How can I add labels on the geom line? - r

Instead of adding legends outside the plot, I want to add names such as "Quantile 1", "Quantile 10" etc. inside the plot as labels.
ggplot() +
geom_line(data=df.quants, aes(x=xvars, y=q01), color="black", size =0.5) +
geom_line(data=df.quants, aes(x=xvars, y=q10), color="black", size =0.7) +
geom_line(data=df.quants, aes(x=xvars, y=q25), color="black", size =1) +
geom_line(data=df.quants, aes(x=xvars, y=q50), color="black", size =1.2) +
geom_line(data=df.quants, aes(x=xvars, y=q75), color="black", size =1) +
geom_line(data=df.quants, aes(x=xvars, y=q90), color="black", size =0.7) +
geom_line(data=df.quants, aes(x=xvars, y=q99), color="black", size =0.5) +
geom_ribbon(data=df.quants,aes(x=xvars,ymin=q25,ymax=q75),alpha=0.8)+
geom_ribbon(data=df.quants,aes(x=xvars,ymin=q10,ymax=q25),alpha=0.5)+
geom_ribbon(data=df.quants,aes(x=xvars,ymin=q75,ymax=q90),alpha=0.5)+
geom_ribbon(data=df.quants,aes(x=xvars,ymin=q01,ymax=q10),alpha=0.2)+
geom_ribbon(data=df.quants,aes(x=xvars,ymin=q90,ymax=q99),alpha=0.2)+
theme_bw()+
ggtitle("Q")+
ggsave("save.png")
How can I add labels on the plot in either or both of these cases:
At the end of the lines (e.g. https://stackoverflow.com/a/37696769/3942806)
Hovering over the lines towards the left hand side (https://stackoverflow.com/a/37672486/3942806)
dput(df.quants)
structure(list(xvars = c(21.1084, 40.4038, 42.4758, 44.0298,
44.8068, 53.0948, 53.3538, 54.3898, 56.4617, 62.9367, 67.3397,
68.8937, 68.8937, 74.3327, 78.7356, 80.2896, 87.8006, 95.0526,
98.6785, 105.6715, 114.4775, 116.5495, 121.7294, 127.4274, 133.6434,
146.3343, 153.0683, 158.2483, 163.6872, 169.9032, 180.7812, 186.4791,
186.9971, 194.5081, 196.3211, 203.8321, 209.789, 215.746, 218.336,
222.998, 230.7679, 237.5019, 241.1279, 242.12505, 250.9698, 254.0778,
264.1788, 274.5387, 284.8987, 292.6687, 303.0286, 310.7986, 326.3385,
336.6985, 344.4684, 362.5983, 378.1383, 389.275200000003, 393.6782,
409.2181, 427.348, 450.6579, 450.6579, 450.6579, 453.2479, 463.6079,
476.5578, 489.5078, 499.8677, 510.2277, 523.1776, 533.5376, 543.8975,
567.2074, 611.2372, 613.8272, 621.5971, 637.1371, 652.677, 660.447,
668.2169, 678.5769, 696.447800000002, 714.8367, 744.880600000001,
764.0465, 766.6365, 779.5864, 784.7664, 810.6663, 815.8463, 839.1561,
852.1061, 872.826, 896.1359, 903.9059, 916.8558, 937.5757, 966.0656,
984.1955), q01 = c(0.07287449, 0.0573897264, 0.0557969357, 0.0537193707,
0.0518303892, 0.0518080158, 0.0514479006, 0.0517025388, 0.0516258276,
0.0459982978, 0.0471084591, 0.0402322638, 0.0406957203, 0.0373694866919881,
0.0375932247971234, 0.0378606448, 0.0374813557445557, 0.036479866,
0.0368506252, 0.0362731762, 0.0367099924, 0.0329852952, 0.0280992996,
0.0278553199, 0.0277327966, 0.0279245722, 0.0279458806, 0.0277967218,
0.0279831703, 0.0237609194, 0.0207585756691242, 0.0207543139705945,
0.0196036650330279, 0.0188940975085873, 0.0186277436, 0.0167249092,
0.0167046666, 0.0166865548, 0.0161687604, 0.0161591718, 0.0161879376,
0.011199656, 0.0111985905, 0.01105689088, 0.0110845916, 0.0106222032239633,
0.0109610059070531, 0.0109652675220967, 0.0109769869296186, 0.01043682232,
0.00988280416, 0.00995951416, 0.0109119973340507, 0.0099936076,
0.00955359025, 0.00895376068, 0.00836565071, 0.00829852949, 0.00825058604,
0.00660771382, 0.00658320918, 0.00658320918, 0.00647347103215001,
0.00720008536, 0.00722565544, 0.00697102063, 0.00688152578, 0.00688898372,
0.00692733882, 0.00618580850401875, 0.0061218835, 0.0061090985,
0.00609311725, 0.00584274444, 0.00583954821, 0.00575325, 0.00575325,
0.0050873645, 0.00522693399, 0.00516087826, 0.00496803746, 0.00490198142,
0.00490198142, 0.00490198142, 0.0057798848, 0.00555082036, 0.00518857905,
0.00508949534, 0.0050127851, 0.0049701683, 0.0049275515, 0.00487428075,
0.00479011332, 0.00476347782, 0.0047783937, 0.00476880492, 0.00487747698,
0.00485510337, 0.0048582996, 0.00479330958), q10 = c(0.492542083954826,
0.45454932, 0.43124864, 0.41944381, 0.37937352, 0.38026848, 0.37053055,
0.37472832, 0.35278072, 0.34281907, 0.34762414, 0.28118472, 0.28004471,
0.272746634508843, 0.24855102, 0.25194972, 0.242531451945451,
0.2256552, 0.206232684634562, 0.19673984, 0.20522054, 0.18095038,
