r@i@1290 m@iii@g oii @im@com
2019-Jun-06 16:49 UTC
[R] Plotting more than one regression line in ggplot
Hi Rui,
NewestdataUltra looks like this (Note that "HistoricalMEDIAN" is
hidden, but it follows "RCP8.5MEDIAN" listing the same way):
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
[ reached 'max' / getOption("max.print") -- omitted 212 rows
]
If I wanted scatter plots and regression lines of onepctCO2MEDIAN, RCP4.5MEDIAN
and RCP8.5MEDIAN, would I do something like this?
:ggplot(subset(NewestdataUltra, L1 != 'onepctCO2MEDIAN'), aes(x, value,
colour = L1)) + geom_point() + scale_color_manual(values =c("green",
"blue" "red", "black")) + geom_smooth(method = lm,
se=FALSE)
Thanks,
-----Original Message-----
From: Rui Barradas <ruipbarradas at sapo.pt>
To: rain1290 <rain1290 at aim.com>; r-help <r-help at R-project.org>
Sent: Thu, Jun 6, 2019 11:53 am
Subject: Re: [R] Plotting more than one regression line in ggplot
Hello,
It's impossible to say without seeing the data.
What is the return value of
df_tmp <- subset(NewestdataUltra, L1 != 'onepctCO2MEDIAN')
unique(df_tmp$L1)
The number of colors must be the same as
length(unique(df_tmp$L1))
Hope this helps,
Rui Barradas
?s 16:49 de 06/06/19, rain1290 at aim.com escreveu:> Hi Rui,
>
> Yes, you are right. It should be this, but I tried with only 3 colors,
> as you suggested:
>
> ggplot(subset(NewestdataUltra, L1 != 'onepctCO2MEDIAN'), aes(x,
value,
> colour = L1)) + geom_point() + scale_color_manual(values
=c("green",
> "blue" "red")) + geom_smooth(method = lm, se=FALSE)
>
> **//___^
> **//___^I still end up with the same error, however, when I specify only
> 3 colors. Why could this be?
>
>
> -----Original Message-----
> From: Rui Barradas <ruipbarradas at sapo.pt>
> To: rain1290 <rain1290 at aim.com>; r-help <r-help at
R-project.org>
> Sent: Thu, Jun 6, 2019 11:18 am
> Subject: Re: [R] Plotting more than one regression line in ggplot
>
> Hello,
>
> 1) In the text you say your dataset is named NewestdataUltra but in the
> ggplot instruction it's Newestdata. One of these is wrong.
>
> 2) Is it onepctCO2MEDIAN or RCPonepctCO2MEDIAN?
>
> 3) You are filtering out the value in point ) above. So you only plot 3
> regression lines, you don't need 4 colors.
>
>
> Hope this helps,
>
> Rui Barradas
>
> ?s 15:35 de 06/06/19, rain1290 at aim.com <mailto:rain1290 at
aim.com> escreveu:
>? > Hi Rui (and everyone),
>? >
>? >
>? > Thank you for this! Yes, this did work fine, as I can see my scatter
>? > plots and regression lines on the same plot, along with the
appropriate
>? > coloring scheme! :)
>? >
>? > Just one last question concerning this - I melted other dataframes
into
>? > my new "NewestdataUltra". I now have 4 objects listed in
there in this
>? > order (starting from the top of the list):
"onepctCO2MEDIAN",
>? > "RCP4.5MEDIAN", RCP8.5MEDIAN", and
"HistoricalMEDIAN". I tried plotting
>? > colored scattered plots and regression lines for these in this
manner:
>? >
>? > ggplot(subset(Newestdata, L1 != 'RCPonepctCO2MEDIAN'), aes(x,
value,
>? > colour = L1)) + geom_point() + scale_color_manual(values
=c("green",
>? > "blue" "red", "black")) +
geom_smooth(method = lm, se=FALSE)
>? >
>? > However, I received this error:
>? >
>? > Error: unexpected string constant in
"ggplot(subset(NewestdataUltra, L1
>? > != 'RCPonepctCO2MEDIAN'), aes(x, value, colour = L1)) +
geom_point() +
>? > scale_color_manual(values =c("green", "blue"
"red""
>? >
>? > **//___^
>? >
>? > Why would this error appear?? I think that I assigned the colors
>? > correctly to each of the four objects in question, so why would this
> occur?
