R help - Jun 2019 - Plotting more than one regression line in ggplot

Hi David (and everyone),

Thank you for your response. I changed the column names to x and y, but the
error/warning persists:
Warning message:
Computation failed in `stat_smooth()`:
'what' must be a function or character string 
It is quite baffling as to why this is happening. Why would it work for the
scatter plot and not the regression line?

-----Original Message-----
From: David Winsemius <dwinsemius at comcast.net>
To: r-help <r-help at r-project.org>
Sent: Wed, Jun 5, 2019 12:00 pm
Subject: Re: [R] Plotting more than one regression line in ggplot


On 6/5/19 8:04 AM, rain1290--- via R-help wrote:
> 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,

TRhe error came because you did not reference the column names 
correctly. This succeeds with the data you offered:


ggplot(onepctCO2MEDIAN) +
 ???? geom_jitter(aes(x,y),
 ???????????????? colour="blue") + geom_smooth(aes(x,y), method=lm)


# At some point you changed the column names from 
(RCP1pctCO2cumulativeMedian, departurea) to (x,y) , but didn't adjust 
your code.


Best;

David.
>
> -----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]]
>>
>> ______________________________________________
>> R-help at 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 at 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.

	[[alternative HTML version deleted]]

On 6/5/19 9:37 AM, rain1290 at aim.com wrote:
> Hi David (and everyone),
>
> Thank you for your response. I changed the column names to x and y, 
> but the error/warning persists:
>
> Warning message: Computation failed in `stat_smooth()`: 'what' must
be
> a function or character string
>
> It is quite baffling as to why this is happening. Why would it work 
> for the scatter plot and not the regression line?

Since it works perfectly well on my machine, that means we are now 
lacking the required information (from you)? that is generally delivered 
via `sessionInfo()`. I get:

R version 3.5.2 (2018-12-20)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 18.04.1 LTS

Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/libopenblasp-r0.2.20.so

locale:
 ?[1] LC_CTYPE=en_US.UTF-8?????? LC_NUMERIC=C LC_TIME=en_US.UTF-8
 ?[4] LC_COLLATE=en_US.UTF-8???? LC_MONETARY=en_US.UTF-8 
LC_MESSAGES=en_US.UTF-8
 ?[7] LC_PAPER=en_US.UTF-8?????? LC_NAME=C LC_ADDRESS=C
[10] LC_TELEPHONE=C???????????? LC_MEASUREMENT=en_US.UTF-8 
LC_IDENTIFICATION=C

attached base packages:
[1] stats???? graphics? grDevices utils???? datasets? methods base

other attached packages:
[1] ggplot2_3.1.1 zoo_1.8-5

loaded via a namespace (and not attached):
 ?[1] Rcpp_1.0.1?????? lattice_0.20-38? withr_2.1.2 assertthat_0.2.1 
dplyr_0.8.0.1
 ?[6] crayon_1.3.4???? R6_2.4.0???????? grid_3.5.2 plyr_1.8.4?????? 
gtable_0.3.0
[11] magrittr_1.5???? scales_1.0.0???? pillar_1.3.1 rlang_0.3.4????? 
lazyeval_0.2.2
[16] rstudioapi_0.10? labeling_0.3???? tools_3.5.2 glue_1.3.1?????? 
purrr_0.3.2
[21] munsell_0.5.0??? yaml_2.2.0?????? compiler_3.5.2 pkgconfig_2.0.2? 
colorspace_1.4-1
[26] tidyselect_0.2.5 tibble_2.1.1

I'm also running:

RStudio
Version 1.1.463 ? ? 2009-2018 RStudio, Inc.


You should now restart a clean session, try again with just the required 
packages and report back with full code and data.


Best;

David

>
>
> -----Original Message-----
> From: David Winsemius <dwinsemius at comcast.net>
> To: r-help <r-help at r-project.org>
> Sent: Wed, Jun 5, 2019 12:00 pm
> Subject: Re: [R] Plotting more than one regression line in ggplot
>
>
> On 6/5/19 8:04 AM, rain1290--- via R-help wrote:
> > 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,
>
>
> TRhe error came because you did not reference the column names
> correctly. This succeeds with the data you offered:
>
>
> ggplot(onepctCO2MEDIAN) +
> ???? geom_jitter(aes(x,y),
> ???????????????? colour="blue") + geom_smooth(aes(x,y),
method=lm)
>
>
> # At some point you changed the column names from
> (RCP1pctCO2cumulativeMedian, departurea) to (x,y) , but didn't adjust
> your code.
>
>
> Best;
>
> David.
>
> >
> > -----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]]
> >>
> >> ______________________________________________
> >> R-help at 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 at 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.
	[[alternative HTML version deleted]]

On 6/5/19 9:57 AM, David Winsemius wrote:
> On 6/5/19 9:37 AM, rain1290 at aim.com wrote:
>> Hi David (and everyone),
>>
>> Thank you for your response. I changed the column names to x and y,
>> but the error/warning persists:
>>
>> Warning message: Computation failed in `stat_smooth()`: 'what'
must be
>> a function or character string
>>
>> It is quite baffling as to why this is happening. Why would it work
>> for the scatter plot and not the regression line?