0.170956713240997, 0.16841043, 0.163157896833582, 0.16456426,
0.16100576, 0.15623268, 0.15471976, 0.15003198, 0.143000209281909,
0.1429789, 0.14078417, 0.13547836, 0.13492432, 0.13260178, 0.12952273,
0.1337311, 0.1273386, 0.123471123238866, 0.12135096, 0.10445342,
0.10836355, 0.10458128, 0.10262094, 0.10075645, 0.10061794, 0.099659066,
0.099925431, 0.0973364588484978, 0.0949499261725975, 0.0949499261725975,
0.1001705, 0.09823141, 0.091689753, 0.0820796952618794, 0.080683995,
0.079256336, 0.078052418, 0.0678883475337737, 0.067302367, 0.0675474110377157,
0.065970594, 0.068889834, 0.069379928, 0.06499041, 0.0639143363015129,
0.0628169628570211, 0.061410608, 0.0606541642970382, 0.0605369686562966,
0.06094183, 0.0605476229844449, 0.0566162367773279, 0.056371194,
0.054080544, 0.0546025993937779, 0.051779245, 0.052375877, 0.051907098,
0.050639252, 0.050308969, 0.050308969, 0.050308969, 0.053643725,
0.053505218, 0.0507671, 0.049691026, 0.04884935, 0.04810356,
0.04757085, 0.04687833, 0.045727678, 0.045503944, 0.04687833,
0.046729174, 0.051971022, 0.050308975, 0.0498615, 0.048039636
), q25 = c(0.6404219, 0.6244939, 0.605822475, 0.602040281120818,
0.5927978, 0.588349675, 0.579639875, 0.5777754, 0.5689325, 0.55953015,
0.5641647, 0.53696995, 0.53358725, 0.518511625, 0.509855075,
0.5100149, 0.4870019, 0.477573, 0.46324315, 0.45551885, 0.4599403,
0.4263797, 0.414766675, 0.403526531046239, 0.39313875, 0.385361200596633,
0.3733752, 0.364585555646708, 0.358486025, 0.34375665, 0.321915594917963,
0.3211166, 0.317574060052206, 0.299701695823567, 0.2932026, 0.28931385,
0.27794055, 0.28041765, 0.2627317, 0.252370517653953, 0.248348618836565,
0.2258683, 0.2306094, 0.22400385, 0.2216066, 0.21785105, 0.214521628563819,
0.2121244, 0.210153425, 0.2043469, 0.2011506, 0.2003516, 0.207196875,
0.206317924738973, 0.200431525, 0.189537609205199, 0.187220325,
0.181600263653314, 0.179948860004262, 0.1733433, 0.1733433, 0.170413425,
0.1667377, 0.16812275, 0.16993395, 0.1648199, 0.16276905, 0.15768165,
0.15347325, 0.150916225, 0.14910505, 0.14990415, 0.1474537, 0.1441509,
0.142712575, 0.138690575, 0.14098125, 0.135813975, 0.137385475,
0.14217985, 0.139969074168975, 0.139516275, 0.139516275, 0.139516275,
0.143751322267206, 0.1424995, 0.140688225, 0.1389303, 0.136639675,
0.134801865933305, 0.137785025, 0.135813975, 0.132537822288515,
0.128356075, 0.129900875, 0.1293416, 0.14106115, 0.137598575,
0.1421266, 0.1387705), q50 = c(0.7691242, 0.7631579, 0.75559345,
0.751917760334541, 0.7506925, 0.746484148060942, 0.7420094, 0.7371617,
0.7325804, 0.72565525, 0.72682715, 0.7165992, 0.7147347, 0.702002962412103,
0.69640955, 0.6950778, 0.6869806, 0.6838909, 0.6740358, 0.6714255,
0.6721713, 0.6567228, 0.64947795, 0.63834435, 0.6361602, 0.6261453,
0.613253782228852, 0.603665, 0.593756671084594, 0.579267, 0.5622203,
0.5610484, 0.5582783, 0.5308971, 0.5144897, 0.5100149, 0.49355425,
0.4915832, 0.4779459, 0.4607394, 0.4513105, 0.424462, 0.42510125,
0.4174302, 0.4121031, 0.40336673736416, 0.3968677, 0.3919668,
0.39036865, 0.3808864, 0.373961218836565, 0.3727893, 0.38408265,
0.3834434, 0.37646495, 0.3681014, 0.3637332, 0.3615491, 0.3576603,
0.3552099, 0.35398465, 0.34775195, 0.3416791, 0.3381632, 0.3388025,
0.33187725, 0.33059875, 0.3258044, 0.3180268, 0.3064138, 0.3049222,
0.3091839, 0.3065736, 0.2999148, 0.29900915, 0.2925634, 0.3009802,
0.2956531, 0.29698485, 0.3044961, 0.30412315, 0.3014596, 0.3014596,
0.3014596, 0.3147773, 0.3135521, 0.3128596, 0.30998295, 0.3091306,
0.3039633, 0.30907735, 0.303856783177072, 0.2949073, 0.28595785,
0.285371829778393, 0.2846793, 0.2958662, 0.29607925, 0.3035372,
0.30359045), q75 = c(0.8668229, 0.8637865, 0.86104305, 0.858752425,
0.8584061, 0.8549169, 0.852066925, 0.8492436, 0.8462604, 0.843783275,
0.843410426177285, 0.838909, 0.838349675, 0.833795025, 0.831530975,
0.8301726, 0.8252717, 0.8239399, 0.820557211213509, 0.81797355,
0.8167483, 0.8088643, 0.80244515, 0.7948274, 0.7947475, 0.787183054698487,
0.7810036, 0.77716815, 0.769097575, 0.7540486, 0.74861495, 0.7479224,
0.746617297091413, 0.7200618, 0.704879607926699, 0.702588945727679,
0.690203494363946, 0.68458345, 0.6740891, 0.658480725, 0.6435649,
