[R] Plotting more than one regression line in ggplot

Rui Barradas ru|pb@rr@d@@ @end|ng |rom @@po@pt
Wed Jun 5 17:15:01 CEST 2019


Hello,

And please don't cross post. You have asked both

r-help using r-project.org and
r-sig-geo using r-project.org

when you should have asked just one of them.

This is a question for r-help using r-project.org

Rui Barradas

Às 15:52 de 05/06/19, Rui Barradas escreveu:
> Hello,
> 
> This is pretty basic ggplot.
> 
> 
> lm1 <- ggplot(onepctCO2MEDIAN, aes(x, y)) +
>    geom_point(colour = 'blue') +
>    geom_smooth(method = 'lm')
> 
> lm1
> 
> 
> If you want to combine several datasets, you will have to have a 
> variable telling which dataset is which. In the example below, this is 
> column 'id'.
> 
> 
> onepctCO2MEDIAN2 <- onepctCO2MEDIAN
> onepctCO2MEDIAN2$y <- jitter(onepctCO2MEDIAN2$y) + 2
> onepctCO2MEDIAN$id <- 1
> onepctCO2MEDIAN2$id <- 2
> df2 <- rbind(onepctCO2MEDIAN, onepctCO2MEDIAN2)
> 
> ggplot(df2, aes(x, y, group = id, colour = factor(id))) +
>    geom_point() +
>    geom_smooth(method = 'lm')
> 
> 
> Hope this helps,
> 
> Rui Barradas
> 
> Às 15:21 de 05/06/19, rain1290--- via R-help escreveu:
>> I am trying to plot, using ggplot, a series of scatter plots with 
>> regression lines for several datasets. I started with the following 
>> dataset, "onepectCO2MEDIAN". The data for this dataset is as follows:
>>      onepctCO2MEDIAN
>>                      x          y
>>      layer.1   0.000000000  0.0000000
>>      layer.2   0.006794447  4.9002490
>>      layer.3   0.014288058  0.1608000
>>      layer.4   0.022087920  6.6349133
>>      layer.5   0.030797357 -1.2429506
>>      layer.6   0.038451072  1.5643374
>>      layer.7   0.048087904 -2.2659035
>>      layer.8   0.058677729  2.2070045
>>      layer.9   0.069261406 -2.3677001
>>      layer.10  0.080524530 -1.0913506
>>      layer.11  0.092760246  0.4099940
>>      layer.12  0.103789609 -0.1259727
>>      layer.13  0.116953168 -2.4138253
>>      layer.14  0.129253298  7.0890257
>>      layer.15  0.141710050 -0.7593539
>>      layer.16  0.156002052  0.0454416
>>      layer.17  0.170648172 -1.5349683
>>      layer.18  0.185318425  6.5524201
>>      layer.19  0.199463055 -0.8312563
>>      layer.20  0.213513337 -2.5099183
>>      layer.21  0.228839271  0.1365968
>>      layer.22  0.246981293 -1.3719845
>>      layer.23  0.263012767 -0.8712988
>>      layer.24  0.278505564  0.6632584
>>      layer.25  0.293658361  0.7938036
>>      layer.26  0.310747266  3.4880637
>>      layer.27  0.325990349 -4.4612208
>>      layer.28  0.342517540  0.0871734
>>      layer.29  0.362751633 -1.4171578
>>      layer.30  0.380199537 -0.9956508
>>      layer.31  0.394992948  0.3215526
>>      layer.32  0.414373398  3.1403866
>>      layer.33  0.430690214 -0.7376099
>>      layer.34  0.449738145 -2.4860541
>>      layer.35  0.470167458 -3.4235858
>>      layer.36  0.489019871  0.4824748
>>      layer.37  0.507242471 -0.9785386
>>      layer.38  0.524314284  8.5359684
>>      layer.39  0.543750525  5.4844742
>>      layer.40  0.564234197  3.2149367
>>      layer.41  0.583679616  3.9168916
>>      layer.42  0.601459444  4.4907020
>>      layer.43  0.619924664  6.5410410
>>      layer.44  0.639932007  4.8068650
