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 8.0798552
dput(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,
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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,
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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,
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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",
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"layer.80", "layer.81", "layer.82", "layer.83", "layer.84", "layer.85",
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"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!
You should be able to get a scatter plot with a regression line by doing the following:
library(tidyverse)
#> Registered S3 methods overwritten by 'ggplot2':
#> method from
#> [.quosures rlang
#> c.quosures rlang
#> print.quosures rlang
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,
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0.56423419713974, 0.583679616451263, 0.601459443569183, 0.619924664497375,
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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,
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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"))
# Create scatterplot from dataframe "onepctCO2MEDIAN" with "x" and "y" variables and add "lm"
onepctCO2MEDIAN %>%
ggplot(aes(x = x, y = y)) +
geom_point() +
xlab("x") +
ylab("y") +
geom_smooth(method = "lm")
Created on 2019-06-07 by the reprex package (v0.3.0)
Related
I have two polygons
coords1[,1]
-15.99719 -16.01133 -16.04000 -16.08308 -16.14041 -16.21175 -16.29681 -16.39525 -16.50668 -16.63064 -16.76664 -16.91413 -17.07252 -17.24116 -17.41939 -17.60647 -17.80166 -18.00417 -18.21319 -18.42788 -18.64736 -18.87076 -19.09718 -19.32570 -19.55541 -19.78538 -20.01468 -20.24240 -20.46760 -20.68940 -20.90688 -21.11919 -21.32546 -21.52486 -21.71659 -21.89988 -22.07399 -22.23822 -22.39191 -22.53443 -22.66522 -22.78374 -22.88953 -22.98215 -23.06124 -23.12646 -23.17757 -23.21435 -23.23666 -23.24441 -23.23756 -23.21615 -23.18025 -23.13002 -23.06566 -22.98742 -22.89562 -22.79063 -22.67288 -22.54283 -22.40101 -22.24800 -22.08440 -21.91088 -21.72813 -21.53690 -21.33795 -21.13208-20.92012 -20.70293 -20.48137 -20.25635 -20.02876 -19.79953 -19.56958 -19.33983 -19.11120 -18.88463 -18.66102 -18.44127 -18.22626 -18.01687 -17.81393 -17.61826 -17.43066 -17.25187 -17.08262 -16.92358 -16.77540 -16.63868 -16.51396 -16.40174 -16.30249 -16.21659 -16.14440 -16.08620 -16.04224 -16.01268 -15.99764 -15.99719
coords1[,2]
6.225418 6.262789 6.300443 6.338229 6.375996 6.413591 6.450863 6.487662 6.523839 6.559250 6.593750 6.627202 6.659471 6.690426 6.719943 6.747904 6.774196 6.798712 6.821354 6.842031 6.860660 6.877166 6.891481 6.903550 6.913322 6.920758 6.925830 6.928515 6.928804 6.926696 6.922198 6.915329 6.906116 6.894597 6.880818 6.864834 6.846711 6.826520 6.804343 6.780269 6.754396 6.726828 6.697675 6.667055 6.635091 6.601912 6.567652 6.532448 6.496442 6.459780 6.422608 6.385077 6.347338 6.309542 6.271842 6.234389 6.197335 6.160829 6.125017 6.090044 6.056051 6.023174 5.991546 5.961295 5.932541 5.905401 5.879985 5.856394 5.834723 5.815060 5.797484 5.782066 5.768867 5.757941 5.749333 5.743075 5.739195 5.737707 5.738617 5.741922 5.747609 5.755654 5.766025 5.778680 5.793569 5.810631 5.829798 5.850993 5.874129 5.899115 5.925849 5.954224 5.984126 6.015434 6.048021 6.081758 6.116508 6.152130 6.188483 6.225418
coords1.sys[,1]
-17.27076 -17.28943 -17.32370 -17.37346 -17.43849 -17.51853 -17.61326 -17.72229 -17.84520 -17.98148 -18.13059 -18.29192 -18.46483 -18.64862 -18.84254 -19.04583 -19.25765 -19.47717 -19.70348 -19.93569 -20.17285 -20.41402 -20.65821 -20.90445 -21.15175 -21.39911 -21.64554 -21.89003 -22.13161 -22.36931 -22.60216 -22.82924 -23.04962 -23.26241 -23.46677 -23.66187 -23.84692 -24.02117 -24.18394 -24.33455 -24.47241 -24.59695 -24.70769 -24.80416 -24.88599 -24.95284 -25.00445 -25.04060 -25.06116 -25.06603 -25.05520 -25.02871 -24.98667 -24.92926 -24.85668 -24.76926 -24.66732 -24.55129 -24.42163 -24.27886 -24.12357 -23.95636 -23.77792 -23.58897 -23.39027 -23.18261 -22.96683 -22.74380 -22.51443 -22.27962 -22.04034 -21.79754 -21.55219 -21.30530 -21.05785 -20.81083 -20.56525 -20.32209 -20.08233 -19.84693 -19.61685 -19.39301 -19.17632 -18.96763 -18.76781 -18.57764 -18.39789 -18.22930 -18.07253 -17.92822
-17.79696 -17.67926 -17.57560 -17.48640 -17.41203 -17.35277 -17.30887 -17.28050 -17.26778 -17.27076
coords1.sys[,2]
6.465179 6.538004 6.611223 6.684541 6.757663 6.830295 6.902143 6.972919 7.042338 7.110120 7.175992 7.239689 7.300955 7.359542 7.415215 7.467750 7.516935 7.562573 7.604478 7.642483 7.676435 7.706197 7.731648 7.752688 7.769230 7.781208 7.788574 7.791299 7.789371 7.782798 7.771606 7.755841 7.735567 7.710864 7.681832 7.648589 7.611267 7.570018 7.525007 7.476416 7.424440 7.369288 7.311183 7.250359 7.187060 7.121542 7.054068 6.984910 6.914346 6.842661 6.770143 6.697084 6.623779 6.550522 6.477608 6.405332 6.333984 6.263851 6.195216 6.128355 6.063538 6.001025 5.941069 5.883910 5.829778 5.778892 5.731457 5.687664 5.647688 5.611692 5.579819 5.552199 5.528941 5.510141 5.495874 5.486197 5.481149 5.480751 5.485003 5.493890 5.507375 5.525404 5.547904 5.574784 5.605938 5.641238 5.680543 5.723695 5.770520 5.820829 5.874419 5.931076 5.990571 6.052663 6.117104 6.183634 6.251984 6.321880 6.393041 6.465179
plot(1,1,ylim=c(0,15),xlim=c(-30,-10), t="n", xlab="", ylab="")
polygon(coords1[,1], coords1[,2], border=2,col=alpha("red",0.5))
polygon(coords1.sys[,1], coords1.sys[,2], border=2,col=alpha("black",0.5))
I am trying to calculate the percent overlap, as shown using gArea and gIntersection here.