0.630833155763904, 0.626811225, 0.62129765, 0.6129342, 0.60827295,
0.60275945, 0.593117408906883, 0.59125295, 0.58507352145749,
0.5743661, 0.5681334, 0.5741264, 0.575431476028127, 0.573353929725122,
0.5659493, 0.560702075, 0.556706775, 0.5519923, 0.54645215, 0.53976665,
0.53526525, 0.5334541, 0.5324419, 0.52743445, 0.519204135014916,
0.519017675, 0.517899, 0.50905605, 0.495258875, 0.5004794, 0.50298315,
0.491023875559344, 0.4816748, 0.485164082175581, 0.479171075,
0.48889305, 0.482500525, 0.485696775, 0.4886533, 0.4919028, 0.490890725,
0.490890725, 0.490890725, 0.506552325, 0.50649905, 0.504741075,
0.49978695, 0.502477093543576, 0.492915025, 0.49629765, 0.4903047,
0.4775197, 0.4731249, 0.464175375, 0.4632431, 0.46942255, 0.472725375,
0.4760281, 0.474536573433838), q90 = c(0.9314937, 0.93079054,
0.92979966, 0.928574429757085, 0.92748774, 0.92662476, 0.92585765,
0.9235457, 0.92188366, 0.92058388, 0.91802683, 0.91566162, 0.91534197,
0.9129022, 0.91192198, 0.91067548, 0.907671, 0.9073088, 0.90595568,
0.904773066349883, 0.9035372, 0.897741346746218, 0.89466225,
0.889740052584701, 0.88860004, 0.88158958, 0.88022584, 0.878883448075858,
0.86893244, 0.863030027896868, 0.86177288, 0.8616024, 0.859290453515875,
0.8365012, 0.82799918, 0.824568514587684, 0.819273379833795,
0.81630088, 0.81448968, 0.79439591, 0.78960152, 0.783315567773279,
0.776464946030258, 0.776731300370765, 0.76594926, 0.75919456,
0.75371832, 0.75075644, 0.74735775, 0.74310678, 0.72495204, 0.7112508,
0.713807792386533, 0.7141487, 0.71468144, 0.713530774319199,
0.71050504, 0.707809474097592, 0.70632856, 0.70217348, 0.69276586,
0.68746007, 0.68621354, 0.68354994, 0.67928834, 0.66894312, 0.66838907,
0.66891114, 0.66275304248029, 0.65147025, 0.655188582416365,
0.65889626, 0.64831662, 0.640571045322821, 0.64626035, 0.64103984,
0.637385467717878, 0.63600045, 0.639899844314937, 0.638908996019603,
0.64134882, 0.64137014, 0.64137014, 0.64137014, 0.6497443, 0.64977628,
0.64734715, 0.64238229, 0.6446303, 0.634775211037716, 0.635307911037716,
0.631685502855317, 0.62823354, 0.62139354, 0.61645005, 0.61583208,
0.61267846, 0.61427655, 0.6135734, 0.61338161), q99 = c(0.9813552,
0.983496688, 0.982289538, 0.981875103, 0.98133816, 0.981210342,
0.980869382, 0.98074156, 0.980605188, 0.980628629, 0.980474118,
0.97956530234349, 0.979405495101854, 0.979192435, 0.979102933,
0.97900704, 0.978866424, 0.97889414, 0.978801398, 0.978465764,
0.978167456, 0.97708924, 0.977054095, 0.977258668, 0.975373952,
0.972782846, 0.972770058, 0.972859574, 0.972306655, 0.97231411,
0.972591068, 0.97259746, 0.972355645, 0.962840406286384, 0.963136582842531,
0.943974016, 0.944772016962071, 0.944242504, 0.944018764, 0.935328143137652,
0.935241848623481, 0.934724015665886, 0.926759001178564, 0.926816535265289,
0.926234804, 0.917745605, 0.91511187081824, 0.915103346793096,
0.913937796999999, 0.90959943, 0.903311344, 0.894027274664394,
0.895148090432559, 0.897357759215854, 0.897743441, 0.894050713829107,
0.893945237587897, 0.889042197096101, 0.889281912489239, 0.888979338,
0.886543834, 0.886235893490944, 0.886239091206478, 0.886258277499681,
0.868235644, 0.868526506, 0.870900274999999, 0.871323255148946,
0.869995737948434, 0.867188371, 0.864700617419987, 0.864726187301939,
0.856755777, 0.844385296, 0.855691437, 0.83904428249137, 0.832750945,
0.837923525, 0.856581078, 0.855506063483912, 0.855462386340294,
0.838475343, 0.838475343, 0.838475343, 0.855438949824206, 0.855484757560196,
0.855492214633497, 0.855447472193693, 0.855524173519071, 0.85631259,
0.859764525, 0.861629, 0.865305772, 0.861820776, 0.861149560000001,
0.861581055999999, 0.861485167999999, 0.858912205, 0.86234816,
0.860478344)), .Names = c("xvars", "q01", "q10", "q25", "q50",
"q75", "q90", "q99"), row.names = c(NA, -100L), class = "data.frame")


You should try the directlabels package. Here's an example:
library(tidyverse)
library(directlabels)
df.quants %>%
gather(var,val,-1) %>%
ggplot(aes(xvars,val,fill=var)) +
geom_area(position="identity", alpha = .5) +
geom_line() +
scale_fill_grey(guide="none") +
geom_dl(aes(label=var), method="last.points")
Make sure to browse through its documentation as there are many more options.