>? >
>? > Thank you, once again!
>? >
>? > -----Original Message-----
>? > From: Rui Barradas <ruipbarradas at sapo.pt
<mailto:ruipbarradas at sapo.pt>>
>? > To: rain1290 <rain1290 at aim.com <mailto:rain1290 at
aim.com>>; r-help
> <r-help at R-project.org <mailto:r-help at R-project.org>>
>? > Sent: Thu, Jun 6, 2019 6:52 am
>? > Subject: Re: [R] Plotting more than one regression line in ggplot
>? >
>? > Hello,
>? >
>? > You are confusing some of the values of L1 with L1 itself.
>? > If you just want two of those values in your plot,
"onepctCO2MEDIAN" and
>? > "RCP8.5MEDIAN", you need to subset the data filtering out
the rows with
>? > L1 == "RCP4.5MEDIAN".
>? >
>? > And please forget geom_jitter, it is completely inappropriate for the
>? > type of scatter plot you are trying to graph. You jitter when there
is
>? > overplotting, not as a general purpose technique.
>? >
>? > Here is one way to do it.
>? >
>? >
>? > ggplot(subset(NewestdataUltra, L1 != 'RCP4.5MEDIAN'),
>? >? ? ? ? ? aes(x, value, colour = L1)) +
>? >? ? geom_point() +
>? >? ? scale_color_manual(values = c("green", "red"))
+
>? >? ? geom_smooth(method = lm)
>? >
>? >
>? > Hope this helps,
>? >
>? > Rui Barradas
>? >
>? > ?s 22:37 de 05/06/19, rain1290 at aim.com <mailto:rain1290 at
aim.com>
> <mailto:rain1290 at aim.com <mailto:rain1290 at aim.com>>
escreveu:
>? >? > 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 at sapo.pt
> <mailto:ruipbarradas at sapo.pt> <mailto:ruipbarradas at sapo.pt
> <mailto:ruipbarradas at sapo.pt>>>
>? >? > To: rain1290 <rain1290 at aim.com <mailto:rain1290 at
aim.com>
> <mailto:rain1290 at aim.com <mailto:rain1290 at aim.com>>>;
r-help
>? > <r-help at R-project.org <mailto:r-help at R-project.org>
> <mailto:r-help at R-project.org <mailto:r-help at
R-project.org>>>;
>? >? > r-sig-geo <r-sig-geo at r-project.org
> <mailto:r-sig-geo at r-project.org> <mailto:r-sig-geo at
r-project.org
> <mailto:r-sig-geo at 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
>? >? >
>? >? > ?s 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 at r-project.org <mailto:R-help at
r-project.org>
> <mailto:R-help at r-project.org <mailto: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]]
Hello,
Try this.