kt.small.g=data.frame(coords1[,1], coords1[,2])
names(kt.small.g)=c("x","y")
summary(kt.small.g)
kt.small.s=data.frame(coords1.sys[,1], coords1.sys[,2])
names(kt.small.s)=c("x","y")
kt.small.g_pol <- Polygons(list(Polygon(kt.small.g)), "small.g")
kt.small.s_pol <- Polygons(list(Polygon(kt.small.s)), "small.s")
kt.small.g_area <- gArea(shape["small.g"])
kt.small.intersections <- gIntersection(shape["small.g"], shape["small.s"])
but after running kt.small.g_area <- gArea(shape["small.g"]) or kt.small.intersections <- gIntersection(shape["small.g"], shape["small.s"]) I get the error:
Error in h(simpleError(msg, call)) :
error in evaluating the argument 'obj' in selecting a method for function 'is.projected': NAs not permitted in row index
I have run through the code in the linked example without error. I have checked my data for NAs, parallel structure to the example, and tried to change the names in shape[] to smaller strings or strings without "." and I still get the same error.
Thank you for your help.
Not sure what percentage you're after, but all of the areas are listed below for you to do the math on.
The following solution uses the sf library to work with the spatial objects.
If you're working with sp objects (SpatialPolygonsDataframes, etc), they can usually be changed to sf using as(x, 'sf').
library(dplyr)
library(ggplot2)
library(sf)
# Cleaning your data pasted from SO
poly1_x <- as.numeric(c("-15.99719", "-16.01133", "-16.04000", "-16.08308", "-16.14041", "-16.21175", "-16.29681", "-16.39525", "-16.50668", "-16.63064", "-16.76664", "-16.91413", "-17.07252", "-17.24116", "-17.41939", "-17.60647", "-17.80166", "-18.00417", "-18.21319", "-18.42788", "-18.64736", "-18.87076", "-19.09718", "-19.32570", "-19.55541", "-19.78538", "-20.01468", "-20.24240", "-20.46760", "-20.68940", "-20.90688", "-21.11919", "-21.32546", "-21.52486", "-21.71659", "-21.89988", "-22.07399", "-22.23822", "-22.39191", "-22.53443", "-22.66522", "-22.78374", "-22.88953", "-22.98215", "-23.06124", "-23.12646", "-23.17757", "-23.21435", "-23.23666", "-23.24441", "-23.23756", "-23.21615", "-23.18025", "-23.13002", "-23.06566", "-22.98742", "-22.89562", "-22.79063", "-22.67288", "-22.54283", "-22.40101", "-22.24800", "-22.08440", "-21.91088", "-21.72813", "-21.53690", "-21.33795", "-21.13208","-20.92012", "-20.70293", "-20.48137", "-20.25635", "-20.02876", "-19.79953", "-19.56958", "-19.33983", "-19.11120", "-18.88463", "-18.66102", "-18.44127", "-18.22626", "-18.01687", "-17.81393", "-17.61826", "-17.43066", "-17.25187", "-17.08262", "-16.92358", "-16.77540", "-16.63868", "-16.51396", "-16.40174", "-16.30249", "-16.21659", "-16.14440", "-16.08620", "-16.04224", "-16.01268", "-15.99764", "-15.99719"))
poly1_y <- c(6.225418, 6.262789, 6.300443, 6.338229, 6.375996, 6.413591, 6.450863, 6.487662, 6.523839, 6.55925, 6.59375, 6.627202, 6.659471, 6.690426, 6.719943, 6.747904, 6.774196, 6.798712, 6.821354, 6.842031, 6.86066, 6.877166, 6.891481, 6.90355, 6.913322, 6.920758, 6.92583, 6.928515, 6.928804, 6.926696, 6.922198, 6.915329, 6.906116, 6.894597, 6.880818, 6.864834, 6.846711, 6.82652, 6.804343, 6.780269, 6.754396, 6.726828, 6.697675, 6.667055, 6.635091, 6.601912, 6.567652, 6.532448, 6.496442, 6.45978, 6.422608, 6.385077, 6.347338, 6.309542, 6.271842, 6.234389, 6.197335, 6.160829, 6.125017, 6.090044, 6.056051, 6.023174, 5.991546, 5.961295, 5.932541, 5.905401, 5.879985, 5.856394, 5.834723, 5.81506, 5.797484, 5.782066, 5.768867, 5.757941, 5.749333, 5.743075, 5.739195, 5.737707, 5.738617, 5.741922, 5.747609, 5.755654, 5.766025, 5.77868, 5.793569, 5.810631, 5.829798, 5.850993, 5.874129, 5.899115, 5.925849, 5.954224, 5.984126, 6.015434, 6.048021, 6.081758, 6.116508, 6.15213, 6.188483, 6.225418)