I'll add that I can reproduce a similar error but not the one you reported:


 > lm <- ggplot(onepctCO2MEDIAN) +
+???? geom_point(aes(x,y),
+???????????????? colour="blue") + geom_smooth(aes(x,y), method=lm)
 > lm
Warning message:
Computation failed in `stat_smooth()`:
'what' must be a function or character string

Rerunning after removing the `lm` data object allows successful execution:

 ?rm(lm)
 ?ggplot(onepctCO2MEDIAN) +
 ???? geom_point(aes(x,y),
 ???????????????? colour="blue") + geom_smooth(aes(x,y), method=lm)


So it's probably related to the non-standard evaluation where a function 
or a function name can be used and if there is a function name offered, 
the ggplot evaluation model first turns it into a character string and 
then accesses a data object instead of a function.

I'm guessing this would be seen by the package maintainer in due course, 
but I'm copying him.

-- 

David
>
> Since it works perfectly well on my machine, that means we are now
> lacking the required information (from you)? that is generally delivered
> via `sessionInfo()`. I get:
>
> R version 3.5.2 (2018-12-20)
> Platform: x86_64-pc-linux-gnu (64-bit)
> Running under: Ubuntu 18.04.1 LTS
>
> Matrix products: default
> BLAS: /usr/lib/x86_64-linux-gnu/openblas/libblas.so.3
> LAPACK: /usr/lib/x86_64-linux-gnu/libopenblasp-r0.2.20.so
>
> locale:
>   ?[1] LC_CTYPE=en_US.UTF-8?????? LC_NUMERIC=C LC_TIME=en_US.UTF-8
>   ?[4] LC_COLLATE=en_US.UTF-8???? LC_MONETARY=en_US.UTF-8
> LC_MESSAGES=en_US.UTF-8
>   ?[7] LC_PAPER=en_US.UTF-8?????? LC_NAME=C LC_ADDRESS=C
> [10] LC_TELEPHONE=C???????????? LC_MEASUREMENT=en_US.UTF-8
> LC_IDENTIFICATION=C
>
> attached base packages:
> [1] stats???? graphics? grDevices utils???? datasets? methods base
>
> other attached packages:
> [1] ggplot2_3.1.1 zoo_1.8-5
>
> loaded via a namespace (and not attached):
>   ?[1] Rcpp_1.0.1?????? lattice_0.20-38? withr_2.1.2 assertthat_0.2.1
> dplyr_0.8.0.1
>   ?[6] crayon_1.3.4???? R6_2.4.0???????? grid_3.5.2 plyr_1.8.4
> gtable_0.3.0
> [11] magrittr_1.5???? scales_1.0.0???? pillar_1.3.1 rlang_0.3.4
> lazyeval_0.2.2
> [16] rstudioapi_0.10? labeling_0.3???? tools_3.5.2 glue_1.3.1
> purrr_0.3.2
> [21] munsell_0.5.0??? yaml_2.2.0?????? compiler_3.5.2 pkgconfig_2.0.2
> colorspace_1.4-1
> [26] tidyselect_0.2.5 tibble_2.1.1
>
> I'm also running:
>
> RStudio
> Version 1.1.463 ? ? 2009-2018 RStudio, Inc.
>
>
> You should now restart a clean session, try again with just the required
> packages and report back with full code and data.
>
>
> Best;
>
> David
>
>
>>
>> -----Original Message-----
>> From: David Winsemius <dwinsemius at comcast.net>
>> To: r-help <r-help at r-project.org>
>> Sent: Wed, Jun 5, 2019 12:00 pm
>> Subject: Re: [R] Plotting more than one regression line in ggplot
>>
>>
>> On 6/5/19 8:04 AM, rain1290--- via R-help wrote:
>>> 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,
>>
>> TRhe error came because you did not reference the column names
>> correctly. This succeeds with the data you offered:
>>
>>
>> ggplot(onepctCO2MEDIAN) +
>>  ???? geom_jitter(aes(x,y),
>>  ???????????????? colour="blue") + geom_smooth(aes(x,y),
method=lm)
>>
>>
>> # At some point you changed the column names from
>> (RCP1pctCO2cumulativeMedian, departurea) to (x,y) , but didn't
adjust
>> your code.
>>
>>
>> Best;
>>
>> David.
>>
>>> -----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]]
>>>>
>>>> ______________________________________________
>>>> R-help at 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 at 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.
> 	[[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at 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.