ID = 1:100), .Names = c("train_auc_1", "train_auc_2", "train_auc_3",
"train_auc_4", "train_auc_5", "train_auc_6", "train_auc_7", "train_auc_8",
"train_auc_9", "ID"), row.names = c(NA, -100L), class = "data.frame")
EDIT: Added a picture for clarification.


Here is a way to do it. Notice that I reshape the data to use full power of plotting aesthetics:
library(tidyr)
library(ggplot2)
# reshape the data
df %>%
gather(trainauc, value, -ID) -> df
# get the order
df %>%
filter(ID == 100) %>%
arrange(desc(value)) %>%
.$trainauc -> leg_order
# plot
ggplot(df, aes(ID)) +
geom_line(aes(y = value, colour = trainauc)) +
scale_colour_discrete(breaks = leg_order) +
labs(title = "auc curves", y = "auc result", x = "rounds") +
theme_bw(base_size = 11, base_family = "") +

Related

ggplot2 order by rownames with heatmap

Question:
Below can find the data, codes, and output. How can I get the plot sorted according to the original order in the row names, instead of the alphabetic order?
Note: I understand there are many existing questions and answers saying we can use as. character() and specify the orders in factor levels. However, the codes for the heatmap are a result of StackOverflow help, and I don't know how to follow those guidances to modify the codes.
Data:
data <- structure(c(1.56415665339664, 1.88622232430646, 2.7670527911374,
1.92703163268293, 1.92815958820144, 1.53777698134781, 1.85785080937573,
2.73057928043023, 1.91265151742415, 1.91392443413493, 1.51188863842245,
1.82978143286307, 2.69398442644669, 1.89813137541848, 1.89955330864784,
1.48650974337831, 1.80204149133308, 2.65731564638771, 1.88348256348151,
1.8850572392635, 1.46165563934645, 1.77465595548961, 2.62061921610674,
1.86871647260771, 1.87044727645794, 1.4373390243787, 1.74764749626653,
2.58394008473444, 1.85384450032525, 1.85573446770023, 1.41357009067807,
1.72103652543546, 2.5473217079521, 1.83887802369739, 1.84092983214118,
1.39035667008188, 1.69484124901252, 2.51080590056645, 1.82382837308096,
1.82604433604935, 1.36770438358188, 1.66907773176055, 2.47443270873259,
1.80870680674341, 1.81108886908555, 1.34561679288903, 1.64375997112343,
2.4382403018842, 1.79352448643103, 1.79607422149822, 1.3240955522757,
1.61889997899129, 2.40226488416451, 1.77829245397141, 1.78101106231344,
1.30314055915218, 1.59450786977524, 2.36654062491116, 1.76302160898326,
1.7659099185843, 1.28275010205015, 1.57059195336362, 2.33109960753632,
1.74772268775752, 1.7507811557552, 1.26292100489292, 1.54715883163515,
2.29597179596148, 1.73240624336288, 1.73563495918782, 1.24364876662612,
1.52421349731482, 2.26118501761437, 1.71708262702006, 1.72048131688628,
1.22492769546226, 1.50175943407199, 2.22676496187464, 1.70176197077873,
1.70533000345043, 1.20675103715734, 1.47979871687523, 2.19273519276265,
1.68645417152199, 1.69019056527759, 1.18911109688617, 1.45833211173251,
2.15911717460239, 1.67116887631423, 1.67507230702478, 1.17199935441569,
1.43735917405612, 2.12593030935165, 1.65591546909929, 1.65998427933569,
1.15540657239252, 1.41687834499844, 2.09319198427861, 1.64070305874773,
1.6449352678292, 1.13932289766278, 1.39688704520578, 2.06091762867183,
1.6255404684443, 1.62993378333913, 1.12373795562949, 1.37738176553192,
2.02912077829616, 1.6104362263992, 1.61498805338851, 1.10864093772681,
1.35835815434096, 1.99781314634913, 1.5953985578604, 1.60010601487567,
1.09402068215196, 1.33981110110915, 1.96700469972745, 1.58043537839775,
1.58529530794391, 1.07986574804581, 1.32173481610856, 1.93670373947838,
1.56555428842454, 1.57056327100153, 1.06616448335306, 1.30412290602036,
1.90691698438448, 1.55076256891683, 1.55591693685494, 1.05290508662397,
1.28696844538424, 1.87764965670914, 1.53606717828693, 1.54136302991323,
1.04007566304237, 1.27026404384093, 1.84890556921326, 1.52147475036339,
1.52690796441975, 1.02766427498045, 1.25400190916953, 1.82068721263795,
1.50699159342693, 1.51255784366333, 1.01565898739092, 1.23817390615927,
1.79299584293262, 1.49262369024903, 1.49831846011925, 1.0040479083513,
1.22277161138752, 1.76583156759166, 1.47837669907795, 1.48419529646884,
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1.16524369529089, 1.66241206053094, 1.42269978906386, 1.42896377616518,
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1.41549328031103, 0.942007524719625, 1.13880169017355, 1.61379715369429,
1.39571051700261, 1.40216554912609, 0.932833116212497, 1.12612900591028,
1.59024634304597, 1.38244167262157, 1.38898398786489, 0.923962843515001,
1.11380958437724, 1.56719183657471, 1.36932770881932, 1.37595172535787,
0.915386378581994, 1.10183426022178, 1.54462692599157, 1.35637153532236,
1.3630716205394, 0.907093641174831, 1.09019393194762, 1.52254448146634,
1.34357578664111, 1.35034626933109, 0.899074805097146, 1.07887958114475,
1.50093700627199, 1.33094282970668, 1.33777801183386, 0.89132030273522,
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1.29404053293171, 1.30103552339406, 0.869551054721558, 1.03670538800144,
1.41909679318253, 1.28207734256312, 1.28911419066604, 0.862763461210944,
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1.27566249504498, 1.19257743610158, 1.1997487371841, 0.815758629792936,
0.957587283315014, 1.25945945858363, 1.18216953683933, 1.18933348544938,
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1.17908564604669, 0.805775023052616, 0.942552236185361, 1.22810791295855,
1.1618706821728, 1.16900467607732, 0.801013384459458, 0.935340532491705,
1.21294234895183, 1.15197832707131, 1.15908990390117, 0.796397594302229,
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0.775322836401382, 0.895967346034515, 1.12857358277151, 1.09616012019459,
1.10303940177539, 0.771474662022726, 0.89000174390193, 1.11554263939148,
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1.10278600069095, 1.07887022447868, 1.08563740651938, 0.764109350129453,
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1.05412698649671, 1.06069660698705, 0.753828691536061, 0.862422524307139,
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0.735674754410845, 0.833687079792661, 0.988802891064574, 1.00169924608359,
1.00768663713703, 0.732923935338581, 0.829304145550759, 0.978624023348409,
0.994787369801221, 1.00067938395813, 0.730244003477527, 0.82502771879015,
0.968643665843796, 0.988013815799624, 0.993807733054007, 0.727632338342786,
0.820854469794238, 0.958856511298594, 0.981376492887521, 0.987069700023661,
0.725086419474772, 0.816781178550003, 0.949257397865192, 0.974873298102964,
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0.968502119815104, 0.973986486183567, 0.72018221570783, 0.808922117204624,
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0.665168203935704, 0.796150328920716, 0.796234064228217, 0.653683506694951,
0.703929279389845, 0.66036110932326, 0.793574374358407, 0.793517898118688,
0.652537193557989, 0.702232810498201, 0.655615894359165, 0.791054108219602,
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0.643778669888508, 0.689539715446396, 0.619722717150336, 0.772753135566687,
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0.594966695694488, 0.760967019339396, 0.758834559291943, 0.636607466772238,
0.67953970625735, 0.591002408513372, 0.759146546039657, 0.75687813555014,
0.635613405472859, 0.678183674860939, 0.587081790383065, 0.757364700448588,
0.754960702215028, 0.634626079518729, 0.67684432070982, 0.583203947327774,
0.755620597087154, 0.753081380305464, 0.633645224839319, 0.675521191782987,
0.579368009167761, 0.75391336968409, 0.751239309380749, 0.632670586179664,
0.674213848720291, 0.575573128819215, 0.752242170829969, 0.749433647221233,
0.631701916797938, 0.672921864424234, 0.571818481616423, 0.750606171632756,
0.747663569509711, 0.630738978174469, 0.671644823675892, 0.568103264655477,
0.749004561375194, 0.745928269513948, 0.629781539731715, 0.67038232276441,
0.564426696158795, 0.747436547174325, 0.74422695777065, 0.62882937856474,
0.66913396912956, 0.560788014859765, 0.745901353643456, 0.742558861771208,
0.627882279181762, 0.667899381016863, 0.557186479406819, 0.74439822255683,
0.740923225649459, 0.626940033254362, 0.666678187144791, 0.553621367786292,
0.742926412517243, 0.73931930987174, 0.626002439376954, 0.665470026383597,
0.550091976763438, 0.741485198626834, 0.737746390929453, 0.62506930283514,
0.664274547445332, 0.54659762134097, 0.740073872161253, 0.736203761034359
), dim = c(5L, 151L), dimnames = list(c("highest_pi_count", "second_pi_count",
"highest_si_count", "max_overhangz_minus", "max_overhangz_plus"
), NULL))
Codes:
library(latticeExtra)
library(ggplot2)
library(tidyverse)
rownames(data)
as.data.frame(data) |>
rownames_to_column() %>%
pivot_longer(-rowname) %>%
ggplot(aes(factor(name, unique(name)), rowname, fill = value)) +
scale_x_discrete(labels = ~., breaks = ~ c(6:29/10)) + ggtitle("Title") + theme(plot.title = element_text(hjust = 0.5)) +
geom_tile() +
scale_fill_gradientn(colours = c("blue4", "white", "red3")) +
scale_y_discrete(position = "right") +
theme(legend.position = "none",
axis.ticks = element_blank(),
axis.title = element_blank(),
text = element_text(face = 2))
Output:
> rownames(data)
[1] "highest_pi_count" "second_pi_count" "highest_si_count" "max_overhangz_minus" "max_overhangz_plus"