poly2_x <- c("-17.27076 -17.28943 -17.32370 -17.37346 -17.43849 -17.51853 -17.61326 -17.72229 -17.84520 -17.98148 -18.13059 -18.29192 -18.46483 -18.64862 -18.84254 -19.04583 -19.25765 -19.47717 -19.70348 -19.93569 -20.17285 -20.41402 -20.65821 -20.90445 -21.15175 -21.39911 -21.64554 -21.89003 -22.13161 -22.36931 -22.60216 -22.82924 -23.04962 -23.26241 -23.46677 -23.66187 -23.84692 -24.02117 -24.18394 -24.33455 -24.47241 -24.59695 -24.70769 -24.80416 -24.88599 -24.95284 -25.00445 -25.04060 -25.06116 -25.06603 -25.05520 -25.02871 -24.98667 -24.92926 -24.85668 -24.76926 -24.66732 -24.55129 -24.42163 -24.27886 -24.12357 -23.95636 -23.77792 -23.58897 -23.39027 -23.18261 -22.96683 -22.74380 -22.51443 -22.27962 -22.04034 -21.79754 -21.55219 -21.30530 -21.05785 -20.81083 -20.56525 -20.32209 -20.08233 -19.84693 -19.61685 -19.39301 -19.17632 -18.96763 -18.76781 -18.57764 -18.39789 -18.22930 -18.07253 -17.92822 -17.79696 -17.67926 -17.57560 -17.48640 -17.41203 -17.35277 -17.30887 -17.28050 -17.26778 -17.27076")
poly2_x <- stringr::str_split(poly2_x, pattern = ' ') %>% unlist()
poly2_y <- c(6.465179, 6.538004, 6.611223, 6.684541, 6.757663, 6.830295, 6.902143, 6.972919, 7.042338, 7.11012, 7.175992, 7.239689, 7.300955, 7.359542, 7.415215, 7.46775, 7.516935, 7.562573, 7.604478, 7.642483, 7.676435, 7.706197, 7.731648, 7.752688, 7.76923, 7.781208, 7.788574, 7.791299, 7.789371, 7.782798, 7.771606, 7.755841, 7.735567, 7.710864, 7.681832, 7.648589, 7.611267, 7.570018, 7.525007, 7.476416, 7.42444, 7.369288, 7.311183, 7.250359, 7.18706, 7.121542, 7.054068, 6.98491, 6.914346, 6.842661, 6.770143, 6.697084, 6.623779, 6.550522, 6.477608, 6.405332, 6.333984, 6.263851, 6.195216, 6.128355, 6.063538, 6.001025, 5.941069, 5.88391, 5.829778, 5.778892, 5.731457, 5.687664, 5.647688, 5.611692, 5.579819, 5.552199, 5.528941, 5.510141, 5.495874, 5.486197, 5.481149, 5.480751, 5.485003, 5.49389, 5.507375, 5.525404, 5.547904, 5.574784, 5.605938, 5.641238, 5.680543, 5.723695, 5.77052, 5.820829, 5.874419, 5.931076, 5.990571, 6.052663, 6.117104, 6.183634, 6.251984, 6.32188, 6.393041, 6.465179)
# Make polygons as sf objects
poly1 <- data.frame(x = poly1_x, y = poly1_y) %>%
st_as_sf(coords = c('x', 'y')) %>%
st_combine() %>%
st_cast('POLYGON')
poly2 <- data.frame(x = poly2_x, y = poly2_y) %>%
st_as_sf(coords = c('x', 'y')) %>%
st_combine() %>%
st_cast('POLYGON')
# Plot
ggplot() +
geom_sf(data = poly1, fill = 'red', alpha = .5) +
geom_sf(data = poly2, fill = 'blue', alpha = .5)
# Area of polygon1: (red)
st_area(poly1)
#> [1] 6.62603
# Area of polygon2: (blue)
st_area(poly2)
#> [1] 13.88645
# Area covered only by BOTH polygons (purple)
st_intersection(poly1, poly2) %>%
st_area
#> [1] 5.678321
Created on 2020-12-30 by the reprex package (v0.3.0)
I am trying to create a stratigraphic plot of geochemical element data which should be possible using package tidypaleo.
I want multiple plots of the different element data with Depth (cm) downcore set as the y axis. The data look as follows.