values_to_plot <- c("onepctCO2MEDIAN", "RCP4.5MEDIAN",
"RCP8.5MEDIAN")
sub_df <- subset(NewestdataUltra, L1 %in% values_to_plot)
ggplot(sub_df, aes(x, value, colour = L1)) +
geom_point() +
scale_color_manual(values = c("green", "red",
"blue")) +
geom_smooth(method = lm)
If you have more L1 values to plot, add more colors. The number of
colors must be equal to
length(values_to_plot)
Hope this helps,
Rui Barradas
?s 17:49 de 06/06/19, rain1290 at aim.com escreveu:> Hi Rui, NewestdataUltra looks like this (Note that
"HistoricalMEDIAN" is
> hidden, but it follows "RCP8.5MEDIAN" listing the same way): 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 [ reached
'max' /
> getOption("max.print") -- omitted 212 rows ]
>
>
> If I wanted scatter plots and regression lines of onepctCO2MEDIAN,
> RCP4.5MEDIAN and RCP8.5MEDIAN, would I do something like this? :
> ggplot(subset(NewestdataUltra, L1 != 'onepctCO2MEDIAN'), aes(x,
value,
> colour = L1)) + geom_point() + scale_color_manual(values
=c("green",
> "blue" "red", "black")) + geom_smooth(method
= lm, se=FALSE)
> **//___^
> Thanks,
>
> -----Original Message-----
> From: Rui Barradas <ruipbarradas at sapo.pt>
> To: rain1290 <rain1290 at aim.com>; r-help <r-help at
R-project.org>
> Sent: Thu, Jun 6, 2019 11:53 am
> Subject: Re: [R] Plotting more than one regression line in ggplot
>
> Hello,
>
> It's impossible to say without seeing the data.
>
> What is the return value of
>
> df_tmp <- subset(NewestdataUltra, L1 != 'onepctCO2MEDIAN')
> unique(df_tmp$L1)
>
> The number of colors must be the same as
>
> length(unique(df_tmp$L1))
>
>
> Hope this helps,
>
> Rui Barradas
>
> ?s 16:49 de 06/06/19, rain1290 at aim.com <mailto:rain1290 at
aim.com> escreveu:
> > Hi Rui,
> >
> > Yes, you are right. It should be this, but I tried with only 3
colors,
> > as you suggested:
> >
> > ggplot(subset(NewestdataUltra, L1 != 'onepctCO2MEDIAN'),
aes(x, value,
> > colour = L1)) + geom_point() + scale_color_manual(values
=c("green",
> > "blue" "red")) + geom_smooth(method = lm,
se=FALSE)
> >
> > **//___^
> > **//___^I still end up with the same error, however, when I specify
only
> > 3 colors. Why could this be?
> >
> >
> > -----Original Message-----
> > From: Rui Barradas <ruipbarradas at sapo.pt
<mailto:ruipbarradas at sapo.pt>>
> > To: rain1290 <rain1290 at aim.com <mailto:rain1290 at
aim.com>>; r-help
> <r-help at R-project.org <mailto:r-help at R-project.org>>
> > Sent: Thu, Jun 6, 2019 11:18 am
> > Subject: Re: [R] Plotting more than one regression line in ggplot
> >
> > Hello,
> >
> > 1) In the text you say your dataset is named NewestdataUltra but in
the
> > ggplot instruction it's Newestdata. One of these is wrong.
> >
> > 2) Is it onepctCO2MEDIAN or RCPonepctCO2MEDIAN?
> >
> > 3) You are filtering out the value in point ) above. So you only plot
3
> > regression lines, you don't need 4 colors.
> >
> >
> > Hope this helps,
> >
> > Rui Barradas
> >
> > ?s 15:35 de 06/06/19, rain1290 at aim.com <mailto:rain1290 at
aim.com>
> <mailto:rain1290 at aim.com <mailto:rain1290 at aim.com>>
escreveu:
> >? > Hi Rui (and everyone),
> >? >
> >? >
> >? > Thank you for this! Yes, this did work fine, as I can see my
scatter
> >? > plots and regression lines on the same plot, along with the
> appropriate
> >? > coloring scheme! :)
> >? >
> >? > Just one last question concerning this - I melted other
dataframes
> into
> >? > my new "NewestdataUltra". I now have 4 objects listed
in there in this
> >? > order (starting from the top of the list):
"onepctCO2MEDIAN",
> >? > "RCP4.5MEDIAN", RCP8.5MEDIAN", and
"HistoricalMEDIAN". I tried
> plotting
> >? > colored scattered plots and regression lines for these in this
manner:
> >? >
> >? > ggplot(subset(Newestdata, L1 != 'RCPonepctCO2MEDIAN'),
aes(x, value,
> >? > colour = L1)) + geom_point() + scale_color_manual(values
=c("green",
> >? > "blue" "red", "black")) +
geom_smooth(method = lm, se=FALSE)
> >? >
> >? > However, I received this error:
> >? >
> >? > Error: unexpected string constant in
> "ggplot(subset(NewestdataUltra, L1
> >? > != 'RCPonepctCO2MEDIAN'), aes(x, value, colour = L1)) +
geom_point() +
> >? > scale_color_manual(values =c("green",
"blue" "red""
> >? >
> >? > **//___^
> >? >
> >? > Why would this error appear?? I think that I assigned the
colors
> >? > correctly to each of the four objects in question, so why would
this
> > occur?