To fix your issue convert row name to factor with the order of the levels set according to the row names of your original dataset:
as.data.frame(data) |>
rownames_to_column() |>
pivot_longer(-rowname) |>
mutate(rowname = factor(rowname, rownames(data))) |>
ggplot(aes(factor(name, unique(name)), rowname, fill = value)) +
scale_x_discrete(labels = ~., breaks = ~ c(6:29 / 10)) +
ggtitle("Title") +
theme(plot.title = element_text(hjust = 0.5)) +
geom_tile() +
scale_fill_gradientn(colours = c("blue4", "white", "red3")) +
scale_y_discrete(position = "right") +
theme(
legend.position = "none",
axis.ticks = element_blank(),
axis.title = element_blank(),
text = element_text(face = 2)
)

factoextra variable plotting and labeling subset

I've run a PCA using prcomp in R and I am trying to produce a variable plot that has 1) a subset of the variables (arrows) in a different color (black) than the rest of the variables, 2) sort those variables prior to plotting so the black arrows aren't covered up by any of the other arrows, and 3) label the black arrows with their TUXXXX number.
Here is a truncated version of my data:
structure(list(sdev = c(21.7106794138444, 15.6885074594869, 11.9124316528111,
10.155277241318, 9.31528828036412, 7.56876266263865, 7.19938201515987,
5.81620977435434, 5.00785424840699, 4.57228787327195, 4.51525494575488,
3.20601607034873, 2.91477640215067, 2.48737967730048, 2.13230488376163,
1.74923754200417, 1.32745772948038, 1.27373216417502, 0.924437474777366,
0.749074623004602, 2.499709597053e-15), rotation = structure(c(-0.0710441966458092,
0.091894514828866, -0.0892433537986534, -0.269473709517009, -0.270455466278075,
0.217492458575054, 0.104541973199297, 0.198858094257877, 0.0222680112919805,
-0.220704163347643, -0.0144913885562279, 0.191255085890651, -0.0639203495167002,
0.156262929972648, 0.184067836594737, -0.221797618857792, 0.152932751853774,
0.218733634550932, 0.213989867048259, -0.219209176045661, 0.162232843055052,
-0.182649403408074, 0.0732706002149817, -0.0636694683826245,
0.197950156891487, -0.201332798849071, -0.0908133550739104, 0.204561640782066,
0.144543461720936, 0.128722984809536, 0.152014925749702, -0.219186163224382,
0.137427869376807, -0.0385728465064452, -0.210836096156869, 0.295086522896984,
0.0791956927556792, 0.154250304318938, 0.212537035577304, 0.165554637810987,
0.0559168852882808, 0.0389301896007549, 8.50109782205011e-06,
0.0386719091643949, -0.223181316780788, 0.0201295766763838, -0.0993945550528442,
-0.0797657364873552, 0.290392094157839, -0.210104310439075, 0.190507620860241,
0.288216604566037, -0.128091623622577, 0.0523741236254804, 0.165286635170839,
0.26567738477018, 0.067304658063138, -0.185395359345644, -0.0824392053628523,
0.0232331903282599, 0.206712718290849, -0.0599454190622519, 0.0694655529225049,
0.27934713843206, 0.120105146108152, 0.276987279291797, 0.137068573563571,
0.290227550805898, 0.0299855300238849, -0.048045392789825, 0.217209812823655,
-0.245207498414819, -0.0969050397538762, 0.0152958298727508,
0.0611874790392221, 0.244015616675892, -0.341439467152496, -0.0574074669754257,
-0.187473105527714, 0.0859725296785313, -0.230526618631008, 0.164238788534203,
-0.422116092865793, -0.0847447867791298, 0.0984005915083912,
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-13.8464231033084, -6.95076374785849, 5.03179685038719, 16.6482451825695,
25.4557137741208, -6.16437895161065, -0.188023057317339, 3.51919999146276,
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9.91999265542052, -6.2673275997563, -6.19445525060979, -4.89432563084305,
13.3155996092707, -17.5672684031691, -11.0570104414685, -10.1512940397755,
-2.83422832939901, 11.2933772476208, 18.438427176494, -10.6101681685668,
2.08048057352476, 5.50745324586983, -0.13719717270706, -8.9884667602456,
-2.05928444313446, -0.305773393272364, 4.86554463593651, 3.76285186780856,
6.3828926870771, -9.3655246100571, 7.43651870615979, -1.67082019758757,
10.9895599029683, -13.9919213196391, -7.47010213808747, -5.18316808251628,
3.09935494483666, 0.0636557688816208, -1.54858827353552, 5.76445544260896,
-7.0244817763404, -6.91485718432494, 6.12343812013661, 16.0347161023267,
-6.04452306419056, 0.503323158087318, 1.11905480618314, -3.32310396567328,
3.1274151532053, -1.0139189902977, -2.77210893619864, 5.73300675328722,
-2.20016077060467, 6.88733384115661, 9.29615931028018, 7.89283806484175,
-0.0231784873612931, -13.6472361241707, 8.57047305874539, 9.82836851225084,
-12.0042402273719, -9.50514572716062, -7.91330903314343, 8.52172081325052,
-3.03276814511544, -8.49580406093405, -2.33842120098311, -0.32804627167184,
-3.21259723306479, 11.1229701308803, 0.598883041283415, 5.30460923308376,
1.00174438392002, -1.97289932239362, -10.2991918599681, -3.87835358264123,
-2.25659286308468, -0.166946108131337, -4.78949081440092, 3.19183354598423,
4.8383258847991, 0.890821633270318, 14.2375666218091, -6.1498396420083,
0.00274092818159516, 2.69868755607018, -6.72994548395586, -2.87563409646143,
6.39162216555694, -1.86430696261611, 1.49349337044142, -0.729377873822674,
3.91976580406387, -4.55169784656593, 4.01470477896383, 9.45815735561592,
3.87143750044459, 2.8485319829077, -3.54554995799273, 2.1592779575771,
-10.2265407210419, -2.57734842434015, 3.85728531842232, 3.91861430861892,
-6.08938026261039, 2.90775931244037, -5.65086822564584, -7.43442226552497,
-0.28834246695089, 4.46777893840091, 1.61867182502613, -1.24379496084697,
3.09330484415506, 4.6129428255061, 4.21327794340158, -2.73480960596815,
-1.34501116390485, -4.95417459779772, -1.50853746838879, 4.27315750243976,
5.82184171959861, -3.417633941994, 9.09574374372561, -2.51371486672449,
-5.3839624715871, 4.02549123440248, -4.25205519103745, -6.14575157593085,