Image of data
I am using this code:
ggplot(wapITRAX, aes(x =BrTi , y = wapITRAX$Depth))+
labs(y = "Depth (cm)")+
geom_lineh()+
theme_classic()+
scale_y_reverse()
However, this only plots one element and I am trying to achieve a plot like this Image of plot
> dput(head(wapITRAX))
structure(list(Depth = 0:5, IncCoh = c(6.049230907, 5.975282432,
5.736199822, 5.658584418, 5.659008377, 5.597103404), BrTi =
c(50.50197628,
22.09236453, 23.48370927, 18.62638581, 14.36924414, 17.48777896
), AlIncCOh = c(16.69633736, 8.200449193, 23.70907643, 20.32310407,
28.62692352, 26.44224866), BrCl = c(8.04090623, 4.306048968,
3.417836951, 3.156895904, 2.787628518, 2.059316731), FeTi =
c(332.715415,
235.9371921, 372.726817, 390.7871397, 396.986099, 495.2624867
), CaTi = c(4.071146245, 3.27955665, 4.395989975, 3.677383592,
3.028670721, 4.523910733), ZrRb = structure(c(363L, 447L, 407L,
395L, 450L, 410L), .Label = c("#DIV/0!", "0.447638604",
"0.478169284",
"0.54554134", "0.548501778", "0.561420163", "0.579454254",
"0.579498861",
"0.580801291", "0.589758019", "0.590194076", "0.590277778",
"0.591357754",
"0.592870544", "0.593851133", "0.598519653", "0.599931082",
"0.600979737",
"0.601426307", "0.611710677", "0.617065868", "0.618499405",
"0.621310093",
"0.627720871", "0.63775246", "0.64005168", "0.643958869",
"0.644371941",
"0.645605974", "0.645661658", "0.646672915", "0.647348952",
"0.651578947",
"0.652401176", "0.656186383", "0.657906264", "0.658835905",
"0.662074554",
"0.662361624", "0.669589393", "0.67103429", "0.671371769",
"0.674335863",
"0.674781688", "0.676097561", "0.676639083", "0.677849462",
"0.680497925",
"0.680610514", "0.680725971", "0.683906537", "0.68855859",
"0.689067202",
"0.692353115", "0.692732291", "0.695411392", "0.696067091",
"0.696794872",
"0.699376436", "0.701762744", "0.702015197", "0.702432938",
"0.70361991",
"0.705235754", "0.705426357", "0.708084164", "0.708258528",
"0.708925221",
"0.715226656", "0.715263314", "0.717828827", "0.718975706",
"0.719799305",
"0.720363636", "0.72476489", "0.725426857", "0.725461098",
"0.726030739",
"0.7267645", "0.726998188", "0.727170554", "0.727533265",
"0.730362368",
"0.731182796", "0.735042735", "0.735849057", "0.736184046",
"0.737214792",
"0.738692342", "0.742223591", "0.742639327", "0.742714724",
"0.744126167",
"0.745790081", "0.746207701", "0.746606335", "0.747041077",
"0.749019608",
"0.751204307", "0.751326495", "0.752443737", "0.752994012",
"0.753398969",
"0.754587869", "0.755151515", "0.755466053", "0.756316411",
"0.757107679",
"0.759175941", "0.76070965", "0.761635833", "0.763760166",
"0.763861189",
"0.764076577", "0.765001936", "0.765509391", "0.765795207",
"0.76598579",
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), class = "factor"), MnFe = c(0.012176723, 0.010329834,
0.009460859,
0.004488071, 0.0033725, 0.003435313), MnIncCoh = c(169.4430276,
331.1977339, 490.5686845, 279.5752228, 272.3091921, 286.0408118
), CuRb = c(0.392971246, 1.484304933, 0.735426009, 0.491651206,
1.142857143, 0.4345898)), row.names = c(NA, 6L), class =
"data.frame")
Using your posted data. This should approximate the desired design.
First step, Transform the data from a wide format to a long format using the pivot_longer function from tidyr.
Then plot the data using "depth" as the independent variable and the parameters' values as the dependent variables.
Then use facet_wrap() to separate the plots. coord_flip() will make the independent variable (Depth) appear on the y-axis.
#fixed 1 column of data.
originaldata$ZrRb <- as.numeric(as.character(originaldata$ZrRb))
library(tidyr)
#Make wide
wapITRAX<-pivot_longer(originaldata, -1, names_to="parameter", values_to = "value")
library(ggplot2)
ggplot(wapITRAX, aes(x = Depth , y = value))+
labs(x = "Depth (cm)")+
geom_line() +
theme_classic() +
coord_flip() +
scale_x_reverse() +
facet_wrap(vars(parameter), nrow=1, scales = "free_x")
o<-read.csv("old.csv')
Callosal_FA CST_FA SLF_FA Area_SMA_A
0.556566554 0.539971971 0.482016736 -0.007984
0.586793895 0.554954237 0.487595985 0.05567
0.613107046 0.597039029 0.467378312 0.136
0.59241945 0.58101919 0.460784717 0.03253
0.586344082 0.555524562 0.479480255 -0.01629
0.607088378 0.56048251 0.478998182 0.07981
0.595145661 0.571902322 0.461452732 0.07882
0.591501695 0.581156582 0.51408736 0.1143
0.587255765 0.566562088 0.462376015 0.1717
0.583943048 0.571209263 0.46400787 -0.01861
0.603512157 0.587332337 0.477376739 0.05672
0.582126533 0.565946603 0.459743433 0.002831
0.570966197 0.556258709 0.470341615 -0.003823
0.570307147 0.542675924 0.504833121 0.01764
0.579498276 0.569837284 0.475364742 -0.000387
0.570543729 0.542095809 0.468923119 0.117
0.613672747 0.572339549 0.486481493 0.1264
0.570649037 0.554125163 0.522845609 0.04696
0.580601176 0.558799894 0.504017998 0.1056
0.576166024 0.542110191 0.476548484 0.05783
0.579598762 0.546776236 0.491528835 0.08022
0.604775228 0.576144869 0.506060596 0.1515
0.555354582 0.556518053 0.492985322 -0.01114
0.580857907 0.556575944 0.484096309 0.03578
I wanted to plot the regression model result (r squared) for multiple group.
