[R] Plotting more than one regression line in ggplot
PIKAL Petr
petr@p|k@| @end|ng |rom prechez@@cz
Thu Jun 6 08:42:31 CEST 2019
Hi
It is probably time to consult documentation, including R-Intro. GGplot paradigm is that you have set of values (x,y) and factor variable(s) used for changing colour, size, plotting character or several other plot items.
so something like
pl <- ggplot(NewestdataULTRA, aes(x=x, y=value, colour=L1))
pl +geom_point()+geom_smooth(method="lm")
Cheers
Petr
> -----Original Message-----
> From: R-help <r-help-bounces using r-project.org> On Behalf Of rain1290--- via R-
> help
> Sent: Wednesday, June 5, 2019 11:37 PM
> To: ruipbarradas using sapo.pt; r-help using R-project.org; r-sig-geo using r-project.org
> Subject: Re: [R] Plotting more than one regression line in ggplot
>
> Hi Rui (and everyone),
>
> Thank you so much for your response! Much appreciated!
> What if I wanted I create several regression lines and scatter plots in the same
> ggplot using a "melted" dataset? I would like to create a scatter plot and
> regression line for both the objects of "onepctCO2MEDIAN" and
> "RCP8.5MEDIANThis melted dataset looks like this:
>
> >NewestdataUltra
> x variable value L1
> 1 0.000000000 y 0.00000000 onepctCO2MEDIAN
> 2 0.006794447 y 4.90024902 onepctCO2MEDIAN
> 3 0.014288058 y 0.16079999 onepctCO2MEDIAN
> 4 0.022087920 y 6.63491326 onepctCO2MEDIAN
> 5 0.030797357 y -1.24295056 onepctCO2MEDIAN
> 6 0.038451072 y 1.56433744 onepctCO2MEDIAN
> 7 0.048087904 y -2.26590352 onepctCO2MEDIAN
> 8 0.058677729 y 2.20700446 onepctCO2MEDIAN
> 9 0.069261406 y -2.36770013 onepctCO2MEDIAN
> 10 0.080524530 y -1.09135062 onepctCO2MEDIAN
> 11 0.092760246 y 0.40999399 onepctCO2MEDIAN
> 12 0.103789609 y -0.12597268 onepctCO2MEDIAN
> 13 0.116953168 y -2.41382534 onepctCO2MEDIAN
> 14 0.129253298 y 7.08902570 onepctCO2MEDIAN
> 15 0.141710050 y -0.75935388 onepctCO2MEDIAN
> 16 0.156002052 y 0.04544160 onepctCO2MEDIAN
> 17 0.170648172 y -1.53496826 onepctCO2MEDIAN
> 18 0.185318425 y 6.55242014 onepctCO2MEDIAN
> 19 0.199463055 y -0.83125628 onepctCO2MEDIAN
> 20 0.213513337 y -2.50991826 onepctCO2MEDIAN
> 21 0.228839271 y 0.13659682 onepctCO2MEDIAN
> 22 0.246981293 y -1.37198445 onepctCO2MEDIAN
> 23 0.263012767 y -0.87129883 onepctCO2MEDIAN
> 24 0.278505564 y 0.66325836 onepctCO2MEDIAN
> 25 0.293658361 y 0.79380363 onepctCO2MEDIAN
> 26 0.310747266 y 3.48806374 onepctCO2MEDIAN
> 27 0.325990349 y -4.46122081 onepctCO2MEDIAN
> 28 0.342517540 y 0.08717340 onepctCO2MEDIAN
> 29 0.362751633 y -1.41715777 onepctCO2MEDIAN
> 30 0.380199537 y -0.99565082 onepctCO2MEDIAN
> 31 0.394992948 y 0.32155262 onepctCO2MEDIAN
> 32 0.414373398 y 3.14038657 onepctCO2MEDIAN
> 33 0.430690214 y -0.73760988 onepctCO2MEDIAN
