Plotting more than one regression line in ggplot

Hi Jeff (and everyone),

Thank you for your response and feedback. Yes, I know what you mean - it was a blind and quick choice to use "lm" as my object name. Unfortunately, changing the object name to something else does not eliminate that error/warning message. As a result, the same error/warning appears when running it. Oddly enough, the scatter plot is just fine - it's the regression line that struggles to appear. Could there be another reason for that?
Thanks, again,


-----Original Message-----
From: Jeff Newmiller <jdnewmil at dcn.davis.ca.us>
To: rain1290 <rain1290 at aim.com>; rain1290--- via R-help <r-help at r-project.org>; r-help <r-help at R-project.org>; r-sig-geo <r-sig-geo at r-project.org>
Sent: Wed, Jun 5, 2019 10:49 am
Subject: Re: [R] Plotting more than one regression line in ggplot

Please read the Posting Guide... posting HTML on a plain text mailing list really interferes with clear communication.

If you had spent even a small amount of time working with R tutorials then you would know that "lm" is the name of a very basic, very important R function. However, you are defining your own object called "lm" that is very different indeed than the usual "lm" function. I would guess that in a clean new R workspace where you had not already run your ggplot function and assigned the result to your own "lm" object then this code might run. However, once you have run it once and try to run it again, your "method" argument gives the wrong version of "lm" to geom_smooth and you confuse it.

As the doctor said to the man pounding his own head against the wall, "If it hurts, don't do that." Avoid re-using important object names in R... some common names I see abused this way are df, data, c, t, T, and F. Your choice was unusual, but quite effective at illustrating the problem.

On June 5, 2019 7:21:57 AM PDT, rain1290--- via R-help <r-help at r-project.org> wrote:

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]]