I have tried this one and managed to do for one group.
y <- lm(o$Area_SMA_A ~ o$CST_FA + o$SLF_FA + o$Callosal_FA)
then by using the following code:
library(ggplot2)
ggplot(y$model, aes_string(x = names(y$model)[2], y = names(y$model)[1])) +
geom_point() +
stat_smooth(method = "lm", col = "lightblue") +
labs(title = paste("Adj R2 = ",signif(summary(y)$adj.r.squared, 5),
"Intercept =",signif(y$coef[[1]],5 ),
" Slope =",signif(y$coef[[2]], 5),
" P =",signif(summary(y)$coef[2,4], 5)))
I produced this image, which what I wanted.
For I have three groups, I want to add another regression model for the two groups into this plot. Is there a way to do it please? Thank you.
m <- read.csv("middle.csv')
Callosal_FA CST_FA SLF_FA Area_SMA_A
0.599350895 0.59082334 0.518316923 0.04286
0.591540991 0.585592011 0.517415822 0.1291
0.62120411 0.613751115 0.456966929 0.05915
0.59344635 0.571179365 0.500941682 0.01122
0.621645795 0.599144316 0.487736421 0.0471
0.611521291 0.596407776 0.508636999 -0.08177
0.561589532 0.549150165 0.509993364 -0.002053
0.608089072 0.581477369 0.496346462 0.1157
0.583942196 0.576979247 0.505747697 0.01913
0.614675486 0.584447311 0.513085904 0.006673
0.599312499 0.585156336 0.475447955 0.05582
0.591977354 0.578031977 0.505042846 0.08293
0.602347244 0.582916321 0.504538196 -0.07645
0.628674145 0.595462642 0.469785878 0.04787
0.595963981 0.547983665 0.497874226 0.1132
0.604934306 0.586583356 0.502788492 0.08803
0.599656344 0.580235613 0.471793292 0.0118
0.587288357 0.559298093 0.535857414 0.06225
0.586031623 0.582565008 0.475876222 0.282
0.58277546 0.555852007 0.497386116 0.05266
y <- read.csv("young.csv')
Callosal_FA CST_FA SLF_FA Area_SMA_A
0.641939581 0.610050256 0.497039292 -0.05461
0.600969207 0.581011925 0.486918544 0.03801
0.597728695 0.569094851 0.522076721 0.08515
0.605851215 0.575788238 0.522207993 0.001711
0.615141198 0.586422768 0.49536629 0.08908
0.664600517 0.636086957 0.50723616 0.04712
0.617076761 0.577625164 0.50950881 0.02169
0.612482041 0.569112478 0.512551218 0.04043
0.627284885 0.597122461 0.541768958 0.003275
0.627408656 0.607896037 0.505038914 0.06681
0.609205487 0.577178474 0.508818934 -0.04759
0.606824376 0.593485569 0.530833127 0.05503
0.608929339 0.583816742 0.506553103 0.08804
0.623125338 0.599054187 0.518118823 0.04499
0.606161965 0.578010045 0.491883074 0.1487
0.605391626 0.585302201 0.488368677 0.1316
0.640007128 0.599344654 0.503622583 0.1909
0.598483618 0.588507596 0.508622188 0.2013
0.625079582 0.597286968 0.510829857 0.09116
0.620938861 0.577980188 0.52410613 0.02284
0.615765316 0.577922653 0.542867003 0.08179
0.606476852 0.571277288 0.486362068 0.2072
0.607761045 0.585516175 0.509739355 0.075
0.633673687 0.615854958 0.470963903 0.02209
0.641553411 0.621000635 0.492999164 0.101
0.588310547 0.57312727 0.490874808 0.07214
0.588535558 0.571499503 -0.08068 -0.03153
hey i have a dataset that contains a z value of several sampling points, i want to interpolate them to an extent which i had created and gridded earlier, but i keep getting NA for my var1.pred value.
Error in seq.default(min(z[valid]), max(z[valid]), length = cuts + 1) :
'from' must be a finite number
In addition: Warning messages:
1: In min(z[valid]) : no non-missing arguments to min; returning Inf
2: In max(z[valid]) : no non-missing arguments to max; returning -Inf
here's the sample of my code.