> >? >
> >? > Thank you, once again!
> >? >
> >? > -----Original Message-----
> >? > From: Rui Barradas <ruipbarradas at sapo.pt
> <mailto:ruipbarradas at sapo.pt> <mailto:ruipbarradas at sapo.pt
> <mailto:ruipbarradas at sapo.pt>>>
> >? > To: rain1290 <rain1290 at aim.com <mailto:rain1290 at
aim.com>
> <mailto:rain1290 at aim.com <mailto:rain1290 at aim.com>>>;
r-help
> > <r-help at R-project.org <mailto:r-help at R-project.org>
> <mailto:r-help at R-project.org <mailto:r-help at
R-project.org>>>
> >? > Sent: Thu, Jun 6, 2019 6:52 am
> >? > Subject: Re: [R] Plotting more than one regression line in
ggplot
> >? >
> >? > Hello,
> >? >
> >? > You are confusing some of the values of L1 with L1 itself.
> >? > If you just want two of those values in your plot,
> "onepctCO2MEDIAN" and
> >? > "RCP8.5MEDIAN", you need to subset the data filtering
out the rows
> with
> >? > L1 == "RCP4.5MEDIAN".
> >? >
> >? > And please forget geom_jitter, it is completely inappropriate
for the
> >? > type of scatter plot you are trying to graph. You jitter when
there is
> >? > overplotting, not as a general purpose technique.
> >? >
> >? > Here is one way to do it.
> >? >
> >? >
> >? > ggplot(subset(NewestdataUltra, L1 != 'RCP4.5MEDIAN'),
> >? >? ? ? ? ? aes(x, value, colour = L1)) +
> >? >? ? geom_point() +
> >? >? ? scale_color_manual(values = c("green",
"red")) +
> >? >? ? geom_smooth(method = lm)
> >? >
> >? >
> >? > Hope this helps,
> >? >
> >? > Rui Barradas
> >? >
> >? > ?s 22:37 de 05/06/19, rain1290 at aim.com <mailto:rain1290
at aim.com>
> <mailto:rain1290 at aim.com <mailto:rain1290 at aim.com>>
> > <mailto:rain1290 at aim.com <mailto:rain1290 at aim.com>
> <mailto:rain1290 at aim.com <mailto:rain1290 at aim.com>>>
escreveu:
> >? >? > 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 at sapo.pt
> <mailto:ruipbarradas at sapo.pt>
> > <mailto:ruipbarradas at sapo.pt <mailto:ruipbarradas at
sapo.pt>>
> <mailto:ruipbarradas at sapo.pt <mailto:ruipbarradas at sapo.pt>
> > <mailto:ruipbarradas at sapo.pt <mailto:ruipbarradas at
sapo.pt>>>>
> >? >? > To: rain1290 <rain1290 at aim.com <mailto:rain1290
at aim.com>
> <mailto:rain1290 at aim.com <mailto:rain1290 at aim.com>>
> > <mailto:rain1290 at aim.com <mailto:rain1290 at aim.com>
> <mailto:rain1290 at aim.com <mailto:rain1290 at
aim.com>>>>; r-help
> >? > <r-help at R-project.org <mailto:r-help at
R-project.org>
> <mailto:r-help at R-project.org <mailto:r-help at
R-project.org>>
> > <mailto:r-help at R-project.org <mailto:r-help at
R-project.org>
> <mailto:r-help at R-project.org <mailto:r-help at