3.39653326861517, 2.02195972923006, 0.737129651195039, -3.82060608464456,
-5.8916049884138, -1.48103866101421, -4.15462594283813, 2.85762680978641,
8.01848063520863, -0.33318325779775, -4.11692676832453, -3.14609004733945,
-3.87716607273847, 2.15863837910027, 5.89633795035078, 6.78408908767204,
5.31335299395838, 2.26271596099398, -6.04004269690954, 0.66943773718038,
-7.25501768327073, -1.85352333808763, 0.881321761644734, -3.37300816578494,
1.72336449307423, -1.12738959732561, -1.00315691989581, 1.22856047955961,
-5.49078567616185, 7.36566150881169, 1.5098504796481, -4.40047569826546,
1.27392003732061, -1.32431052177641, -3.49056795319117, -1.81317399652518,
4.21470358856118, -3.35477920804357, 0.76847614798403, 4.53289945581295,
1.08860795433414, 2.64380516830634, -3.5282442958868, 0.44695028657078,
6.40236529107031, 1.40990912221294, -0.646731159533322, -0.886819655598922,
-0.75355529529178, -3.22681748481868, 1.14443040171423, -1.01721629940821,
-1.91406441412825, 2.79795257160194, 1.42125707801834, -3.78513731974819,
5.22015934186783, -3.11038146921718, 4.2502371748613, -2.23573426796635,
1.2890326250481, -3.2044887828359, -0.0731034485321765, 1.00689042463065,
3.10770789167095, 0.653717111815948, 2.0046773828616, -5.05502285926648,
0.670269628945531, -0.0735066911646989, 0.567378074513561, -4.12216401435608,
-1.34361612453716, -2.31031886740573, 4.81653041064168, 0.0225272846463933,
-2.29390683891735, -3.34883149458521, 1.62567523985947, 1.46413728406672,
2.19861127383831, -2.2813563892377, 1.48246659900362, 1.20813467297598,
4.19016124903691, -3.8965814643401, 3.56184752348759, -1.3878373295987,
1.21458977444305, -0.654562661488364, 0.95632241225039, -1.55232118983605,
-2.44238882925152, 1.13264815277383, -1.78862294430386, 0.991256365490394,
-3.88951966260596, 0.202107196565979, 0.551090451321218, 2.66348016156913,
-0.854309938495967, -0.232716071672556, 0.851674118269924, -0.985653498045505,
1.36933618443016, -0.586856938122795, -4.1119301713715, 1.0178280457984,
0.338189042904915, -3.94726389810293, 1.81377558126379, 1.58372328030388,
1.72308989346244, 2.19193280022478, -1.61256462530986, 1.96795000825428,
-0.618527965915178, 0.0756192601567935, -0.659358025397941, 0.0429550715360451,
-0.381324238450748, -0.652905276182954, 0.170764900323459, -0.641706794178386,
-0.0221222785810836, 2.30873232738461, 1.27649223277723, 0.0239704300112933,
1.61258498499148, -2.05589657580369, 0.0265571467877399, 1.25029287962319,
-0.571431828720408, -1.73619374916576, -0.0382088144200337, -0.321239936961026,
-0.611330806517872, -2.02090803294801, 3.14396363436869, -1.10262030332252,
-1.04168768271449, 0.37429480503427, 0.104514606536275, -0.478767952336214,
-0.192546893385304, 2.1627661920923, 0.195395664072845, -0.782469508379251,
2.08546244595102, -0.0517755897340584, -2.39907743930418, -0.211807017194547,
1.71381905614487, 0.83072521628824, -1.60469551897193, 0.245800797687136,
-1.46819802906202, 0.849407708022543, 0.917523253251796, -1.60319562494994,
1.89391093257302, 0.378604048008997, 0.14292959825461, -0.126413703865446,
-1.54645185235878, -0.749700454486876, -0.0658077625468692, 1.55140944467166,
0.302322289091245, 0.458890126236888, -0.788003883776506, -1.8522098865949,
-0.303600234099745, -0.869244048674518, 2.09285131170145, 1.13594169034256,
0.00257581110260907, 1.28821287823238, -0.603719944771219, -0.0929817189825319,
0.646083878133434, -0.997976432253114, -0.0887921104756663, -0.252335674196718,
0.885171983511843, -0.455664633944459, -0.080944547822266, -1.11153038212543,
0.684953529364659, 0.00107091275654292, -0.0523472212020604,
-0.722665903230519, 0.112695429436832, -0.431332703576418, 2.28632079906497,
0.389976510624337, -0.672770348738164, -0.710872748519771, 1.11097033239239,
-0.117525841496901, -0.38659967304807, -0.311519238694312, -0.58769206070627,
0.880912821150173, -0.223180949008615, -0.0563287542495416, 0.677577799103385,
0.174786309548343, -0.486054451272286, -0.875421020334039, -1.99840144432528e-15,
-2.19269047363468e-15, -2.80331313717852e-15, 3.39658856596259e-15,
4.44089209850063e-16, 4.44089209850063e-16, -2.44249065417534e-15,
1.11022302462516e-15, -6.66133814775094e-16, -4.44089209850063e-15,
-3.5527136788005e-15, -2.33146835171283e-15, -6.43929354282591e-15,
2.44249065417534e-15, -1.4432899320127e-15, -2.19269047363468e-15,
1.0547118733939e-15, -1.11022302462516e-15, -9.99200722162641e-16,
1.33226762955019e-15, -1.55431223447522e-15), .Dim = c(21L, 21L
), .Dimnames = list(c("EDA_01", "EDA_02", "EDA_03", "EDA_04",
"EDA_05", "EDA_06", "EDA_07", "EDA_08", "EDA_09", "NDA_01", "NDA_02",
"NDA_03", "NDA_04", "NDA_05", "NDA_06", "NDA_08", "NDA_09", "NDA_10",
"NDA_11", "NDA_12", "NDA_13"), c("PC1", "PC2", "PC3", "PC4",
"PC5", "PC6", "PC7", "PC8", "PC9", "PC10", "PC11", "PC12", "PC13",
"PC14", "PC15", "PC16", "PC17", "PC18", "PC19", "PC20", "PC21"
)))), class = "prcomp")
Here is the minimal code to reproduce this problem:
library(factoextra)
library(tidyverse)
# create a named factor for coding the coloration of the variables in the plot
markers <- facto_summarize(pca,
element = "var",
result = "contrib",
axes = c(1, 2)) %>%
mutate(candidate = ifelse(name == "TU35976" | name == "TU18317" | name == "TU12311" | name == "TU3565" | name == "TU9890" | name == "TU18316", "1", "0")) %>%
select(name, candidate)
markers_vec <- as.factor(markers$candidate)
names(markers_vec) <- markers$name
(var_cluster_PC12 <- fviz_pca_var(pca,
col.var = markers_vec,
axes = c(1,2),
select.var = list(contrib = 200),
palette = c(
"grey90",
"black"),
label = "none",
) +
theme_bw()
)
Which produces this plot:
This image doesn't quite do it justice, so here is a plot of the full data set that shows how bad the overlap is:

Probably the simplest method, given your particular colour scheme, is to make the arrows all black but use the alpha channel to make the gray ones gray. This means the black arrows will still be completely black even if other arrows are drawn over the top:
fviz_pca_var(pca,
axes = c(1,2),
select.var = list(contrib = 200),
alpha.var = ifelse(markers_vec == 0, 0.2, 1),
label = "none") +
theme_bw()

How to color scatter plot points based on temporal sequence

I have a dataframe with observations of a temporal event. I can easily plot the observations based on their Xand Y values, either in base R or ggplot2:
plot(df$Y ~ df$X)
ggplot(df, aes(x=X, y=Y)) +
geom_point()
What I'd like to do though is add in the temporal dimension by coloring the observations differently depending on the time they were made. This could be done by defining thresholds for different time steps and assigning discrete colors to each time step. But what I'm interested in is a continuous coloring where the flow of time can be directly read off the flow of colors or color hues or color transparencies. Any help is greatly appreciated.
Reproducible data (slightly shorter than data underlying shown graphs):
structure(list(X = c(171.000358830368, 171.453956550099, 171.075127685269,
171.140924277581, 171.271520544141, 171.582558980529, 171.23762532992,
171.70218914837, 171.318375693213, 170.939546828382, 171.70218914837,
171.779948757467, 171.809856299427, 172.066064242221, 171.603494259901,
171.718139837416, 171.947430992445, 171.930483385334, 172.002261486039,
172.153793031971, 122.654817251517, 171.710164492893, 172.012230666692,
171.395138384244, 171.750041215507, 171.631407965731, 171.927492631138,
172.059085815763, 171.816834725885, 170.787018364384, 170.328436054326,
170.083194210252, 170.405198745358, 170.505887469957, 170.429124778926,
171.187779426653, 171.00634033876, 170.984408141322, 170.731190952725,
170.924593057402, 170.570687144205, 170.751129314032, 170.539782684179,
170.561714881617, 170.461026157017, 170.631499146191, 170.686329639785,
170.863781055416, 170.782033774058, 170.655425179759, 170.645455999106,
170.612557702949, 170.658415933955, 170.514859732545, 170.382269629855,
170.167932245806, 170.187870607113, 169.841940038438, 175.365863038509,
190.973612269532, 206.626222813496, 214.924568789419, 214.509850874236,
211.538038121446, 209.610995501136, 207.007045514458, 204.585531533737,
202.489012842319, 200.693563406635, 199.331773329375, 198.61997383072,
198.494362154486, 202.238786407918, 205.8695620019, 206.616253632843,
207.53541208909, 208.81146721273, 209.850255836818, 210.903998231887,
211.630751501523, 211.825150524265, 211.487195300113, 210.759445112412,
209.407624215806, 207.816542983517, 205.843642132201, 203.585622714198,
201.110275157949, 198.862224920598, 196.914247020916, 195.676074783759,
195.283289066014, 196.015026925976, 197.60710507633, 200.479226022586,
204.110001616568, 207.405812740595, 210.878078362188, 214.015379513825,
216.768867210305, 218.423751198776, 219.404718575074, 219.467524413191,
218.760709504862, 217.317172146244, 215.572565531892, 213.46408382369,
211.338654508377, 209.181323814973, 207.720838849244, 206.537497105681,
205.904454134187, 205.898472625795, 205.953303119389, 206.365030280376,
206.977137972497, 208.319986606516, 209.067675155523, 209.547192744954,
210.106463779612, 210.356690214013, 210.602928976153, 210.692651602034,
210.849167738293, 210.88405987058, 210.998705448095, 211.037585252643,
210.902004395756, 210.895025969299, 210.958828725481, 210.92692734739,
210.975776332592, 211.201079815359, 211.164193846942, 211.304759294155,
210.646793371028, 198.816366689593, 179.579835700717, 164.568243472769,
159.956500502489, 159.636489803513, 159.535801078913, 159.997374143168,
160.238628314981, 160.281495791791, 160.576583539133, 160.637395541118,
156.724492134644, 153.810500629644, 153.846389679996, 154.022844177562,
154.29300897327, 154.442546683072, 154.536256981214, 154.665856329709,
154.665856329709, 154.833338564686, 156.847113056681, 176.676810294436,
177.112463488991, 176.71868085318, 176.042770404877, 175.822451512436,
175.75964567432, 176.817375741649, 176.028813551962, 176.347827332872,
176.622976718907, 182.215687065486, 118.910392998086, 174.380907989949,
171.889609744655, 168.855988071813, 164.924143222097, 160.275514283399,
156.671655477181, 154.165403460906, 107.676123319726, 107.769833617868,
108.581324923058, 109.676937876871, 109.244275436511, 110.393721965853,
161.248506315174, 163.97707106002, 165.507340290323, 166.298893234206,
168.008607716271, 169.06434394747, 170.018394536004, 170.41118025375,
170.202824378093, 170.201827460028, 121.025853132745, 117.483803246579,
120.870333914552, 166.984772863163, 166.489304584687, 168.118268703459,
181.382263562859, 196.653054487796, 135.095357788943, 135.297732156208,
202.44614536551, 203.460011037964, 204.440978414263, 205.227546767819,
205.43490572541, 204.935449774673, 203.891676560258, 202.264706277617,
199.827241607851, 176.081650209426, 194.729002621683, 194.670184455827,
191.186952735516, 190.463190220076, 190.508051533017, 191.482040482858,
186.606114225261, 171.208714706025, 158.889798172571, 149.82880987666,
152.986049389604, 156.597883540345, 159.647455902232, 161.754940692369,
162.893421122992, 114.542894953814, 162.976165322415, 114.268742485845,
160.762010299286, 159.259654774813, 157.995562667957, 156.561994489993,
155.638848361484, 154.469463470836, 154.00390273432, 154.431580584353,
154.255126086787, 155.244068807608, 157.058459686534, 159.101144802424,
161.906472238301, 165.29399982434, 120.406767014167, 172.028181355737,
175.03588315888, 177.740521870158, 179.910812498411, 181.483949205524,
181.988389746588, 181.854802725832, 180.508963337618, 178.901931416283,
176.58609075049, 173.537515306668, 170.679351213327, 167.374567826712,
164.487493109477, 162.203553821774, 160.569605112675, 159.562717866678,
159.828894990125, 159.632502131252, 160.2495944137, 161.450880682439,
162.705003608642, 164.622077048298, 166.212161362521, 167.468278124855,
168.602770883216, 169.155063491416, 169.462114255542, 169.404293007752,
169.003531945484, 168.422328713389, 167.728473739909, 166.825265972708,
165.984864043623, 169.386348482576, 183.504702123976, 200.99862033463,
214.553715269111, 218.552353629205, 217.590327696148, 217.000152201465,
216.115885877505, 215.405083296914, 214.675339273083, 214.063231580962,
213.56477254829, 212.972603217475, 212.488101037718, 212.097309156103,
211.685581995116, 211.786270719716, 211.46426618461, 210.97178866033,
210.657759469747, 210.36167480434, 210.032691842776, 209.635918452769,
209.435537921635, 209.197274504018, 209.046739876151, 208.712772324261,
208.585166811897, 208.3319496233, 203.956476234505, 189.73444311431,
179.21097601654, 176.815381905519, 177.826256823777, 175.90718954799,
175.461567172782, 177.582011897768, 177.488301599626, 177.463378647992,
177.577027307441, 177.676719113976, 177.633851637166, 177.843204430888,
177.995732894886, 177.92196095805, 176.699739409939, 176.824354168107,
176.859246300394, 176.68877331122, 175.325986315895, 176.695751737677,
174.103764767783, 176.520294158177, 178.304777495142, 176.684785638959,
176.697745573808, 177.861148956064, 176.614004456319, 176.121526932039,
176.364774939983, 173.25239673998, 176.064702602315, 174.207444246579,
174.133672309744, 173.831606135945, 174.066878799366, 174.03597433934,
175.830426856959, 174.100774013587, 174.019026732229, 173.965193156701,
173.955223976047, 174.028995912883, 173.886436629538, 174.420784712563,
179.872929611928, 198.741597834692, 208.031877285631, 208.418681494985,
208.232257816765, 247.112062365176, 207.772678588642, 207.722832685375,
207.639091567886, 207.613171698187, 207.569307303312, 207.722832685375,
207.850438197739, 208.002966661736, 208.157488961865, 208.43463218403,
208.722741504914, 209.112536468464, 209.628940026312, 210.13038981318,
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You could do:
library(ggplot2)
ggplot(df, aes(x = X, y = Y, color = starttime_ms)) +
geom_point() +
scale_color_gradientn(colors = c("red", "gold", "forestgreen"), name = "time")
An alternative that might help keep track of the motion better would be to use geom_segment:
df$X2 <- dplyr::lag(df$X)
df$Y2 <- dplyr::lag(df$Y)
ggplot(df, aes(x = X, y = Y, color = starttime_ms)) +
geom_segment(aes(xend = X2, yend = Y2), size = 1) +
scale_color_gradientn(colors = c("red", "gold", "forestgreen"), name = "time")