#convert to spdf
coordinates(VELOCITY2)<- ~ X + Y
wg<-gstat(id='V', formula = V~1, data=VELOCITY2 )
#variogram
vv<-variogram(wg, cutoff=2000, width=100)
print(plot(vv,plot.numbers=T))
#initial variogram model
vm<-vgm(psill=0.02, range=550, model="Wav", nugget=0.005)
print(plot(vv, model=vm))
#fit variogram
vmf<-fit.variogram(vv,vm)
print(plot(vv, model=vmf))
# points to be interpolated
xx<-seq(from=488300, to=493200, by=100)
yy<-seq(from=9839400, to=9843200, by=100)
xy<-expand.grid(x=xx,y=yy)
coordinates(xy)<- ~ x+y
#ordinary kriging
kk<-krige(V~1, VELOCITY2, newdata=grid, model=vmf)
#plot
spplot(kk, "var1.pred")
my dput
structure(list(X = c(491810.00721276, 492328.97433014, 490911.89327549,
491615.51887818, 491615.51887818, 492894.620021, 492151.9979203,
492572.42983547, 492347.61141516, 491363.11382593, 491353.29751125,
492072.93297881, 490716.22127832, 492001.85406044, 492018.98815452,
492077.66253205, 492050.13933868, 490972.9839127, 491655.7778789,
491576.10196219, 492355.7400162, 492297.13259429, 492673.39998931,
492505.61098796, 492938.89101704, 492796.38161778, 492663.73140998,
492766.00027009, 492765.78359527, 491933.88466968, 492333.89864649,
492720.51113432, 492666.86568757, 492667.84225007, 492522.21401529,
492831.86513802, 492878.85586085, 493201.72451331, 492638.4094498,
492819.43215484, 492796.76931284, 492747.65005034, 492788.05373669,
492762.22524575, 492244.6870987, 492264.07015541, 493008.44619315,
492815.19350734, 492290.80611714, 492277.18886875, 493134.10402992,
493079.00698391, 493078.7734634, 491865.03127595, 492051.82525174,
492670.54384925, 492371.64034572, 491846.41277618, 492775.84682769,
492411.87697905, 492638.79940336, 492638.87569731, 492495.60555568,
490338.97585592, 490362.31496736, 490377.77810208, 489826.99294604,
489853.05092929, 489834.89614387, 490306.53786769, 490308.6412613,
489636.52553863, 489814.82046046, 489667.51345374, 490203.52431788,
491203.81484533, 491077.79256743, 491073.15243053, 491084.72133938,
490958.56246482, 490941.8523819, 491050.5864517, 490764.25539687,
490188.41994785, 490419.69106592, 490424.64284814, 490735.1435195,
490387.98623199, 489297.98195959, 489300.76955718, 490397.404689,
489661.53774563, 490894.97121725, 491108.0970718, 491121.07516021,
490612.02505037, 490615.90676419, 490585.43667157, 490603.01613921,
490591.97121732, 490535.56215982, 489776.74367816, 489958.02334144,
490066.17495271, 490031.0577653, 490190.24001607, 490211.20925445,
490214.70901031, 490003.5550795, 490604.9470475, 491123.82247476,
489847.73806302, 489976.32595346, 491294.31450964, 491007.18618313,
490369.37771158, 490354.14687653, 489273.8003189, 493001.10122237,
489539.64309234, 489012.00149085, 489142.87160796, 488409.5044205,
489078.66848285, 488976.293483, 489208.90896154, 489567.98757469,
490259.16079274, 490199.06081707, 490548.30691066, 489506.84939121,
489507.3984635, 489021.03298499, 488958.65896146, 490198.91372226,
489139.35891258, 488770.78518218, 488912.45339509, 488981.85549448,
488921.30666655, 489881.9584, 489672.654689, 489896.83645177,
489617.50564114, 489919.08864898, 489379.67238921, 491965.57000272,
491962.99825592, 492682.55996244), Y = c(9840083.34991902, 9839461.79230204,
9839986.04132536, 9839995.68878658, 9839995.68878658, 9839486.28400126,
9839853.49933327, 9839540.02081761, 9840596.63605199, 9840110.85284895,
9840123.81671612, 9839970.95343491, 9840217.59113002, 9840621.88702863,
9840939.65655981, 9840492.69562223, 9840364.30304425, 9840527.17804416,
9840153.15948959, 9841067.64777074, 9840733.71222385, 9840674.12726294,
9841985.09015356, 9841070.55597392, 9841095.72784893, 9841691.20050513,
9841720.81866902, 9841676.02960665, 9841673.8772629, 9841246.79718484,
9841422.27277072, 9841223.11749737, 9841990.83136454, 9841994.02765366,
9841585.87726301, 9841625.27960673, 9841777.00030985, 9841315.42609103,
9841973.23663798, 9841953.58624746, 9841942.04523162, 9841975.5950365,
9841921.55109098, 9841756.52179438, 9841803.37823974, 9841535.90655976,
9841695.74445044, 9841543.94562221, 9842174.64777079, 9842182.19659889,
9841376.54230196, 9841406.85773171, 9841406.8294114, 9841667.93488034,
9841949.92609129, 9841973.67413798, 9841897.64874747, 9842246.51398172,
9842171.76691117, 9841921.16437243, 9842138.53937229, 9842136.97003635,
9842380.89386459, 9839975.91827856, 9840042.95343491, 9840089.22394263,
9839589.44562232, 9839978.97296608, 9839972.67706767, 9840000.61749732,
9840046.62823938, 9840384.73566135, 9840302.14484109, 9840018.78351297,
9842250.19659889, 9842008.34698953, 9842209.1907394, 9842203.61261452,
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9842110.55011467, 9842137.70929444, 9841800.60968466, 9841802.06769271,