>>      layer.45  0.661347181  8.1510170
>>      layer.46  0.684117317  0.2697413
>>      layer.47  0.704829752 -0.1807501
>>      layer.48  0.725045770  9.7181249
>>      layer.49  0.745165825  1.5406466
>>      layer.50  0.765016139 -1.6476041
>>      layer.51  0.783461511  4.8024603
>>      layer.52  0.806382924  4.0421516
>>      layer.53  0.829241335  9.3756512
>>      layer.54  0.849924415  5.3305050
>>      layer.55  0.871352434  7.5445803
>>      layer.56  0.893632233  6.4679547
>>      layer.57  0.916052133  2.8096065
>>      layer.58  0.938579470  5.3921661
>>      layer.59  0.959907651  7.2043689
>>      layer.60  0.981643587  3.3350806
>>      layer.61  1.004116774  8.8690707
>>      layer.62  1.028363466  1.7861299
>>      layer.63  1.054009140  6.2555038
>>      layer.64  1.072440803  7.6079236
>>      layer.65  1.094457805  7.6871483
>>      layer.66  1.123176277  4.7787764
>>      layer.67  1.149430871 12.7110502
>>      layer.68  1.170912921 -0.7156284
>>      layer.69  1.196743071  1.6490899
>>      layer.70  1.218625903  3.0363024
>>      layer.71  1.241868377  4.2974769
>>      layer.72  1.267941594  1.9543778
>>      layer.73  1.290708780  3.9986964
>>      layer.74  1.313222289  4.5179472
>>      layer.75  1.339045882  0.9337905
>>      layer.76  1.362803459  3.3050770
>>      layer.77  1.384450197  3.5422970
>>      layer.78  1.409720302  5.9973660
>>      layer.79  1.435851157  0.5081869
>>      layer.80  1.455592215  7.9661630
>>      layer.81  1.479495347  9.9460496
>>      layer.82  1.506051958  3.7908372
>>      layer.83  1.525728464  2.5735847
>>      layer.84  1.549362063 10.1404974
>>      layer.85  1.573440671 13.7408304
>>      layer.86  1.600278735  0.9335771
>>      layer.87  1.623879492  9.7588742
>>      layer.88  1.650029302  1.2769395
>>      layer.89  1.672362328 13.4970906
>>      layer.90  1.700221121 10.2087502
>>      layer.91  1.724793375  1.6811275
>>      layer.92  1.751070559  6.1178992
>>      layer.93  1.778022110 -0.1567626
>>      layer.94  1.803022087  3.8237479
>>      layer.95  1.830668867  4.4331468
>>      layer.96  1.855736911  5.9790707
>>      layer.97  1.882615030 11.3104333
>>      layer.98  1.909218490  8.2142607
>>      layer.99  1.938130021 15.3209674
>>      layer.100 1.963727593  5.8178217
>>      layer.101 1.993271947  9.6004907
>>      layer.102 2.022548139  3.4063646
>>      layer.103 2.050679922  4.7375010
>>      layer.104 2.078064442  3.0133019
>>      layer.105 2.104113460  5.5659522
>>      layer.106 2.133597612 12.0346333
>>      layer.107 2.164026260 -0.4028320
>>      layer.108 2.194852829 10.5996780
>>      layer.109 2.224257946  5.4479584
>>      layer.110 2.252194643  4.7052374
>>      layer.111 2.277335048 14.0962019
>>      layer.112 2.304058313  5.7149016
>>      layer.113 2.330930233  3.7780072
>>      layer.114 2.357022762  4.4120620
>>      layer.115 2.386489272  4.1866085
>>      layer.116 2.417503953  6.9078802
>>      layer.117 2.448524356  2.7825739
>>      layer.118 2.478698969  7.6171786
>>      layer.119 2.510175705 10.2410603
>>      layer.120 2.539697886  8.1820711
>>      layer.121 2.567915559  4.8275494
>>      layer.122 2.597463250 19.1624883