You can extend that approach to also use custom labels, linewidths, fillings etc. One way could be:
labs <- setNames(c("G", "F", "E", "D", "C", "B", "A"), c("q99", "q90", "q75", "q50", "q25", "q10", "q01"))
df.quants %>%
rev %>%
gather(var,val,-xvars,factor_key=TRUE) %>%
ggplot(aes(xvars,val,fill=var)) +
geom_area(position="identity") +
geom_line(aes(size=var)) +
scale_fill_manual(values = c(grey.colors(3,.9,.3), grey.colors(4)), guide="none") +
scale_size_manual(values = c(1:3,4:1), guide="none") +
geom_dl(aes(label=labs[var]), method="last.points")

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,
0.992819225075914, 1.2077863640027, 1.73919343054343, 1.46425595551545,
1.47019352744474, 0.98196123570733, 1.19320931263264, 1.71307949511363,
1.45026647522637, 1.45631802244833, 0.9714623771931, 1.17903145855638,
1.68748692465827, 1.43641295742272, 1.4425733488853, 0.96131124954466,
1.16524369529089, 1.66241206053094, 1.42269978906386, 1.42896377616518,
0.951496636765001, 1.15183684475424, 1.63785049711299, 1.40913104971445,
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,
1.06788228949262, 1.47979668795232, 1.31847477179054, 1.32536893978401,
0.883820828081197, 1.05719325369659, 1.45911544607085, 1.30617346866088,
1.31312090423067, 0.876567338404172, 1.04680379851168, 1.4388849766195,
1.29404053293171, 1.30103552339406, 0.869551054721558, 1.03670538800144,
1.41909679318253, 1.28207734256312, 1.28911419066604, 0.862763461210944,
1.02688963517278, 1.39974226496544, 1.2702850494734, 1.27735808271664,
0.856196303691171, 1.01734831012073, 1.38081265180883, 1.25866458822613,
1.26576816767268, 0.849841587290416, 1.00807334680985, 1.36229913631591,
1.24721668475813, 1.25434521333641, 0.843691573408777, 0.99905684861186,
1.34419285322773, 1.23594186511587, 1.24308979541463, 0.837738776073223,
0.990291092711936, 1.3264849161844, 1.22484046417117, 1.23200230573094,
0.831975957773722, 0.981768533488905, 1.3091664420122, 1.21391263428855,
1.22108296039557, 0.826396124860962, 0.973481804967925, 1.29222857267723,
1.20315835391962, 1.21033180790988, 0.820992522578248, 0.965423722437341,
1.27566249504498, 1.19257743610158, 1.1997487371841, 0.815758629792936,
0.957587283315014, 1.25945945858363, 1.18216953683933, 1.18933348544938,
0.810688153486053, 0.949965667343234, 1.24361079114564, 1.17193416335278,
1.17908564604669, 0.805775023052616, 0.942552236185361, 1.22810791295855,
1.1618706821728, 1.16900467607732, 0.801013384459458, 0.935340532491705,
1.21294234895183, 1.15197832707131, 1.15908990390117, 0.796397594302229,
0.928324278496812, 1.19810573954163, 1.14225620681276, 1.14934053647087,
0.791922213798429, 0.921497374205249, 1.18358984999023, 1.13270331271594,
1.13975566649139, 0.787582002749033, 0.914853895218226, 1.16938657845174,
1.12331852601676, 1.13033427939609, 0.783371913497309, 0.908388090248925,
1.15548796281005, 1.11410062502406, 1.12107526013177, 0.779287084909823,
0.902094378370215, 1.14188618640925, 1.10504829206212, 1.11197739974653,
0.775322836401382, 0.895967346034515, 1.12857358277151, 1.09616012019459,
1.10303940177539, 0.771474662022726, 0.89000174390193, 1.11554263939148,
1.08743461972608, 1.09425988841997, 0.767738224627101, 0.884192483509395,
1.10278600069095, 1.07887022447868, 1.08563740651938, 0.764109350129453,
0.878534633810428, 1.09029647021224, 1.07046529784161, 1.07717043331055,
0.760584021869845, 0.873023417612164, 1.07806701212338, 1.0622181385934,
1.06885738197716, 0.757158375090736, 0.867654207933682, 1.06609075210328,
1.05412698649671, 1.06069660698705, 0.753828691536061, 0.862422524307139,
1.05436097767014, 1.04619002766682, 1.05268640921891, 0.750591394178479,
0.857324029040955, 1.04287113801187, 1.03840539971537, 1.04482504087941,
0.747443042079812, 0.852354523462208, 1.03161484337265, 1.03077119667177,
1.03711071021304, 0.744380325388455, 0.847509944153447, 1.02058586404586,
1.02328547368523, 1.02954158600691, 0.741400060476472, 0.84278635919742,
1.00977812901932, 1.01594625151082, 1.02211580189372, 0.738499185218138,
0.838179964441562, 0.999185724315382, 1.00875152078335, 1.0148314604562,
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,
0.980463287105968, 0.722603822563399, 0.812804731306956, 0.939841306316456,
0.968502119815104, 0.973986486183567, 0.72018221570783, 0.808922117204624,
0.930603357166104, 0.96226084064944, 0.967637281620371, 0.717819355809315,
0.805130424971885, 0.921538807713388, 0.956147340242261, 0.961413652937977,
0.715513085094331, 0.801426839700833, 0.912643049029987, 0.950159497830092,
0.955313577336244, 0.713261327765121, 0.797808639697236, 0.903911602905182,
0.944295194679964, 0.94933503206341, 0.711062086774516, 0.794273193409158,
0.895340118763694, 0.938552316366345, 0.943475996641087, 0.708913440721818,
0.79081795643482, 0.886924370569017, 0.932928754900547, 0.937734454949501,