9842097.74445065, 9841639.30499731, 9842195.63995834, 9842542.10675523,
9842116.55011473, 9841963.44464579, 9841829.30792699, 9841930.18585674,
9841916.66632539, 9842076.43488016, 9842082.75030963, 9842131.36456766,
9842160.68292699, 9842132.72687234, 9842139.580388, 9842277.19952862,
9842102.06183342, 9842101.63605201, 9842143.56085666, 9842095.04718486,
9841791.23859127, 9842670.9856614, 9843067.83527079, 9841903.34601296,
9841830.02277074, 9843129.77081764, 9843097.71808326, 9842604.47394268,
9840407.78644266, 9841952.95148171, 9842186.80011454, 9842038.18195044,
9841950.33234116, 9841538.57843486, 9842189.03839584, 9842814.41534891,
9842339.88898166, 9841739.39484119, 9841739.58624731, 9841750.17023162,
9842428.79816146, 9842966.83429408, 9841471.2981614, 9842028.5803879,
9841446.35480217, 9841755.92120829, 9842498.21027067, 9842371.99152076,
9842484.98761453, 9842385.0296069, 9840908.95441133, 9840831.87628639,
9842363.49738009, 9842105.66730203, 9842228.79132547, 9842178.55792694,
9840714.60968473, 9841214.43976303, 9842612.580388), V = c(6.8575591273834,
6.9091981717661, 6.81861092653243, 6.83544315031305, 6.83544315031305,
6.86928044706404, 6.87308158923757, 6.90102887370632, 6.93656422063757,
6.82756100389376, 6.8279728230811, 6.86916707425107, 6.88723098934826,
6.80869108780012, 6.81041873685147, 6.84851460419374, 6.83998564798438,
6.95597672440102, 6.84830429624437, 6.83571668853121, 6.81554716876882,
6.81653691949333, 6.86570172920796, 8.4183926299318, 6.82540315375968,
6.83694453186651, 6.83616001733514, 6.83366932709608, 6.83281519168562,
6.80657805425162, 6.79252081867902, 6.82804093704906, 6.86560659062316,
6.86560443487979, 6.81210486339519, 6.83024981887722, 6.85348365590436,
6.82737621767244, 6.86002774823981, 6.87890401083686, 6.87433304662824,
6.87310828011749, 6.87227288578899, 6.8406970455203, 6.79788666568234,
6.79289704147439, 6.84212179617635, 6.82201406577053, 6.85818255251501,
6.85882147766148, 6.81441839578817, 6.81109679654478, 6.81075562992338,
6.7695290140362, 6.78453986430733, 6.86470017777305, 6.82941505329464,
6.80201545646814, 6.89940111534327, 6.83386524913627, 6.88022016259413,
6.88000932400808, 6.89652613707228, 6.80951701420202, 6.81047007954082,
6.91318917468862, 6.81620742405261, 6.81609592365983, 6.81555114576811,
6.82359364040975, 6.82243031847043, 6.74848377545697, 6.77432742350875,
6.82113095074504, 6.73035636876622, 6.73157311534001, 6.68948620878327,
6.68804994926179, 6.68991058622174, 6.82298306298922, 6.79655085098109,
6.67806113435277, 6.67880893125878, 6.67462932793097, 6.76784233910405,
6.76791677619622, 6.68328242293505, 6.62279457979837, 6.80333643693172,
6.8017836170837, 6.74582126343433, 6.89705699013895, 6.67169623224357,
6.71095156872004, 6.70398418262631, 6.74214143831379, 6.77269747758851,
6.75839168452443, 6.75917136037271, 6.72567955117309, 6.72476400985706,
6.7940929187327, 6.76465011146018, 6.76185819997855, 6.76483265829331,
6.73217398985043, 6.7558472215621, 6.75644688026535, 6.76569985187991,
6.72096268409918, 6.79914751724536, 6.73903734858573, 6.76387478912845,
6.75057145302792, 6.78523214680787, 6.80514090870779, 6.79610181104104,
6.94632505323771, 6.87151617920864, 6.73501760825965, 6.8043110280055,
6.76237168672284, 6.87393143300434, 6.77223974414773, 6.81073018103125,
6.87291116726081, 6.85121557850258, 6.84429643254038, 6.71871340520001,
6.80737642861958, 6.87505551354325, 6.78810343307566, 6.77795244044547,
6.80445829734336, 6.96781526094347, 6.85340711647284, 6.86963847089039,
6.81734050576888, 6.79958184646059, 6.81761012476222, 7.11505624553277,
7.10405850051035, 6.74511681211045, 6.82787357725889, 6.75689662271503,
6.75616848941266, 6.82089585076081, 6.81664705027901, 6.91617186341967
)), .Names = c("X", "Y", "V"), row.names = c(NA, -149L), class = c("tbl_df",
"tbl", "data.frame"))
i am facing a problem in plot ols estimations in a scatterplot:
I have this data frame: With 9 columns and 99 rows:
structure(list(Y = c(-0.145442175, 0.291096141, 0.489923112,
-2.038363166, 1.180430664, 0.188114666, 0.850922634, 1.172142766,
-3.980837975, 0.285762444, 2.497040646, 0.658010994, -0.925171981,
0.37076995, -1.108211119, -0.409242669, -1.234583525, -0.385841816,
0.016744771, -0.584406288, 1.17224811, -0.746804388, -0.625028046,
0.257871468, -2.735845346, 2.619304857, -0.406825232, 0.323665151,
2.218951363, -0.821029648, -0.872854889, -2.663306158, -0.121976044,
0.881566376, -1.972706678, -3.855576256, 2.927421113, 1.314753531,
0.234296206, 0.828464757, -0.909318569, 0.616134903, -0.567630403,
0.624571064, -0.414112923, 0.642200314, -0.309421266, 0.195312598,
-0.519988256, 0, 0.081070175, 0.032446432, -0.534025032, -0.426783307,
-0.38495511, -0.207900219, -1.953789746, -0.616924355, -0.783222881,