>>      layer.123 2.627518773 16.0677109
>>      layer.124 2.658759236 12.5897081
>>      layer.125 2.692401528  9.2907988
>>      layer.126 2.721903205  7.4262502
>>      layer.127 2.753021359  9.3902518
>>      layer.128 2.786313415 12.6193550
>>      layer.129 2.819564104 11.1121040
>>      layer.130 2.850823164 15.7907100
>>      layer.131 2.880394101 10.7425287
>>      layer.132 2.911391258  7.7971430
>>      layer.133 2.942965150  8.8060858
>>      layer.134 2.974468350 17.5606266
>>      layer.135 3.008983612 17.3088605
>>      layer.136 3.040015221 13.4500543
>>      layer.137 3.072668672 14.6377884
>>      layer.138 3.105982423  8.0798552dput(onepctCO2MEDIAN)    
>> dput(onepctCO2MEDIAN)
>>      structure(list(x = c(0, 0.00679444684647024, 0.014288058038801,
>>      0.0220879195258021, 
>> 0.0307973567396402,0.0384510718286037,0.0480879042297602,
>>      0.0586777292191982, 0.0692614056169987, 
>> 0.080524530261755,0.0927602462470531,
>>      0.103789608925581, 0.116953168064356, 0.129253298044205, 
>> 0.141710050404072,
>>      0.156002052128315, 0.170648172497749, 0.185318425297737, 
>> 0.199463054537773,
>>      0.21351333707571, 0.22883927077055, 0.246981292963028, 
>> 0.263012766838074,
>>      0.278505563735962, 0.29365836083889, 0.310747265815735, 
>> 0.325990349054337,
>>      0.342517539858818, 0.362751632928848, 0.380199536681175, 
>> 0.39499294757843,
>>      0.414373397827148, 0.430690214037895, 0.449738144874573, 
>> 0.470167458057404,
>>      0.489019870758057, 0.507242470979691, 0.524314284324646, 
>> 0.543750524520874,
>>      0.56423419713974, 0.583679616451263, 0.601459443569183, 
>> 0.619924664497375,
>>      0.639932006597519, 0.661347180604935, 0.684117317199707, 
>> 0.704829752445221,
>>      0.725045770406723, 0.745165824890137, 0.765016138553619, 
>> 0.783461511135101,
>>      0.806382924318314, 0.829241335391998, 0.84992441534996, 
>> 0.871352434158325,
>>      0.893632233142853, 0.916052132844925, 0.938579469919205, 
>> 0.959907650947571,
>>      0.981643587350845, 1.00411677360535, 1.02836346626282, 
>> 1.05400913953781,
>>      1.07244080305099, 1.09445780515671, 1.12317627668381, 
>> 1.14943087100983,
>>      1.17091292142868, 1.19674307107925, 1.21862590312958, 
>> 1.24186837673187,
>>      1.26794159412384, 1.2907087802887, 1.31322228908539, 
>> 1.33904588222504,
>>      1.36280345916748, 1.38445019721985, 1.40972030162811, 
>> 1.43585115671158,
>>      1.45559221506119, 1.47949534654617, 1.50605195760727, 
>> 1.52572846412659,
>>      1.5493620634079, 1.5734406709671, 1.60027873516083, 
>> 1.62387949228287,
>>      1.65002930164337, 1.67236232757568, 1.70022112131119, 
>> 1.72479337453842,
>>      1.75107055902481, 1.77802211046219, 1.80302208662033, 
>> 1.83066886663437,
>>      1.85573691129684, 1.88261502981186, 1.90921849012375, 
>> 1.93813002109528,
>>      1.96372759342194, 1.99327194690704, 2.02254813909531, 
>> 2.05067992210388,
>>      2.07806444168091, 2.1041134595871, 2.13359761238098, 
>> 2.16402626037598,
>>      2.19485282897949, 2.2242579460144, 2.25219464302063, 
>> 2.27733504772186,
>>      2.30405831336975, 2.33093023300171, 2.35702276229858, 
>> 2.38648927211761,
>>      2.41750395298004, 2.44852435588837, 2.47869896888733, 