0.706813540866439, 0.787440468610379, 0.878660253723646, 0.927422410718391,
0.932108397178287, 0.704760608255926, 0.784138351177934, 0.870543781976314,
0.922031194531849, 0.926595821648137, 0.702752930964936, 0.780909304033727,
0.862571084345134, 0.916753029050316, 0.921194736508511, 0.700788861441736,
0.777751103056251, 0.854738402064476, 0.911585850577083, 0.915903161316576,
0.698866813958788, 0.77466159751369, 0.847042085562406, 0.906527610486473,
0.910719128502428, 0.696985262163986, 0.771638707549953, 0.839478591474624,
0.901576276586997, 0.905640684725585, 0.695142736729139, 0.768680421748302,
0.832044479699982, 0.896729834375788, 0.90066589212762, 0.693337823092351,
0.765784794771495, 0.824736410501997, 0.891986288189406, 0.895792829485681,
0.691569159290967, 0.762949945077154, 0.817551141659994, 0.887343662256013,
0.891019593271567, 0.689835433881839, 0.760174052707016, 0.810485525673035,
0.882800001653769, 0.886344298620863, 0.6881353839457, 0.757455357148564,
0.803536507019115, 0.878353373180141, 0.88176508021654, 0.686467793172536,
0.754792155267527, 0.796701119471732, 0.874001866136701, 0.877280093091286,
0.684831490024889, 0.7521827993096, 0.789976483475408, 0.869743593033824,
0.872887513352707, 0.683225345976117, 0.749625694969754, 0.783359803581409,
0.865576690219552, 0.868585538835388, 0.681648273820716, 0.74711929952741,
0.776848365944517, 0.86149931843675, 0.864372389683703, 0.680099226053889,
0.744662120045772, 0.770439535881419, 0.857509663312525, 0.860246308869087,
0.678577193317622, 0.742252711633559, 0.764130755491001, 0.853605935783729,
0.856205562645381, 0.677081202910631, 0.739889675767395, 0.75791954133658,
0.849786372462227, 0.852248440945717, 0.67561031735961, 0.737571658673098,
0.751803482189895, 0.846049235943467, 0.84837325772426, 0.674163633049295,
0.735297349764132, 0.745780236836504, 0.842392815061733, 0.844578351246036,
0.67274027890897, 0.733065480135467, 0.739847531942042, 0.838815425095341,
0.840862084327889, 0.671339415153075, 0.730874821111148, 0.734003159978691,
0.835315407924883, 0.837222844533538, 0.66996023207371, 0.728724182843864,
0.728244977211044, 0.831891132147497, 0.83365904432554, 0.66860194888288,
0.726612412964853, 0.72257090174049, 0.828540993150013, 0.830169121176865,
0.667263812602402, 0.724538395282482, 0.716978911607115, 0.825263413143681,
0.826751537644663, 0.6659450969995, 0.722501048527904, 0.71146704294807,
0.822056841163083, 0.823404781408691, 0.664645101566158, 0.720499325146197,
0.706033388211285, 0.818919753031688, 0.820127365276744, 0.663363150540402,
0.718532210131447, 0.700676094423347, 0.815850651296407, 0.81691782715934,
0.662098591967731, 0.716598719904252, 0.695393361510352, 0.812848065133384,
0.813774730015795, 0.660850796801012, 0.714697901230176, 0.690183440670466,
0.809910550227147, 0.810696661773713, 0.659619158037194, 0.712828830177725,
0.685044632796959, 0.807036688625131, 0.807682235223833, 0.65840308988929,
0.710990611114427, 0.679975286950419, 0.804225088569508, 0.804730087892066,
0.657202026992117, 0.709182375739667, 0.674973798878868, 0.801474384308113,
0.801838881890468, 0.656015423640367, 0.707403282152963, 0.670038609584492,
0.798783235886211, 0.799007303748793, 0.654842753057613, 0.705652513956377,
0.665168203935704, 0.796150328920716, 0.796234064228217, 0.653683506694951,
0.703929279389845, 0.66036110932326, 0.793574374358407, 0.793517898118688,
0.652537193557989, 0.702232810498201, 0.655615894359165, 0.791054108219602,
0.79085756402133, 0.651403339560998, 0.700562362328734, 0.650931167617108,
0.788588291328647, 0.788251844117223, 0.650281486907035, 0.698917212158154,
0.646305576413202, 0.786175709032535, 0.785699543923806, 0.649171193492958,
0.697296658747865, 0.641737805625809, 0.78381517090886, 0.783199492040099,
0.64807203233824, 0.695700021626499, 0.63722657655324, 0.781505510464259,
0.780750539881858, 0.646983591036597, 0.694126640398684, 0.632770645808186,
0.779245584824428, 0.778351561407705, 0.645905471229425, 0.692575874079065,
0.628368804247696, 0.777034274416723, 0.776001452837246, 0.644837288100137,
0.691047100450625, 0.624019875937613, 0.7748704826463, 0.773699132362083,
0.643778669888508, 0.689539715446396, 0.619722717150336, 0.772753135566687,
0.771443539850621, 0.642729257424162, 0.688053132553661, 0.615476215394868,
0.77068118154563, 0.769233636547476, 0.641688703678407, 0.686586782239811,
0.611279288478086, 0.768653590926998, 0.767068404768254, 0.640656673333622,
0.685140111399023, 0.607130883596222, 0.766669355689472, 0.764946847590445,
0.63963284236946, 0.683712582818977, 0.603029976455569, 0.764727489102711,
0.76286798854108, 0.638616897665165, 0.682303674666839, 0.598975570421445,
0.762827025381632, 0.760830871281802, 0.637608536617296, 0.680912879993784,
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)
)

What is the exact axis value of a grid tick location?