Stratigraphic plot of geochemical data using ggplot2 and tidypaleo

I am trying to create a stratigraphic plot of geochemical element data which should be possible using package tidypaleo.
I want multiple plots of the different element data with Depth (cm) downcore set as the y axis. The data look as follows.
Image of data
I am using this code:
ggplot(wapITRAX, aes(x =BrTi , y = wapITRAX$Depth))+
labs(y = "Depth (cm)")+
geom_lineh()+
theme_classic()+
scale_y_reverse()
However, this only plots one element and I am trying to achieve a plot like this Image of plot
> dput(head(wapITRAX))
structure(list(Depth = 0:5, IncCoh = c(6.049230907, 5.975282432,
5.736199822, 5.658584418, 5.659008377, 5.597103404), BrTi =
c(50.50197628,
22.09236453, 23.48370927, 18.62638581, 14.36924414, 17.48777896
), AlIncCOh = c(16.69633736, 8.200449193, 23.70907643, 20.32310407,
28.62692352, 26.44224866), BrCl = c(8.04090623, 4.306048968,
3.417836951, 3.156895904, 2.787628518, 2.059316731), FeTi =
c(332.715415,
235.9371921, 372.726817, 390.7871397, 396.986099, 495.2624867
), CaTi = c(4.071146245, 3.27955665, 4.395989975, 3.677383592,
3.028670721, 4.523910733), ZrRb = structure(c(363L, 447L, 407L,
395L, 450L, 410L), .Label = c("#DIV/0!", "0.447638604",
"0.478169284",
"0.54554134", "0.548501778", "0.561420163", "0.579454254",
"0.579498861",
"0.580801291", "0.589758019", "0.590194076", "0.590277778",
"0.591357754",
"0.592870544", "0.593851133", "0.598519653", "0.599931082",
"0.600979737",
"0.601426307", "0.611710677", "0.617065868", "0.618499405",
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"2.007683864",
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"2.163963964", "2.25951087", "2.261603376", "2.329896907",
"2.402555911", "2.414500684",
"2.444075305", "2.450268817", "2.484520124", "2.51119403",
"2.515064562",
"2.526086957", "2.554", "2.609715243", "2.61965812", "2.643854749",
"2.704166667", "2.883275261", "3.013186813", "3.02739726",
"3.206896552",
"3.320930233", "3.411627907", "3.688931298", "3.709677419",
"3.748267898",
"3.878865979", "3.936440678", "3.994230769", "33.15909091",
"4.095854922",
"4.29330254", "4.390957447", "4.514634146", "4.6367713",
"4.847665848",
"5.284023669", "5.387755102", "6.171339564", "6.183908046",
"6.36121673",
"6.847826087", "7.003496503", "7.193220339", "8.160550459",
"8.751879699"
), class = "factor"), MnFe = c(0.012176723, 0.010329834,
0.009460859,
0.004488071, 0.0033725, 0.003435313), MnIncCoh = c(169.4430276,
331.1977339, 490.5686845, 279.5752228, 272.3091921, 286.0408118
), CuRb = c(0.392971246, 1.484304933, 0.735426009, 0.491651206,
1.142857143, 0.4345898)), row.names = c(NA, 6L), class =
"data.frame")

Using your posted data. This should approximate the desired design.
First step, Transform the data from a wide format to a long format using the pivot_longer function from tidyr.
Then plot the data using "depth" as the independent variable and the parameters' values as the dependent variables.
Then use facet_wrap() to separate the plots. coord_flip() will make the independent variable (Depth) appear on the y-axis.
#fixed 1 column of data.
originaldata$ZrRb <- as.numeric(as.character(originaldata$ZrRb))
library(tidyr)
#Make wide
wapITRAX<-pivot_longer(originaldata, -1, names_to="parameter", values_to = "value")
library(ggplot2)
ggplot(wapITRAX, aes(x = Depth , y = value))+
labs(x = "Depth (cm)")+
geom_line() +
theme_classic() +
coord_flip() +
scale_x_reverse() +
facet_wrap(vars(parameter), nrow=1, scales = "free_x")