R-project.org>>>>;
> >? >? > r-sig-geo <r-sig-geo at r-project.org
> <mailto:r-sig-geo at r-project.org>
> > <mailto:r-sig-geo at r-project.org <mailto:r-sig-geo at
r-project.org>>
> <mailto:r-sig-geo at r-project.org <mailto:r-sig-geo at
r-project.org>
> > <mailto:r-sig-geo at r-project.org <mailto:r-sig-geo at
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
> >? >? >
> >? >? > ?s 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 at r-project.org <mailto:R-help at
r-project.org>
> <mailto:R-help at r-project.org <mailto:R-help at
r-project.org>>
> > <mailto:R-help at r-project.org <mailto:R-help at
r-project.org>
> <mailto:R-help at r-project.org <mailto: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@i@1290 m@iii@g oii @im@com
2019-Jun-06 20:08 UTC
[R] Plotting more than one regression line in ggplot
Hi Rui,
Yes! This worked just fine! Thank you so, so much for your time and patience!?
-----Original Message-----
From: Rui Barradas <ruipbarradas at sapo.pt>
To: rain1290 <rain1290 at aim.com>; r-help <r-help at R-project.org>
Sent: Thu, Jun 6, 2019 3:25 pm
Subject: Re: [R] Plotting more than one regression line in ggplot
Hello,
Try this.
values_to_plot <- c("onepctCO2MEDIAN", "RCP4.5MEDIAN",
"RCP8.5MEDIAN")
sub_df <- subset(NewestdataUltra, L1 %in% values_to_plot)
ggplot(sub_df, aes(x, value, colour = L1)) +
? geom_point() +
? scale_color_manual(values = c("green", "red",
"blue")) +
? geom_smooth(method = lm)
If you have more L1 values to plot, add more colors. The number of
colors must be equal to
length(values_to_plot)
Hope this helps,
Rui Barradas
?s 17:49 de 06/06/19, rain1290 at aim.com escreveu:> Hi Rui, NewestdataUltra looks like this (Note that
"HistoricalMEDIAN" is
> hidden, but it follows "RCP8.5MEDIAN" listing the same way): 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 [ reached
'max' /
> getOption("max.print") -- omitted 212 rows ]
>
>
> If I wanted scatter plots and regression lines of onepctCO2MEDIAN,
> RCP4.5MEDIAN and RCP8.5MEDIAN, would I do something like this? :
> ggplot(subset(NewestdataUltra, L1 != 'onepctCO2MEDIAN'), aes(x,
value,
> colour = L1)) + geom_point() + scale_color_manual(values
=c("green",
> "blue" "red", "black")) + geom_smooth(method
= lm, se=FALSE)
> **//___^
> Thanks,
>
> -----Original Message-----
> From: Rui Barradas <ruipbarradas at sapo.pt>
> To: rain1290 <rain1290 at aim.com>; r-help <r-help at
R-project.org>
> Sent: Thu, Jun 6, 2019 11:53 am
> Subject: Re: [R] Plotting more than one regression line in ggplot
>
> Hello,
>
> It's impossible to say without seeing the data.