> 34 0.449738145 y -2.48605407 onepctCO2MEDIAN
> 35 0.470167458 y -3.42358584 onepctCO2MEDIAN
> 36 0.489019871 y 0.48247475 onepctCO2MEDIAN
> 37 0.507242471 y -0.97853863 onepctCO2MEDIAN
> 38 0.524314284 y 8.53596838 onepctCO2MEDIAN
> 39 0.543750525 y 5.48447420 onepctCO2MEDIAN
> 40 0.564234197 y 3.21493666 onepctCO2MEDIAN
> 41 0.583679616 y 3.91689160 onepctCO2MEDIAN
> 42 0.601459444 y 4.49070196 onepctCO2MEDIAN
> 43 0.619924664 y 6.54104103 onepctCO2MEDIAN
> 44 0.639932007 y 4.80686500 onepctCO2MEDIAN
> 45 0.661347181 y 8.15101701 onepctCO2MEDIAN
> 46 0.684117317 y 0.26974132 onepctCO2MEDIAN
> 47 0.704829752 y -0.18075007 onepctCO2MEDIAN
> 48 0.725045770 y 9.71812491 onepctCO2MEDIAN
> 49 0.745165825 y 1.54064657 onepctCO2MEDIAN
> 50 0.765016139 y -1.64760409 onepctCO2MEDIAN
> 51 0.783461511 y 4.80246029 onepctCO2MEDIAN
> 52 0.806382924 y 4.04215160 onepctCO2MEDIAN
> 53 0.829241335 y 9.37565122 onepctCO2MEDIAN
> 54 0.849924415 y 5.33050497 onepctCO2MEDIAN
> 55 0.871352434 y 7.54458026 onepctCO2MEDIAN
> 56 0.893632233 y 6.46795471 onepctCO2MEDIAN
> 57 0.916052133 y 2.80960651 onepctCO2MEDIAN
> 58 0.938579470 y 5.39216613 onepctCO2MEDIAN
> 59 0.959907651 y 7.20436888 onepctCO2MEDIAN
> 60 0.981643587 y 3.33508065 onepctCO2MEDIAN
> 61 1.004116774 y 8.86907070 onepctCO2MEDIAN
> 62 1.028363466 y 1.78612989 onepctCO2MEDIAN
> 63 1.054009140 y 6.25550382 onepctCO2MEDIAN
> 64 1.072440803 y 7.60792365 onepctCO2MEDIAN
> 65 1.094457805 y 7.68714831 onepctCO2MEDIAN
> 66 1.123176277 y 4.77877639 onepctCO2MEDIAN
> 67 1.149430871 y 12.71105018 onepctCO2MEDIAN
> 68 1.170912921 y -0.71562844 onepctCO2MEDIAN
> 69 1.196743071 y 1.64908992 onepctCO2MEDIAN
> 70 1.218625903 y 3.03630241 onepctCO2MEDIAN
> 71 1.241868377 y 4.29747688 onepctCO2MEDIAN
> 72 1.267941594 y 1.95437781 onepctCO2MEDIAN
> 73 1.290708780 y 3.99869637 onepctCO2MEDIAN
> 74 1.313222289 y 4.51794725 onepctCO2MEDIAN
> 75 1.339045882 y 0.93379048 onepctCO2MEDIAN
> 76 1.362803459 y 3.30507700 onepctCO2MEDIAN
> 77 1.384450197 y 3.54229702 onepctCO2MEDIAN
> 78 1.409720302 y 5.99736597 onepctCO2MEDIAN
> 79 1.435851157 y 0.50818686 onepctCO2MEDIAN
> 80 1.455592215 y 7.96616301 onepctCO2MEDIAN
> 81 1.479495347 y 9.94604963 onepctCO2MEDIAN
> 82 1.506051958 y 3.79083717 onepctCO2MEDIAN
> 83 1.525728464 y 2.57358469 onepctCO2MEDIAN
> 84 1.549362063 y 10.14049742 onepctCO2MEDIAN
> 85 1.573440671 y 13.74083036 onepctCO2MEDIAN
> 86 1.600278735 y 0.93357712 onepctCO2MEDIAN
> 87 1.623879492 y 9.75887417 onepctCO2MEDIAN
> 88 1.650029302 y 1.27693947 onepctCO2MEDIAN
> 89 1.672362328 y 13.49709060 onepctCO2MEDIAN
> 90 1.700221121 y 10.20875018 onepctCO2MEDIAN
> 91 1.724793375 y 1.68112753 onepctCO2MEDIAN
> 92 1.751070559 y 6.11789915 onepctCO2MEDIAN
> 93 1.778022110 y -0.15676262 onepctCO2MEDIAN