Scatterplot/volcano plot as an output from t.test

It is my data:
> dput(data)
structure(list(foldchange = c(-0.17853057272962, 3.60013440830337,
0.648944710423407, 1.38528656859267, 2.38882890772698, 1.91371568283765,
1.77591931363495, -1.51447851175922, 3.1416903855924, 1.51711016957237,
3.14707703341916, -1.44751697381751, 1.23658565660726, -0.512829478520189,
1.68928069854351, 2.07214007434345, 1.24799276690488, 6.25149659558487,
6.35918877435554, 5.86088034655694, 6.38890659730165, 5.05510489389194,
4.62060389613534, 3.75508710774868, 4.18575763169519, 5.31627264153051,
5.87091236649665, 6.71464565321037, 5.24000610137973, 4.25821377851955,
7.32277714374523, 3.1963295806222, 7.26249808789293, 4.44427454088613,
6.21495395454133, 8.74469985969472, 7.49982946564144, 4.45020943795387,
5.66199031471621, 5.29959827685333, 8.65819317196484, 5.86664903755707,
4.5740575604176, 8.24504501687473, 5.7916074097308, 4.18199181353134,
6.73956641707995, 4.60357435173805, 5.9205153184753, 3.65014593638562,
3.25607795403669, 5.56919529940933, 5.76811109641351, 6.10600807588152,
5.69234974521511, 5.5102283323841, 4.71232921328194, 6.55727667796477,
6.19995053763513, 4.64209842048131, 2.29238227264409, 6.79465189260383,
7.51968952300944, 7.81695579226993, 6.29926703626301, 4.64687557749141,
-2.44220257171186, 5.33199370895397, 5.18820654974805, 5.03498241997507,
6.29395095024283, 6.27602377186869, 6.78363927671209, 2.93759015053983,
6.65061604346668, 5.671080311536, 8.45199131823131, 5.79230415012306,
6.3270025568739, 7.0934690916107, 3.53800869528685, 3.08683779646569,
6.82111375813946, 3.02729078403818, 5.36024214796805, 4.04778690916444,
5.74765756930797, 4.10788604670319, 6.39978058654016, 5.7746717387066,
2.9247167920294, 7.54315906042106, 4.2742172444481, 6.61121261965006,
3.77012175922873, 4.94407566887151, 7.93185716981795, 7.05304621480995,
5.59261760605766, 5.42381827536197, 4.22645498896606, 5.15806113482742,
4.15403623593809, 6.40153592433128, 7.38902001442131, 2.72654942454391,
3.28741231093207, 3.79334363176751, 5.86527050546341, 5.10320299162235,
3.99883612485974, 6.45475273104195, 4.85567883821983, 6.55055641729645,
5.03746875764267, 7.27660375171087, 3.30817125205364, 5.23766518187252,
7.6588755830143, 3.53552741086444, 5.66455197986778, 8.40623211540503,
3.93151438658523, 4.26875667827774, 4.38704995079332, 6.75232207417316,
3.76563594385214, 6.08008097541859, 2.40905905886796, 5.50981339395085,
5.78780269825563, 0.2322416329745, 5.69410860233132, 4.94656296117567,
4.20594226169741, 4.50293112094816, 6.07430576125864, 3.67684848946483,
5.825851099141, 5.22439201628482, 7.72829018644622, 5.24910611944979,
4.01783420322782, 6.3888069709767, 5.26066649741256, 4.81678726754752,
6.5683773907454, 4.86957242886115, 6.76705114368644, 4.45769029291236,
7.77607596853254, 6.85213457577069, 1.40150885676552, 5.43409652313493,
3.21738153172066, 6.23015085020594, 5.50091556711613, 3.99948543388746,
5.85816098688073, 4.33775608630599, 5.91715214825299, 5.45674826103132,
7.66790792082782, 6.63325838131012, 3.89631178894691, 2.38526575667126,
1.58661549426288, 4.76626341270591, 6.73426272316295, 5.54006035262931,
4.07996836453406, 7.12087390022358, 6.96007461543701, 5.68202490906633,
6.58504044389069, 5.41036820315057, 6.61076809589319, 1.23772469006557,
4.1661166499875, 2.94059625298825, 8.38336956160413, 4.84906289871508,
4.93787691221829, 6.82379835301371, 5.82520798412864, 4.87582657907206,
5.36621724700676, 8.91922991774938, 3.49025109999629, 5.1232073414505,
4.27193651596412, 5.07417945071012, 3.61930149745523, 2.7469092502892,
6.67162003616042, 4.86698118654996, 7.53876919017093, 4.58878989189686,
5.78956520376246, 3.98567045767003, 8.14934433289609, 6.88879716040936,
7.00251456012974, 5.05095662412332, 6.39777439550296, 7.96268799093557,
4.82826575143863, 8.31032763539508, 4.74493707321909, 6.8929416113222,
6.84202549278968, 8.20121430968127, 2.91031632522241, 4.86190488550545,
5.5516465446887, 7.74996457744065, 2.25505738807845, 5.71069872298306,
1.97493599527532, 5.60445326341706, 6.39297603198736, 7.16298115056911,
4.52688105225386, 6.46061751569601, 4.78104064111529, 2.84526825975018,
6.5537923066898, 6.98258253798747, 5.0967396817644, 6.64593966293456,
4.8990397150507, 4.59878411928317, 5.55158425631398, 2.1065660739172,
2.40396884881286, 6.45421536580342, 5.98567305090568, 6.48593538806214,
7.41313242816247, 5.99024340460149, 5.63812101302136, -1.43793573368627
), all_pvalue = c(0.818887590433193, 0.00892139546812015, 0.434133425685163,
0.0536266013313456, 0.0450933986128537, 0.0367856407800243, 0.0941222253709068,
0.213526299326008, 0.00855327289085924, 0.0449444491492238, 0.00465098209958804,
0.0369667514121697, 0.0910501610463896, 0.378892060498093, 0.0595757077704777,
0.031626850730261, 0.0878934608628569, 0.0124722939899662, 0.0249040599008334,
0.0150448394759397, 0.0104024068916351, 0.0340577599419123, 0.0244947271472485,
0.122485247246688, 0.0211309039009709, 0.0201043058824927, 0.0152779076456381,
0.00938733157248341, 0.013807428170544, 0.01948348499862, 0.0119978631408916,
0.0997968486684091, 0.00504808432168479, 0.041226720485986, 0.0127407583225205,
0.00709338243276709, 0.00383605674079435, 0.0399854589187244,
0.0163222001450531, 0.00909800553027099, 4.81144191594885e-06,
0.0105231068132293, 0.0377428014886314, 0.00709059633291303,
0.00743882656849872, 0.0696633906261403, 0.00568508439144595,
0.0142206230933159, 0.0183625193075117, 0.0818974933908099, 0.0609423408539195,
0.00581572852382799, 0.00603085345605447, 0.00684099077236254,
0.0194814381299995, 0.0325641567545152, 0.0404062983698557, 0.00626431765905907,
0.00287654691487974, 0.0183318967557602, 0.202860908663261, 0.0033395497287839,