I cannot figure out a precise value of a tick location because I do not know how the scale works. For example, in the following scenario:
> dput(df_partial_2)
structure(list(v = 8:400, Tv_partial = c(7.98105946849764, 8.73878705524418,
9.47352664242238, 10.1859798998468, 10.8768274522901, 11.546729501371,
12.1963264293038, 12.826239385031, 13.4370708532459, 14.0294052067967,
14.6038092429507, 15.1608327039841, 15.7010087825473, 16.2248546122473,
16.7328717438707, 17.2255466076639, 17.7033509620725, 18.1667423293303,
18.6161644182794, 19.0520475347892, 19.4748089801349, 19.8848534376828,
20.2825733482202, 20.6683492742624, 21.0425502536523, 21.405534142766,
21.7576479496252, 22.0992281572083, 22.4306010372483, 22.7520829547891,
23.0639806637737, 23.3665915939217, 23.6602041291518, 23.9450978777947,
24.2215439348345, 24.489805136414, 24.7501363068249, 25.0027844982076,
25.2479892231676, 25.4859826805202, 25.7169899743615, 25.941229326661,
26.1589122835664, 26.3702439156033, 26.5754230119487, 26.7746422689521,
26.9680884730723, 27.1559426783938, 27.3383803788816, 27.515571675528,
27.6876814385425, 27.8548694647289, 28.0172906301918, 28.1750950385095,
28.3284281645058, 28.4774309937505, 28.6222401579151, 28.7629880661037,
28.8998030322791, 29.0328093988977, 29.1621276568663, 29.2878745619276,
29.4101632475811, 29.5291033346404, 29.6448010375253, 29.7573592673884,
29.8668777321649, 29.9734530336404, 30.0771787616219, 30.1781455852996,
30.2764413418811, 30.3721511225791, 30.4653573560312, 30.5561398892264,
30.6445760660137, 30.7307408032637, 30.8147066647521, 30.8965439328325,
30.9763206779655, 31.0541028261659, 31.1299542244299, 31.2039367042032,
31.2761101429469, 31.3465325238588, 31.4152599938029, 31.4823469195027,
31.5478459420476, 31.611808029764, 31.6742825294991, 31.7353172163643,
31.7949583419839, 31.8532506812946, 31.9102375779375, 31.9659609882845,
32.0204615241418, 32.0737784941661, 32.1259499440361, 32.1770126954122,
32.227002383724, 32.2759534948179, 32.3238994005003, 32.3708723930087,
32.4169037184423, 32.4620236091842, 32.5062613153437, 32.5496451352497,
32.5922024450215, 32.6339597272468, 32.674942598791, 32.715175837766,
32.7546834096823, 32.7934884928088, 32.8316135027644, 32.8690801163648,
32.9059092947446, 32.9421213057798, 32.9777357458282, 33.0127715608099,
33.0472470666478, 33.0811799690861, 33.1145873829068, 33.14748585056,
33.1798913602291, 33.2118193633436, 33.2432847915594, 33.2743020732209,
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32.8440273482061, 32.8557518387685, 32.8674307616563, 32.8790639580336,
32.8906512702879, 32.9021925460985, 32.9136876361492, 32.9251363950583,
32.9365386837237, 32.9478943671477, 32.9592033175954, 32.970465412101,
32.9816805354316, 32.9928485786233, 33.0039694414233, 33.0150430301115,
33.0260692602336, 33.037048054894, 33.0479793478448, 33.0588630800318,
33.0696992040632, 33.080487680927, 33.0912284833659, 33.1019215939782,
33.1125670064116, 33.1231647251472, 33.1337147674364, 33.1442171606589,
33.1546719463397, 33.1650791758897, 33.1754389160296, 33.1857512441582,
33.1960162523946, 33.2062340452232, 33.2164047411336, 33.2265284731705,
33.2366053865426, 33.2466356433653, 33.2566194177858, 33.266556901311,
33.2764482977688, 33.2862938282037, 33.2960937274025, 33.3058482477041,
33.3155576550292, 33.3252222334887, 33.3348422803843, 33.344418112939,
33.353950061466, 33.36343847585, 33.3728837202419, 33.3822861784755,
33.3916462489552, 33.4009643497524, 33.4102409144165, 33.4194763961868,
33.4286712638407, 33.4378260070782, 33.4469411312562, 33.4560171606742,
33.4650546401982, 33.4740541300161, 33.4830162121407, 33.4919414849452,
33.5008305688532, 33.5096841003456, 33.518502738622, 33.5272871595919,
33.5360380621786, 33.5447561614472, 33.553442196504, 33.562096923572,
33.5707211220696, 33.5793155896568, 33.5878811468251, 33.5964186331457,
33.6049289120718, 33.6134128655934, 33.6218713997717, 33.6303054405085,
33.6387159368526, 33.6471038606822, 33.6554702042407, 33.6638159850243,
33.6721422404196, 33.680450034595, 33.6887404511186, 33.6970146009249,
33.7052736158521, 33.7135186542826, 33.7217508966821, 33.7299715506615,
33.7381818462813, 33.7463830416085, 33.754576417274, 33.7627632829134,
33.7709449723599, 33.7791228472345, 33.7872982948628, 33.7954727313648,
33.8036475993218, 33.811824370725, 33.8200045449252, 33.828189650849,
33.8363812475827, 33.8445809224218, 33.8527902950166, 33.8610110142303,
33.8692447615159, 33.8774932496098, 33.8857582250076, 33.8940414656565,
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34.1915794829163, 34.201835229085, 34.2121997125799, 34.2226766498556,
34.2332698488808, 34.2439832111475, 34.2548207373935, 34.2657865283575,