>> 2.51017570495605,
>>      2.53969788551331, 2.567915558815, 2.59746325016022, 
>> 2.62751877307892,
>>      2.65875923633575, 2.69240152835846, 2.72190320491791, 
>> 2.75302135944366,
>>      2.78631341457367, 2.8195641040802, 2.85082316398621, 
>> 2.88039410114288,
>>      2.91139125823975, 2.94296514987946, 2.97446835041046, 
>> 3.00898361206055,
>>      3.04001522064209, 3.07266867160797, 3.10598242282867), y = c(0,
>>      4.90024901723162, 0.160799993152722, 6.63491326258641, 
>> -1.24295055804536,
>>      1.56433744259162, -2.26590352245208, 2.20700446463354, 
>> -2.36770012911069,
>>      -1.09135061899174, 0.409993989292701, -0.125972681525582, 
>> -2.41382533818026,
>>      7.08902570153028, -0.759353880417294, 0.0454415959640926, 
>> -1.53496826259972,
>>      6.55242014096194, -0.831256280861552, -2.50991825629084, 
>> 0.136596820654013,
>>      -1.37198445498419, -0.871298832596736, 0.663258363762466, 
>> 0.793803634291308,
>>      3.48806373666998, -4.46122081238949, 0.0871733966938564, 
>> -1.41715777257774,
>>      -0.995650815648318, 0.32155262317503, 3.14038657369241, 
>> -0.737609879885404,
>>      -2.48605406511292, -3.423585843908, 0.482474753780281, 
>> -0.978538630093809,
>>      8.53596837794201, 5.48447420320695, 3.21493665820644, 
>> 3.91689160157513,
>>      4.49070195980797, 6.54104103157039, 4.80686500146557, 
>> 8.15101701282067,
>>      0.26974132191657, -0.180750068063062, 9.71812491230244, 
>> 1.54064657400204,
>>      -1.64760408795688, 4.80246028991894, 4.04215159914344, 
>> 9.37565121768513,
>>      5.33050496938428, 7.54458026088508, 6.46795470819342, 
>> 2.80960651433971,
>>      5.39216613235986, 7.20436888038562, 3.3350806460997, 
>> 8.86907069895943,
>>      1.78612988613659, 6.25550382050395, 7.60792364896564, 
>> 7.68714830528144,
>>      4.77877638957615, 12.7110501777314, -0.715628443181046, 
>> 1.64908991824022,
>>      3.03630240714679, 4.29747688442346, 1.95437780501881, 
>> 3.99869636910933,
>>      4.51794724689848, 0.933790484492299, 3.30507700050003, 
>> 3.5422970157433,
>>      5.99736597322524, 0.508186860060022, 7.96616300581067, 
>> 9.94604963036295,
>>      3.79083717222623, 2.57358468532258, 10.1404974171776, 
>> 13.7408303595752,
>>      0.933577123801399, 9.75887417074129, 1.27693947132921, 
>> 13.4970905965787,
>>      10.2087501765735, 1.68112753028756, 6.1178991508927, 
>> -0.156762622680077,
>>      3.82374791691426, 4.43314678736265, 5.97907067167507, 
>> 11.3104332518482,
>>      8.21426074201525, 15.320967360602, 5.81782169471483, 
>> 9.6004907412354,
>>      3.40636455909704, 4.73750103921864, 3.0133019468806, 
>> 5.56595224859066,
>>      12.0346332527215, -0.40283199827104, 10.5996779538754, 
>> 5.44795836991128,
>>      4.70523736412729, 14.096201892183, 5.71490161813391, 
>> 3.77800720810782,
>>      4.41206200639436, 4.18660847858423, 6.90788020044911, 
>> 2.78257393345915,
>>      7.61717857379431, 10.2410602647684, 8.18207106836167, 
>> 4.82754943871433,
>>      19.1624882857155, 16.0677109398509, 12.589708067017, 
>> 9.29079879799404,
>>      7.42625019725314, 9.39025179806185, 12.6193550331438, 
>> 11.1121039747257,
>>      15.7907099734986, 10.7425286789233, 7.79714300307344, 