>
> What is the return value of
>
> df_tmp <- subset(NewestdataUltra, L1 != 'onepctCO2MEDIAN')
> unique(df_tmp$L1)
>
> The number of colors must be the same as
>
> length(unique(df_tmp$L1))
>
>
> Hope this helps,
>
> Rui Barradas
>
> ?s 16:49 de 06/06/19, rain1290 at aim.com <mailto:rain1290 at
aim.com> escreveu:
>? > Hi Rui,
>? >
>? > Yes, you are right. It should be this, but I tried with only 3
colors,
>? > as you suggested:
>? >
>? > ggplot(subset(NewestdataUltra, L1 != 'onepctCO2MEDIAN'),
aes(x, value,
>? > colour = L1)) + geom_point() + scale_color_manual(values
=c("green",
>? > "blue" "red")) + geom_smooth(method = lm,
se=FALSE)
>? >
>? > **//___^
>? > **//___^I still end up with the same error, however, when I specify
only
>? > 3 colors. Why could this be?
>? >
>? >
>? > -----Original Message-----
>? > From: Rui Barradas <ruipbarradas at sapo.pt
<mailto:ruipbarradas at sapo.pt>>
>? > To: rain1290 <rain1290 at aim.com <mailto:rain1290 at
aim.com>>; r-help
> <r-help at R-project.org <mailto:r-help at R-project.org>>
>? > Sent: Thu, Jun 6, 2019 11:18 am
>? > Subject: Re: [R] Plotting more than one regression line in ggplot
>? >
>? > Hello,
>? >
>? > 1) In the text you say your dataset is named NewestdataUltra but in
the
>? > ggplot instruction it's Newestdata. One of these is wrong.
>? >
>? > 2) Is it onepctCO2MEDIAN or RCPonepctCO2MEDIAN?
>? >
>? > 3) You are filtering out the value in point ) above. So you only plot
3
>? > regression lines, you don't need 4 colors.
>? >
>? >
>? > Hope this helps,
>? >
>? > Rui Barradas
>? >
>? > ?s 15:35 de 06/06/19, rain1290 at aim.com <mailto:rain1290 at
aim.com>
> <mailto:rain1290 at aim.com <mailto:rain1290 at aim.com>>
escreveu:
>? >? > Hi Rui (and everyone),
>? >? >
>? >? >
>? >? > Thank you for this! Yes, this did work fine, as I can see my
scatter
>? >? > plots and regression lines on the same plot, along with the
> appropriate
>? >? > coloring scheme! :)
>? >? >
>? >? > Just one last question concerning this - I melted other
dataframes
> into
>? >? > my new "NewestdataUltra". I now have 4 objects listed
in there in this
>? >? > order (starting from the top of the list):
"onepctCO2MEDIAN",
>? >? > "RCP4.5MEDIAN", RCP8.5MEDIAN", and
"HistoricalMEDIAN". I tried
> plotting
>? >? > colored scattered plots and regression lines for these in this
manner:
>? >? >
>? >? > ggplot(subset(Newestdata, L1 != 'RCPonepctCO2MEDIAN'),
aes(x, value,
>? >? > colour = L1)) + geom_point() + scale_color_manual(values
=c("green",
>? >? > "blue" "red", "black")) +
geom_smooth(method = lm, se=FALSE)
>? >? >
>? >? > However, I received this error:
>? >? >
>? >? > Error: unexpected string constant in
> "ggplot(subset(NewestdataUltra, L1
>? >? > != 'RCPonepctCO2MEDIAN'), aes(x, value, colour = L1)) +
geom_point() +
>? >? > scale_color_manual(values =c("green",
"blue" "red""
>? >? >
>? >? > **//___^
>? >? >
>? >? > Why would this error appear?? I think that I assigned the
colors
>? >? > correctly to each of the four objects in question, so why would
this
>? > occur?
>? >? >
>? >? > Thank you, once again!