0.00804091896430431, 0.00524635934550195, 0.0100089274728679,
0.00470611875383887, 0.361169323059008, 3.90129727113067e-06,
0.0205225005371219, 0.0120500045076898, 0.00732055098038156,
0.0229916087025324, 0.00544774481324614, 0.108252753362848, 0.00911923198666818,
0.0122812312739145, 0.00343585528287351, 2.06257208918569e-05,
0.000904993210532763, 0.0015065294739414, 0.102118204143709,
0.118350948568527, 0.0136202759386966, 0.15251012082679, 0.0428316882385798,
0.0752744217284719, 0.00632986043900174, 0.0269567937932686,
0.00707537967267082, 0.0149356605279715, 0.163005190656644, 0.00929612911973378,
0.0196453775259569, 0.0133262667903121, 0.114115405959882, 0.0189109801950218,
0.00590387539250432, 0.00802692325541374, 0.0184346327727756,
0.00104714399950925, 0.0554774130259537, 0.0084910975380844,
0.0349856904843115, 0.0124547169142572, 8.60050865459788e-07,
0.1188515828269, 0.133720711339729, 0.0641704698591151, 0.0075124796175742,
3.94432669779951e-07, 0.0740343932996142, 0.00160775849728933,
6.61326355967731e-06, 0.0106610228625055, 0.00539717052083514,
0.00492255859958016, 0.122531121480312, 0.0159768620962635, 0.00365780586610517,
0.0135086464724098, 0.0256265865459836, 0.00391215568816396,
0.0271580638871089, 0.0512876942387616, 0.0135566028247977, 0.0169110062500104,
0.0848247460082605, 0.0158705161056627, 0.176345767878009, 0.0124719098589431,
0.0152388258990332, 0.866066700538701, 0.042979313425954, 0.0160125031962862,
0.0441592105265668, 0.0124108545467876, 1.80875437447348e-06,
0.0704671677844812, 0.0111351361909711, 1.62883074487165e-07,
0.000694779973318456, 0.0120079549431507, 0.0196183531679123,
0.0100186493225724, 0.0173294242221405, 0.0573614373022037, 1.30612522568528e-07,
0.023898721968545, 0.00665918028588502, 0.06907634259105, 0.00518730999717143,
0.0109717740506543, 0.394662670743417, 0.0165847750353483, 0.0593829446004973,
0.000113216713641592, 0.0222583368635018, 0.0694462386106761,
0.00437955933335859, 0.0631677226779205, 0.00649674049335009,
1.10699021652115e-07, 0.00543997929535101, 0.00292890932795308,
0.021574456097881, 0.17997075681454, 0.279770535484078, 0.050945514039484,
0.0102923410906512, 0.0103389721465925, 0.112227938286441, 0.00398090342551613,
0.0428676019413789, 0.00337313863923396, 0.0092822848687081,
0.00778850900332348, 0.00146877357609246, 0.448950342618974,
0.0801294647165026, 0.0797698230881222, 3.72112644308374e-05,
0.00728653989704988, 0.0320006421510141, 0.000420503611946363,
0.0207086037412542, 0.0448889114898146, 6.94555482668648e-07,
0.000135994029220134, 0.0982385638169219, 0.0130399195487442,
0.0297056523919866, 0.0208455457844783, 0.104595177359326, 0.100684824982166,
0.00110472016462074, 0.0664329210478157, 0.0140428240948167,
0.0468861767036331, 0.0102813794498838, 0.0693803856754811, 0.00566014993761021,
0.00275831473628789, 0.00234550137829788, 0.0116252548991317,
0.0143153463606759, 0.00995352784254985, 0.00238257560505637,
0.00182950280683248, 0.013195116994233, 0.000640921917352429,
0.000171523469251389, 0.0087256530793244, 0.0989386901919075,
0.0321103798387662, 0.0222773975090858, 0.007943310795799, 0.171053950985746,
0.012874269835152, 0.38817395138115, 0.00787508757030877, 0.0114487159712535,
0.0187831808209386, 0.0452479566115196, 0.00640720682677851,
0.0315482155790946, 0.125132833439637, 0.0115284490664364, 0.00538397509568388,
0.00517772137814985, 0.00176762574966497, 0.0273122011845722,
0.0191341545126795, 0.0235413416908084, 0.270326642321866, 0.179926862630332,
0.008734949388329, 0.0138918131322944, 0.00507817315892406, 0.000173786133243839,
0.00225184544628237, 0.0181059516295825, 0.541544494598043),
probename = c("Mark_1", "Mark_2", "Mark_3", "Mark_4", "Mark_5",
"Mark_6", "Mark_7", "Mark_8", "Mark_9", "Mark_10", "Mark_11",
"Mark_12", "Mark_13", "Mark_14", "Mark_15", "Mark_16", "Mark_17",
"Mark_18", "Mark_19", "Mark_20", "Mark_21", "Mark_22", "Mark_23",
"Mark_24", "Mark_25", "Mark_26", "Mark_27", "Mark_28", "Mark_29",
"Mark_30", "Mark_31", "Mark_32", "Mark_33", "Mark_34", "Mark_35",
"Mark_36", "Mark_37", "Mark_38", "Mark_39", "Mark_40", "Mark_41",
"Mark_42", "Mark_43", "Mark_44", "Mark_45", "Mark_46", "Mark_47",
"Mark_48", "Mark_49", "Mark_50", "Mark_51", "Mark_52", "Mark_53",
"Mark_54", "Mark_55", "Mark_56", "Mark_57", "Mark_58", "Mark_59",
"Mark_60", "Mark_61", "Mark_62", "Mark_63", "Mark_64", "Mark_65",
"Mark_66", "Mark_67", "Mark_68", "Mark_69", "Mark_70", "Mark_71",
"Mark_72", "Mark_73", "Mark_74", "Mark_75", "Mark_76", "Mark_77",
"Mark_78", "Mark_79", "Mark_80", "Mark_81", "Mark_82", "Mark_83",
"Mark_84", "Mark_85", "Mark_86", "Mark_87", "Mark_88", "Mark_89",
"Mark_90", "Mark_91", "Mark_92", "Mark_93", "Mark_94", "Mark_95",
"Mark_96", "Mark_97", "Mark_98", "Mark_99", "Mark_100", "Mark_101",
"Mark_102", "Mark_103", "Mark_104", "Mark_105", "Mark_106",
"Mark_107", "Mark_108", "Mark_109", "Mark_110", "Mark_111",
"Mark_112", "Mark_113", "Mark_114", "Mark_115", "Mark_116",
"Mark_117", "Mark_118", "Mark_119", "Mark_120", "Mark_121",
"Mark_122", "Mark_123", "Mark_124", "Mark_125", "Mark_126",
"Mark_127", "Mark_128", "Mark_129", "Mark_130", "Mark_131",
"Mark_132", "Mark_133", "Mark_134", "Mark_135", "Mark_136",
"Mark_137", "Mark_138", "Mark_139", "Mark_140", "Mark_141",
"Mark_142", "Mark_143", "Mark_144", "Mark_145", "Mark_146",
"Mark_147", "Mark_148", "Mark_149", "Mark_150", "Mark_151",
"Mark_152", "Mark_153", "Mark_154", "Mark_155", "Mark_156",
"Mark_157", "Mark_158", "Mark_159", "Mark_160", "Mark_161",
"Mark_162", "Mark_163", "Mark_164", "Mark_165", "Mark_166",
"Mark_167", "Mark_168", "Mark_169", "Mark_170", "Mark_171",
"Mark_172", "Mark_173", "Mark_174", "Mark_175", "Mark_176",
"Mark_177", "Mark_178", "Mark_179", "Mark_180", "Mark_181",