> 94 1.803022087 y 3.82374792 onepctCO2MEDIAN
> 95 1.830668867 y 4.43314679 onepctCO2MEDIAN
> 96 1.855736911 y 5.97907067 onepctCO2MEDIAN
> 97 1.882615030 y 11.31043325 onepctCO2MEDIAN
> 98 1.909218490 y 8.21426074 onepctCO2MEDIAN
> 99 1.938130021 y 15.32096736 onepctCO2MEDIAN
> 100 1.963727593 y 5.81782169 onepctCO2MEDIAN
> 101 1.993271947 y 9.60049074 onepctCO2MEDIAN
> 102 2.022548139 y 3.40636456 onepctCO2MEDIAN
> 103 2.050679922 y 4.73750104 onepctCO2MEDIAN
> 104 2.078064442 y 3.01330195 onepctCO2MEDIAN
> 105 2.104113460 y 5.56595225 onepctCO2MEDIAN
> 106 2.133597612 y 12.03463325 onepctCO2MEDIAN
> 107 2.164026260 y -0.40283200 onepctCO2MEDIAN
> 108 2.194852829 y 10.59967795 onepctCO2MEDIAN
> 109 2.224257946 y 5.44795837 onepctCO2MEDIAN
> 110 2.252194643 y 4.70523736 onepctCO2MEDIAN
> 111 2.277335048 y 14.09620189 onepctCO2MEDIAN
> 112 2.304058313 y 5.71490162 onepctCO2MEDIAN
> 113 2.330930233 y 3.77800721 onepctCO2MEDIAN
> 114 2.357022762 y 4.41206201 onepctCO2MEDIAN
> 115 2.386489272 y 4.18660848 onepctCO2MEDIAN
> 116 2.417503953 y 6.90788020 onepctCO2MEDIAN
> 117 2.448524356 y 2.78257393 onepctCO2MEDIAN
> 118 2.478698969 y 7.61717857 onepctCO2MEDIAN
> 119 2.510175705 y 10.24106026 onepctCO2MEDIAN
> 120 2.539697886 y 8.18207107 onepctCO2MEDIAN
> 121 2.567915559 y 4.82754944 onepctCO2MEDIAN
> 122 2.597463250 y 19.16248829 onepctCO2MEDIAN
> 123 2.627518773 y 16.06771094 onepctCO2MEDIAN
> 124 2.658759236 y 12.58970807 onepctCO2MEDIAN
> 125 2.692401528 y 9.29079880 onepctCO2MEDIAN
> 126 2.721903205 y 7.42625020 onepctCO2MEDIAN
> 127 2.753021359 y 9.39025180 onepctCO2MEDIAN
> 128 2.786313415 y 12.61935503 onepctCO2MEDIAN
> 129 2.819564104 y 11.11210397 onepctCO2MEDIAN
> 130 2.850823164 y 15.79070997 onepctCO2MEDIAN
> 131 2.880394101 y 10.74252868 onepctCO2MEDIAN
> 132 2.911391258 y 7.79714300 onepctCO2MEDIAN
> 133 2.942965150 y 8.80608578 onepctCO2MEDIAN
> 134 2.974468350 y 17.56062663 onepctCO2MEDIAN
> 135 3.008983612 y 17.30886049 onepctCO2MEDIAN
> 136 3.040015221 y 13.45005435 onepctCO2MEDIAN
> 137 3.072668672 y 14.63778842 onepctCO2MEDIAN
> 138 3.105982423 y 8.07985518 onepctCO2MEDIAN
> 139 0.467429527 y -1.55704023 RCP4.5MEDIAN
> 140 0.478266196 y -3.19367515 RCP4.5MEDIAN
> 141 0.489205229 y -2.44452679 RCP4.5MEDIAN
> 142 0.500039143 y 0.87504367 RCP4.5MEDIAN
> 143 0.511021115 y -0.39185002 RCP4.5MEDIAN
> 144 0.519874968 y -4.18935168 RCP4.5MEDIAN
> 145 0.528508358 y -3.64179524 RCP4.5MEDIAN
> 146 0.537377594 y -2.58167128 RCP4.5MEDIAN
> 147 0.546194211 y 2.20583694 RCP4.5MEDIAN
> 148 0.554720591 y -8.57764597 RCP4.5MEDIAN
> 149 0.563289814 y 2.88442536 RCP4.5MEDIAN
> 150 0.572032790 y -3.90829882 RCP4.5MEDIAN
> 151 0.580939066 y -3.39269048 RCP4.5MEDIAN