34.2768847936956, 34.2881198510005)), row.names = 8:400, class = "data.frame")
ggplot(df_partial_2, aes(log(log(v)))) + theme_bw() + xlab("v") + ylab(bquote(lnT[v])) + scale_x_continuous(labels = ~floor(exp(exp(.))), sec.axis=sec_axis(~., name = "ln ln v")) +
geom_line(aes(y=log(upper)), linetype="dashed") +
geom_line(aes(y=log(Tv_partial))) +
geom_line(aes(y=log(lower)), linetype="dashed")
library("grid")
grid.lines(x = unit(c(0, 0), "npc"), y = unit(c(0.05, 0.1), "npc")) # line
grid.lines(x = unit(c(1, 1), "npc"), y = unit(c(0.05, 0.1), "npc")) # line
grid.text("<- unit(c(0, 0)) is here", 0.01, .075, just=c("left", "bottom"))
grid.text("unit(c(1, 1)) is here ->", 0.84, .075, just=c("left", "bottom"))
grid.lines(x = unit(c(0.4, 0.4), "npc"), y = unit(c(0.05, 0.1), "npc")) # line
grid.text("What is the value of v at this tick?", .3, .11,just=c("left", "bottom"))
As shown in the plot, the function grid put the ticks at a location based on a scaled percentage of the entire plot panel (not the axis). In other words, unit(c(0.4, 0.4)) on x means the tick is at the 40%-60% separation of the entire plot panel, not of the axis. As a consequence, I don't know what is the actual value on the axis for the tick location.
Is there a way to figure out what is the axis value of the tick location?
Or, if I want a small tick to be add onto v = 18 in the plot, is there a way to do it?
Any help is appreciated. Thank you!

There's no consistent answer. Per the grid::unit() docs, "all drawing occurs relative to a viewport." Which means the location will change based on the viewport aspect ratio (and maybe other factors too). For instance, in your example, the tick is about 2/3 between 11 and 27. But if my viewport has a lower aspect ratio, the same code puts the tick about halfway between 11 and 27:
If you're trying to add an extra tick mark, specify breaks including the extra tick within scale_x_continuous():
ggplot(df_partial_2, aes(log(log(v)))) +
geom_line(aes(y=log(upper)), linetype="dashed") +
geom_line(aes(y=log(Tv_partial))) +
geom_line(aes(y=log(lower)), linetype="dashed") +
theme_bw() +
xlab("v") +
ylab(bquote(lnT[v])) +
scale_x_continuous(
labels = ~floor(exp(exp(.))),
breaks = c(.9, 1.1, 1.2, 1.5, 1.8),
sec.axis=sec_axis(~., breaks = c(.9, 1.1, 1.2, 1.5, 1.8), name = "ln ln v")
)

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,
211.046557515231, 211.660659043483, 212.448224315105, 213.349438246175,
212.024534137333, 215.36321273817, 216.563502088844, 217.81264042472,
217.271313915238, 218.686937568026, 220.266055783531, 221.81426953901,
223.14814591044, 224.246749618449, 225.106092990776, 225.724182191289,
226.127934007753, 226.088057285139, 225.885682917874, 225.557696874376,
225.048271742986, 257.697338382997, 223.992535511786, 223.464168937154,
223.130201385264, 222.831125965661), Y = c(150.561649721083,
150.067708443465, 150.155166858818, 149.178216605502, 149.407794945803,
148.660423032789, 148.913853668186, 148.276798619991, 148.487493893341,
147.692417390134, 148.3284785927, 147.692417390134, 147.963737246853,
147.216365333839, 147.264069924031, 145.992941364529, 145.626212327424,
144.316323788391, 144.345145311632, 143.45465962804, 118.779460351005,
143.071035215242, 143.299619709914, 142.858352250634, 142.574112400738,
141.615051368744, 141.139993158078, 140.643070343573, 140.190870582374,
140.33597204421, 140.341935117984, 139.946384557638, 140.207765958067,
139.045960417756, 139.269575684283, 138.122677828407, 138.177339338002,
137.268964433088, 137.874216421154, 137.406115129891, 138.076960929472,
137.840425669768, 138.343311558047, 137.691348825417, 138.413874597706,
137.837444132881, 138.70109598449, 138.061059399408, 138.395985376384,
137.616810403241, 138.267779290242, 137.52736429663, 138.054102480005,
137.291822882555, 137.941797923927, 137.242130601105, 137.811604146527,
137.343502855264, 137.326607479571, 135.242513195539, 137.238155218589,
138.312502343547, 139.236778778526, 138.86110513076, 139.273551066799,
138.584816045896, 138.903840492808, 137.509475075308, 137.144733729462,
135.697694493625, 135.567500716225, 134.488184363121, 135.142134787009,
134.959267191271, 135.420411563131, 134.819134957581, 135.649989903432,
135.13120248509, 136.041565081262, 135.646014520916, 136.444072561011,
135.969014350344, 136.521592520073, 135.799066747784, 136.416244883398,
135.748380620704, 136.195611153758, 135.349848523472, 135.534703810467,
134.372898270156, 134.413645940945, 133.470486439016, 133.743793986993,
133.129597388266, 133.61658174648, 133.007354375898, 133.341286507245,
132.799640639435, 133.348243426648, 132.845357538369, 133.241901944344,