"Mark_182", "Mark_183", "Mark_184", "Mark_185", "Mark_186",
"Mark_187", "Mark_188", "Mark_189", "Mark_190", "Mark_191",
"Mark_192", "Mark_193", "Mark_194", "Mark_195", "Mark_196",
"Mark_197", "Mark_198", "Mark_199", "Mark_200", "Mark_201",
"Mark_202", "Mark_203", "Mark_204", "Mark_205", "Mark_206",
"Mark_207", "Mark_208", "Mark_209", "Mark_210", "Mark_211",
"Mark_212", "Mark_213", "Mark_214", "Mark_215", "Mark_216",
"Mark_217", "Mark_218", "Mark_219", "Mark_220", "Mark_221",
"Mark_222", "Mark_223", "Mark_224", "Mark_225", "Mark_226",
"Mark_227", "Mark_228", "Mark_229", "Mark_230", "Mark_231",
"Mark_232", "Mark_233", "Mark_234", "Mark_235", "Mark_236",
"Mark_237", "Mark_238", "Mark_239", "Mark_240", "Mark_241",
"Mark_242")), row.names = c("Mark_1", "Mark_2", "Mark_3",
"Mark_4", "Mark_5", "Mark_6", "Mark_7", "Mark_8", "Mark_9", "Mark_10",
"Mark_11", "Mark_12", "Mark_13", "Mark_14", "Mark_15", "Mark_16",
"Mark_17", "Mark_18", "Mark_19", "Mark_20", "Mark_21", "Mark_22",
"Mark_23", "Mark_24", "Mark_25", "Mark_26", "Mark_27", "Mark_28",
"Mark_29", "Mark_30", "Mark_31", "Mark_32", "Mark_33", "Mark_34",
"Mark_35", "Mark_36", "Mark_37", "Mark_38", "Mark_39", "Mark_40",
"Mark_41", "Mark_42", "Mark_43", "Mark_44", "Mark_45", "Mark_46",
"Mark_47", "Mark_48", "Mark_49", "Mark_50", "Mark_51", "Mark_52",
"Mark_53", "Mark_54", "Mark_55", "Mark_56", "Mark_57", "Mark_58",
"Mark_59", "Mark_60", "Mark_61", "Mark_62", "Mark_63", "Mark_64",
"Mark_65", "Mark_66", "Mark_67", "Mark_68", "Mark_69", "Mark_70",
"Mark_71", "Mark_72", "Mark_73", "Mark_74", "Mark_75", "Mark_76",
"Mark_77", "Mark_78", "Mark_79", "Mark_80", "Mark_81", "Mark_82",
"Mark_83", "Mark_84", "Mark_85", "Mark_86", "Mark_87", "Mark_88",
"Mark_89", "Mark_90", "Mark_91", "Mark_92", "Mark_93", "Mark_94",
"Mark_95", "Mark_96", "Mark_97", "Mark_98", "Mark_99", "Mark_100",
"Mark_101", "Mark_102", "Mark_103", "Mark_104", "Mark_105", "Mark_106",
"Mark_107", "Mark_108", "Mark_109", "Mark_110", "Mark_111", "Mark_112",
"Mark_113", "Mark_114", "Mark_115", "Mark_116", "Mark_117", "Mark_118",
"Mark_119", "Mark_120", "Mark_121", "Mark_122", "Mark_123", "Mark_124",
"Mark_125", "Mark_126", "Mark_127", "Mark_128", "Mark_129", "Mark_130",
"Mark_131", "Mark_132", "Mark_133", "Mark_134", "Mark_135", "Mark_136",
"Mark_137", "Mark_138", "Mark_139", "Mark_140", "Mark_141", "Mark_142",
"Mark_143", "Mark_144", "Mark_145", "Mark_146", "Mark_147", "Mark_148",
"Mark_149", "Mark_150", "Mark_151", "Mark_152", "Mark_153", "Mark_154",
"Mark_155", "Mark_156", "Mark_157", "Mark_158", "Mark_159", "Mark_160",
"Mark_161", "Mark_162", "Mark_163", "Mark_164", "Mark_165", "Mark_166",
"Mark_167", "Mark_168", "Mark_169", "Mark_170", "Mark_171", "Mark_172",
"Mark_173", "Mark_174", "Mark_175", "Mark_176", "Mark_177", "Mark_178",
"Mark_179", "Mark_180", "Mark_181", "Mark_182", "Mark_183", "Mark_184",
"Mark_185", "Mark_186", "Mark_187", "Mark_188", "Mark_189", "Mark_190",
"Mark_191", "Mark_192", "Mark_193", "Mark_194", "Mark_195", "Mark_196",
"Mark_197", "Mark_198", "Mark_199", "Mark_200", "Mark_201", "Mark_202",
"Mark_203", "Mark_204", "Mark_205", "Mark_206", "Mark_207", "Mark_208",
"Mark_209", "Mark_210", "Mark_211", "Mark_212", "Mark_213", "Mark_214",
"Mark_215", "Mark_216", "Mark_217", "Mark_218", "Mark_219", "Mark_220",
"Mark_221", "Mark_222", "Mark_223", "Mark_224", "Mark_225", "Mark_226",
"Mark_227", "Mark_228", "Mark_229", "Mark_230", "Mark_231", "Mark_232",
"Mark_233", "Mark_234", "Mark_235", "Mark_236", "Mark_237", "Mark_238",
"Mark_239", "Mark_240", "Mark_241", "Mark_242"), class = "data.frame")
I would like to create a nice graph (publication wise) to represent a data stored in this data frame. In general I would like to create a scatterplot or volcano plot with colors/shapes indicating what is important in my data.
I would like to achieve something like that:
Or:
As a filter cutoff we can start with: foldchange > 4 & all_pvalue < 0.05. I would like to also have a possibility to highlight (different color/shape and with a label) only couple of rows. Lets say as a starting point I would like to highlight Mark_23 and Mark_65.
Is it doable in R ? I have already tried something with volcano plot:
volcano = ggplot(data = data, aes(x = foldchange, y = -1*log10(all_pvalue)))
volcano + geom_point()
Can someone help me with going further ?

Here is an attempt to show what's possible
data$zones := interaction(abs(data$foldchange)>4,data$all_pvalue<0.05)
library(ggplot2)
library(ggrepel)
ggplot(data = data, aes(x = foldchange, y = -1*log10(all_pvalue),color = zones))+
geom_point()+
theme_light()+
geom_label_repel(aes(label=ifelse(probename %in% c("Mark_23","Mark_65"),as.character(probename),"")),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50',show.legend = FALSE) +
geom_hline(yintercept = -1*log10(0.05),linetype = "dashed")+
geom_vline(xintercept = 4,linetype = "dashed")+
scale_color_manual(labels = c("bad", "also bad","good","not sure"), values = c("gray50","green","blue", "red"))+
labs(x = "fold change",
y = expression(log[10](p)),
color = "meaning")
there are many things here. geom_label_repel from library(ggrepel) allow to link your few points you want to show with a label. The easiest way of having the different colours is to create a variable that says in what zone you are. That is what I did with the zones variable, that you use in colour to have a changing color. You can manualy change it with the scale_color_manual function.
In the labs function I used the expression function that allows you to do superscripts. You can of course change the theme including, margins, axis, text size etc.
You can for example add theme(legend.position="top") to your plot to have the legend on top.

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