> 152 0.590921065 y -4.60849867 RCP4.5MEDIAN
> 153 0.601575326 y -1.62572657 RCP4.5MEDIAN
> 154 0.612425555 y 1.14198465 RCP4.5MEDIAN
> 155 0.623773319 y -3.38454122 RCP4.5MEDIAN
> 156 0.635363359 y 2.43414265 RCP4.5MEDIAN
> 157 0.646722666 y 3.30007615 RCP4.5MEDIAN
> 158 0.658285673 y -0.79555442 RCP4.5MEDIAN
> 159 0.670250852 y -2.05220500 RCP4.5MEDIAN
> 160 0.681702690 y -5.56808946 RCP4.5MEDIAN
> 161 0.693531145 y 2.24168605 RCP4.5MEDIAN
> 162 0.706016061 y -4.83673351 RCP4.5MEDIAN
> 163 0.718231249 y 0.40086819 RCP4.5MEDIAN
> 164 0.730190911 y -1.98026992 RCP4.5MEDIAN
> 165 0.741269845 y 0.39963115 RCP4.5MEDIAN
> 166 0.751000321 y -0.83241777 RCP4.5MEDIAN
> 167 0.760886972 y -1.66101404 RCP4.5MEDIAN
> 168 0.771137164 y -1.05452982 RCP4.5MEDIAN
> 169 0.781856383 y -1.18338156 RCP4.5MEDIAN
> 170 0.792607542 y 0.22722653 RCP4.5MEDIAN
> 171 0.803724128 y -1.90642564 RCP4.5MEDIAN
> 172 0.815066246 y 0.75010550 RCP4.5MEDIAN
> 173 0.826027437 y -1.31108646 RCP4.5MEDIAN
> 174 0.836766732 y 1.05961515 RCP4.5MEDIAN
> 175 0.847553312 y -2.06588010 RCP4.5MEDIAN
> 176 0.858331452 y 8.53403315 RCP4.5MEDIAN
> 177 0.869154422 y 0.09979751 RCP4.5MEDIAN
> 178 0.879572539 y -2.50854353 RCP4.5MEDIAN
> 179 0.889426601 y 5.29550783 RCP4.5MEDIAN
> 180 0.899009805 y 2.02909481 RCP4.5MEDIAN
> 181 0.908289566 y 2.66922982 RCP4.5MEDIAN
> 182 0.917284978 y -4.17757196 RCP4.5MEDIAN
> 183 0.926128960 y 3.40202916 RCP4.5MEDIAN
> 184 0.934752874 y -1.92292218 RCP4.5MEDIAN
> 185 0.943010943 y 6.36969150 RCP4.5MEDIAN
> 186 0.950999217 y 1.86490308 RCP4.5MEDIAN
> 187 0.958795701 y 8.32126161 RCP4.5MEDIAN
> 188 0.966310396 y 10.15048356 RCP4.5MEDIAN
> 189 0.973635493 y 6.68925964 RCP4.5MEDIAN
> 190 0.980834088 y -1.01615369 RCP4.5MEDIAN
> 191 0.987694790 y 0.20892853 RCP4.5MEDIAN
> 192 0.994548581 y -1.52787222 RCP4.5MEDIAN
> 193 1.001274595 y -0.72374597 RCP4.5MEDIAN
> 194 1.007810612 y 2.26062309 RCP4.5MEDIAN
> 195 1.014270389 y -2.40270340 RCP4.5MEDIAN
> 196 1.022719711 y -1.94548262 RCP4.5MEDIAN
> 197 1.032070810 y -1.13053235 RCP4.5MEDIAN
> 198 1.041118812 y 0.56107969 RCP4.5MEDIAN
> 199 1.050189571 y 3.27941835 RCP4.5MEDIAN
> 200 1.059380475 y 3.01333588 RCP4.5MEDIAN
> 201 1.067877585 y 4.87457336 RCP4.5MEDIAN
> 202 1.076078766 y 1.02457895 RCP4.5MEDIAN
> 203 1.084707357 y 4.49174869 RCP4.5MEDIAN
> 204 1.093223180 y 8.24629303 RCP4.5MEDIAN
> 205 1.101414382 y -0.03364132 RCP4.5MEDIAN
> 206 1.108886304 y 9.12509848 RCP4.5MEDIAN
> 207 1.115482896 y 1.74254621 RCP4.5MEDIAN
> 208 1.121856558 y 2.27004536 RCP4.5MEDIAN
> 209 1.127809421 y -0.65627179 RCP4.5MEDIAN
> 210 1.133265961 y 12.02566969 RCP4.5MEDIAN
> 211 1.138549712 y -1.04260843 RCP4.5MEDIAN
> 212 1.143910237 y -6.47611327 RCP4.5MEDIAN
> 213 1.149437787 y 8.88410567 RCP4.5MEDIAN