132.396139314057, 132.584969983569, 131.617958186543, 131.839585761812,
130.896426259883, 130.981896983977, 129.944322147292, 129.993020583113,
128.968365739605, 128.960414974573, 127.798609434262, 128.082849284158,
127.096954420181, 127.450763464109, 126.738176148109, 127.149628238519,
126.326724057699, 127.023409843635, 126.595062377532, 127.240068190759,
126.893216066235, 127.574000322106, 127.072108279456, 127.73997254215,
127.304668156644, 128.098750814222, 127.663446428716, 128.521135206551,
128.014273935757, 128.852085801011, 128.420756798021, 129.41460242703,
128.987248806556, 129.867796033858, 129.49510392298, 129.345033233,
128.14148617627, 130.371675767766, 130.815924763933, 131.900210345182,
131.529505925561, 132.387194703396, 131.814739621087, 132.715163760969,
132.186437886336, 133.071954341783, 132.563105379731, 133.595710988271,
133.373089567373, 134.173135298725, 133.956476951601, 134.797270353743,
134.562722785297, 135.403516187438, 135.163005545218, 135.992866645441,
131.572241287609, 129.463300862852, 122.968519677278, 123.474387102444,
123.527060920781, 124.246605156184, 123.732786965986, 117.399008772312,
123.862980743386, 124.421521986889, 123.70893467089, 124.808127936574,
126.778923818898, 124.377792779213, 122.935722771521, 124.517925012903,
124.076657553623, 124.838937151073, 124.239648236781, 124.81210331909,
125.153986215469, 125.120195464083, 123.901740722918, 123.046039636341,
120.966914580454, 120.263271875116, 121.53241274336, 121.521480441441,
120.071459668717, 121.39228050967, 120.229481123729, 120.093324272555,
118.693989626911, 118.729768069555, 117.589827133082, 118.195079121148,
108.618382640018, 113.465367772695, 107.992259893742, 117.911833116881,
117.31055651133, 118.451491293432, 122.158535489636, 128.127572337464,
125.310019979223, 125.468041434236, 128.644372064548, 129.146264107198,
128.288575329363, 128.90376577372, 128.18124000143, 128.778541224465,
128.358144523394, 129.135331805279, 128.537036736615, 128.94351959888,
128.079867747271, 127.956630889274, 126.952846803975, 126.741157684996,
125.517733715686, 125.563450614621, 124.14026367388, 123.462460954896,
122.454701487081, 125.26330923466, 123.721854664067, 123.747694650421,
122.82639975233, 123.206048782611, 122.267858508827, 115.131053046914,
122.130707812024, 114.510893374412, 122.343390776632, 123.249777990288,
122.697199820559, 123.432645586025, 123.527060920781, 123.925593018014,
123.003304274293, 124.011063742109, 123.917642252982, 125.041681659391,
124.907512499475, 125.786072035519, 125.602210594152, 126.27603793062,
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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",
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"1.030101225",
"1.032310705", "1.03344968", "1.036769138", "1.037322515",
"1.041150092",
"1.041459782", "1.041961577", "1.042347697", "1.047411444",
"1.048390581",
"1.057811121", "1.060218978", "1.065395654", "1.06921167",
"1.071509648",
"1.073730469", "1.076014602", "1.077266637", "1.079983072",
"1.083003953",
"1.086196504", "1.086445657", "1.0867266", "1.0905", "1.092152628",
"1.094730942", "1.095692666", "1.1074142", "1.109534807",
"1.111154446",
"1.111188325", "1.113985094", "1.114045618", "1.128810226",
"1.129375525",
"1.132705479", "1.154833837", "1.155201819", "1.158940397",
"1.161348047",
"1.162953533", "1.175788329", "1.178036097", "1.179280397",
"1.18116463",
"1.198506534", "1.203134068", "1.207592892", "1.208610568",
"1.212525667",
"1.212841855", "1.214403157", "1.216756112", "1.228462377",
"1.23305986",
"1.241758242", "1.258212878", "1.265571914", "1.265707797",
"1.272666444",
"1.279325988", "1.289559543", "1.291191103", "1.296541003",
"1.305111821",
"1.315201411", "1.342263532", "1.344827586", "1.347944377",
"1.352831595",
"1.377717391", "1.37771934", "1.385440181", "1.403358682",
"1.411889597",
"1.412269549", "1.412544902", "1.433843384", "1.444088526",
"1.473706353",
"1.50172117", "1.508521601", "1.53030303", "1.532658694",
"1.537642783",
"1.54340949", "1.558746736", "1.595342983", "1.596774194",
"1.596969697",
"1.630653266", "1.702558635", "1.70468948", "1.718568102",
"1.740819711",
"1.760157274", "1.775510204", "1.804859813", "1.814081408",
"1.816513761",
"1.849050827", "1.870188679", "1.880195599", "1.887061404",
"1.91858679",
"1.929152149", "1.944140197", "1.946996466", "1.986547085",
"2.007683864",
"2.070983811", "2.099778271", "2.156359393", "2.159613059",
"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")

Plotting `ggplot` sorted on specific value

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 = "") +

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