>? >? >
>? >? > -----Original Message-----
>? >? > From: Rui Barradas <ruipbarradas at sapo.pt
> <mailto:ruipbarradas at sapo.pt> <mailto:ruipbarradas at sapo.pt
> <mailto:ruipbarradas at sapo.pt>>>
>? >? > To: rain1290 <rain1290 at aim.com <mailto:rain1290 at
aim.com>
> <mailto:rain1290 at aim.com <mailto:rain1290 at aim.com>>>;
r-help
>? > <r-help at R-project.org <mailto:r-help at R-project.org>
> <mailto:r-help at R-project.org <mailto:r-help at
R-project.org>>>
>? >? > Sent: Thu, Jun 6, 2019 6:52 am
>? >? > Subject: Re: [R] Plotting more than one regression line in
ggplot
>? >? >
>? >? > Hello,
>? >? >
>? >? > You are confusing some of the values of L1 with L1 itself.
>? >? > If you just want two of those values in your plot,
> "onepctCO2MEDIAN" and
>? >? > "RCP8.5MEDIAN", you need to subset the data filtering
out the rows
> with
>? >? > L1 == "RCP4.5MEDIAN".
>? >? >
>? >? > And please forget geom_jitter, it is completely inappropriate
for the
>? >? > type of scatter plot you are trying to graph. You jitter when
there is
>? >? > overplotting, not as a general purpose technique.
>? >? >
>? >? > Here is one way to do it.
>? >? >
>? >? >
>? >? > ggplot(subset(NewestdataUltra, L1 != 'RCP4.5MEDIAN'),
>? >? >? ? ? ? ? aes(x, value, colour = L1)) +
>? >? >? ? geom_point() +
>? >? >? ? scale_color_manual(values = c("green",
"red")) +
>? >? >? ? geom_smooth(method = lm)
>? >? >
>? >? >
>? >? > Hope this helps,
>? >? >
>? >? > Rui Barradas
>? >? >
>? >? > ?s 22:37 de 05/06/19, rain1290 at aim.com <mailto:rain1290
at aim.com>
> <mailto:rain1290 at aim.com <mailto:rain1290 at aim.com>>
>? > <mailto:rain1290 at aim.com <mailto:rain1290 at aim.com>
> <mailto:rain1290 at aim.com <mailto:rain1290 at aim.com>>>
escreveu:
>? >? >? > 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 at sapo.pt
> <mailto:ruipbarradas at sapo.pt>
>? > <mailto:ruipbarradas at sapo.pt <mailto:ruipbarradas at
sapo.pt>>
> <mailto:ruipbarradas at sapo.pt <mailto:ruipbarradas at sapo.pt>
>? > <mailto:ruipbarradas at sapo.pt <mailto:ruipbarradas at
sapo.pt>>>>
>? >? >? > To: rain1290 <rain1290 at aim.com <mailto:rain1290
at aim.com>
> <mailto:rain1290 at aim.com <mailto:rain1290 at aim.com>>
>? > <mailto:rain1290 at aim.com <mailto:rain1290 at aim.com>
> <mailto:rain1290 at aim.com <mailto:rain1290 at
aim.com>>>>; r-help
>? >? > <r-help at R-project.org <mailto:r-help at
R-project.org>
> <mailto:r-help at R-project.org <mailto:r-help at
R-project.org>>
>? > <mailto:r-help at R-project.org <mailto:r-help at
R-project.org>
> <mailto:r-help at R-project.org <mailto:r-help at
R-project.org>>>>;
>? >? >? > r-sig-geo <r-sig-geo at r-project.org
> <mailto:r-sig-geo at r-project.org>
>? > <mailto:r-sig-geo at r-project.org <mailto:r-sig-geo at
r-project.org>>
> <mailto:r-sig-geo at r-project.org <mailto:r-sig-geo at
r-project.org>
>? > <mailto:r-sig-geo at r-project.org <mailto:r-sig-geo at
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
>? >? >? >
>? >? >? > ?s 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 at r-project.org <mailto:R-help at
r-project.org>
> <mailto:R-help at r-project.org <mailto:R-help at
r-project.org>>
>? > <mailto:R-help at r-project.org <mailto:R-help at
r-project.org>
> <mailto:R-help at r-project.org <mailto: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]]