> 214 1.154488347 y -4.24916247 RCP4.5MEDIAN
> 215 1.159872903 y 7.90741918 RCP4.5MEDIAN
> 216 1.165477487 y -3.91386711 RCP4.5MEDIAN
> 217 1.171103424 y 1.02370701 RCP4.5MEDIAN
> 218 1.177498256 y -3.71206616 RCP4.5MEDIAN
> 219 1.184003888 y -1.05694182 RCP4.5MEDIAN
> 220 1.190395856 y 1.10501459 RCP4.5MEDIAN
> 221 1.197284280 y 2.67668639 RCP4.5MEDIAN
> 222 1.204590551 y 2.21693031 RCP4.5MEDIAN
> 223 1.210807614 y 2.90252830 RCP4.5MEDIAN
> 224 1.216470664 y 2.75093766 RCP4.5MEDIAN
> 225 1.221914148 y -0.73815245 RCP4.5MEDIAN
> 226 1.227580480 y 3.58554626 RCP4.5MEDIAN
> 227 1.233317788 y 10.89961658 RCP4.5MEDIAN
> 228 1.238093406 y 3.23374387 RCP4.5MEDIAN
> 229 0.466622908 y -1.92366466 RCP8.5MEDIAN
> 230 0.474211509 y 4.09292949 RCP8.5MEDIAN
> 231 0.480383051 y -0.84736312 RCP8.5MEDIAN
> 232 0.486304903 y -0.80597889 RCP8.5MEDIAN
> 233 0.492151615 y -0.50244413 RCP8.5MEDIAN
> 234 0.499312643 y 3.07785701 RCP8.5MEDIAN
> 235 0.508859905 y -6.15175322 RCP8.5MEDIAN
> 236 0.518758845 y -0.51590144 RCP8.5MEDIAN
> 237 0.528675758 y 3.33135956 RCP8.5MEDIAN
> 238 0.538928423 y 2.62280891 RCP8.5MEDIAN
> 239 0.549621221 y -6.90096009 RCP8.5MEDIAN
> 240 0.560062840 y -3.45706029 RCP8.5MEDIAN
> 241 0.570860791 y 1.36192518 RCP8.5MEDIAN
> 242 0.581923368 y 0.34822359 RCP8.5MEDIAN
> 243 0.592628298 y 3.06882935 RCP8.5MEDIAN
> 244 0.604230648 y -3.56142825 RCP8.5MEDIAN
> 245 0.615975167 y 10.35932554 RCP8.5MEDIAN
> 246 0.627448279 y 10.21751629 RCP8.5MEDIAN
> 247 0.639401050 y 3.31040335 RCP8.5MEDIAN
> 248 0.651949591 y -0.53558775 RCP8.5MEDIAN
> 249 0.664634427 y 2.66081860 RCP8.5MEDIAN
> 250 0.677343552 y 3.21379656 RCP8.5MEDIAN
>
> Maybe something like this?
>
> lusher<-ggplot(NewestdataULTRA) +
> geom_jitter(aes(x,value,onepctCO2MEDIAN=L1), colour="green") +
> geom_smooth(aes(x, value, onepctCO2MEDIAN=L1), method=lm) +
> geom_jitter(aes(x, value, RCP8.5MEDIAN=L1), colour="red")
>
> I receive this warning, however:
> Warning: Ignoring unknown aesthetics: onepctCO2MEDIAN
> Warning: Ignoring unknown aesthetics: onepctCO2MEDIAN Perhaps I am not
> assigning the columns properly? Essentially, I just want create two scatter plots
> and two regression lines for these two objects. Once again, any assistance
> would be greatly appreciated!
> -----Original Message-----
> From: Rui Barradas <ruipbarradas using sapo.pt>
> To: rain1290 <rain1290 using aim.com>; r-help <r-help using R-project.org>; r-sig-geo
> <r-sig-geo using r-project.org>
> Sent: Wed, Jun 5, 2019 10:52 am
> Subject: Re: [R] Plotting more than one regression line in ggplot
>
> 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.
> >
>
> [[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.
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