>> 8.80608578166101,
>>      17.5606266346039, 17.3088604929222, 13.4500543478523, 
>> 14.6377884248645,
>>      8.07985518296064)), class = "data.frame", row.names = c("layer.1",
>>      "layer.2", "layer.3", "layer.4", "layer.5", "layer.6", "layer.7",
>>      "layer.8", "layer.9", "layer.10", "layer.11", "layer.12", 
>> "layer.13",
>>      "layer.14", "layer.15", "layer.16", "layer.17", "layer.18", 
>> "layer.19",
>>      "layer.20", "layer.21", "layer.22", "layer.23", "layer.24", 
>> "layer.25",
>>      "layer.26", "layer.27", "layer.28", "layer.29", "layer.30", 
>> "layer.31",
>>      "layer.32", "layer.33", "layer.34", "layer.35", "layer.36", 
>> "layer.37",
>>      "layer.38", "layer.39", "layer.40", "layer.41", "layer.42", 
>> "layer.43",
>>      "layer.44", "layer.45", "layer.46", "layer.47", "layer.48", 
>> "layer.49",
>>      "layer.50", "layer.51", "layer.52", "layer.53", "layer.54", 
>> "layer.55",
>>      "layer.56", "layer.57", "layer.58", "layer.59", "layer.60", 
>> "layer.61",
>>      "layer.62", "layer.63", "layer.64", "layer.65", "layer.66", 
>> "layer.67",
>>      "layer.68", "layer.69", "layer.70", "layer.71", "layer.72", 
>> "layer.73",
>>      "layer.74", "layer.75", "layer.76", "layer.77", "layer.78", 
>> "layer.79",
>>      "layer.80", "layer.81", "layer.82", "layer.83", "layer.84", 
>> "layer.85",
>>      "layer.86", "layer.87", "layer.88", "layer.89", "layer.90", 
>> "layer.91",
>>      "layer.92", "layer.93", "layer.94", "layer.95", "layer.96", 
>> "layer.97",
>>      "layer.98", "layer.99", "layer.100", "layer.101", "layer.102",
>>      "layer.103", "layer.104", "layer.105", "layer.106", "layer.107",
>>      "layer.108", "layer.109", "layer.110", "layer.111", "layer.112",
>>      "layer.113", "layer.114", "layer.115", "layer.116", "layer.117",
>>      "layer.118", "layer.119", "layer.120", "layer.121", "layer.122",
>>      "layer.123", "layer.124", "layer.125", "layer.126", "layer.127",
>>      "layer.128", "layer.129", "layer.130", "layer.131", "layer.132",
>>      "layer.133", "layer.134", "layer.135", "layer.136", "layer.137",
>>      "layer.138"))
>> I started with the following to generate the first regression line and 
>> scatter plot:    lm<-ggplot(onepctCO2MEDIAN) +
>>      geom_jitter(aes(RCP1pctCO2cumulativeMedian[1:138], departurea),
>>      colour="blue") + geom_smooth(aes(RCP1pctCO2cumulativeMedian[1:138],
>>      departurea), method=lm)
>> But I receive this error:    Warning message:
>>      Computation failed in `stat_smooth()`:
>>      'what' must be a function or character string
>> A blue scatter plot is successfully generated, but the problem is that 
>> the regression line does not appear, presumably related to the above 
>> warning.
>> Is there a reason for this? I would appreciate any assistance!
>>     [[alternative HTML version deleted]]
>>
>> ______________________________________________
>> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide 
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
> 
> ______________________________________________
> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide 
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.



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