[R] Plotting more than one regression line in ggplot
r@i@1290 m@iii@g oii @im@com
r@i@1290 m@iii@g oii @im@com
Wed Jun 5 23:37:13 CEST 2019
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]]
More information about the R-help
mailing list