-1.935420969, 0.638445535, 1.080925923, -1.598076681, 0.25063631,
-0.697183766, 0.188971653, -0.415267389, -4.154506044, 1.163226552,
0.036569698, -0.547147074, 1.11937374, 0.383311682, -0.875037781,
-0.372684863, 0.306816004, -1.250561544, -1.042237738, -1.757788446,
0.021079982, 1.844023775, 1.674645753, -0.428546132, -0.527705597,
0.542202572, -0.621479123, -0.050415867, -0.122332943, 0.468553764,
0.216998274, 3.088480781, 0.434099931, 2.114916704, -2.407018936,
-0.127060127, 0.546756422, 0.263207486, 0.63453915, 0.76832746
), X = c(0.009476137, -0.0236354, 0.0094081, 0.11715252, 0.032324021,
0.0461193, 0.050794971, 0.032372819, 0.202121874, 0.390821859,
-0.124492596, -0.127305193, -0.22233597, -0.081113713, 0.09952616,
0.22494711, 0.226621495, 0.411607624, 0.089200478, -0.013454832,
-0.013547165, -0.232366214, 0.03140992, -0.026798837, -0.084556341,
-0.091993172, -0.303730207, -0.236679148, -0.284235285, -0.355253166,
-0.179645537, -0.01381843, -0.022950244, -0.050065976, -0.032018504,
-0.087168055, -0.081865767, -0.253991077, -0.242882759, -0.150225053,
-0.16596575, -0.156887247, -0.071795146, -0.100408802, -0.067307731,
0.024006869, -0.019250912, -0.02399429, 0.038421097, 0.062320065,
0.07187025, 0.024019462, 0.038421097, 0.033539309, 0.014351457,
-0.009575137, 0.014343968, 0.028561284, 0.0404213, 0.026065697,
-0.004700435, -0.072739794, -0.042217496, -0.05889531, -0.130522139,
-0.136291869, -0.120099035, -0.091418565, -0.122040844, -0.124609029,
-0.096255449, -0.190338762, -0.11611752, -0.055598423, -0.065293448,
-0.038746326, -0.029090518, -0.067627348, -0.082097445, -0.215845836,
-0.389993696, -0.264371785, -0.126530291, -0.111840985, -0.094952196,
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-0.122020692, -0.107867301, -0.068642333, -0.034348677, -0.073289926,
-0.063314884, -0.092537576, -0.165375956, -0.15042398), Null = c(-0.036795117836493,
0.0120555676565338, -0.0366906491623935, -0.22323992930528, -0.0728300398338213,
-0.0955073599141197, -0.103350601084975, -0.0729090354522075,
-0.400153521158964, -0.887015257107641, 0.1362666683468, 0.13919994231771,
0.221388292373518, 0.087380368104602, -0.189831042487278, -0.452154909992189,
-0.456044210600938, -0.948567833126862, -0.170785020294756, -0.00253939338337472,
-0.00240533038312774, 0.228145471304061, -0.0713518661553421,
0.0165138860659871, 0.0915102566139487, 0.100284493544177, 0.265652059802101,
0.230938443729295, 0.257246215885006, 0.281209408151878, 0.188533028671265,
-0.00201164134414489, 0.0110851592192505, 0.0481858583559124,
0.0237904823161768, 0.094614581053392, 0.0882862377341187, 0.241468070168396,
0.234837060900023, 0.162029971029324, 0.176601607696189, 0.168307425791361,
0.0759851164110966, 0.109970788582389, 0.0703849242291975, -0.059492586621119,
0.00581616568295407, 0.0125631925046972, -0.0827672867080164,
-0.123023227393077, -0.139691063870559, -0.0595125909296922,
-0.0827672867080164, -0.074799966578053, -0.044324863847201,
-0.00820062690976645, -0.0443132308515717, -0.0667648997869916,
-0.0860567642206439, -0.0627706942069095, -0.0153914247452083,
0.0771546773236518, 0.0377224646820258, 0.0596889425617937, 0.1425196179012,
0.148379247725525, 0.13162698340227, 0.0996137276510431, 0.133686233062275,
0.136388667637584, 0.105222539655097, 0.197385328960716, 0.127361748973716,
0.0554268640818151, 0.0678473149754353, 0.0330232883757411, 0.0197208677278167,
0.0707862239701058, 0.0885648870712001, 0.216820906265572, 0.286245951224793,
0.247258814186372, 0.138394666330137, 0.122716205945161, 0.103719679674083,
0.148789344619283, 0.197893429730301, 0.168006688568371, 0.189742414352596,
0.165430712615822, 0.133664933948451, 0.11833998959919, 0.0720581343490991,
0.0270069004188009, 0.077834296346802, 0.0653403280475977, 0.100918894574441,
0.176071877748707, 0.162219750035618), OLS_1 = c(-2.97674658085357,
-2.95792547866683, -2.97674412477729, -2.7937460366665, -2.96913739819288,
-2.95639989365184, -2.95069150171007, -2.96910314906723, -2.3856485268894,
-0.647452287114872, -2.68293610049662, -2.670570393744, -2.10297963546522,
-2.84137496711892, -2.84927190111917, -2.23638642750757, -2.22477621905134,
-0.385841816000001, -2.87715002139054, -2.96747293407547, -2.96740133507642,
-2.02609643038743, -2.9697648045679, -2.95427875550959, -2.8310157181346,
-2.80733412921436, -1.38551048535346, -1.99204069101103, -1.57679230211392,
-0.821029648, -2.39395151432173, -2.96718943992586, -2.95867282134313,
-2.9175506236826, -2.94755679517459, -2.82290206987746, -2.83914454134393,
-1.84931168689084, -1.94200482386918, -2.56030139156351, -2.4747687889082,
-2.52507434784403, -2.86749990988846, -2.77838660436577, -2.87908253396987,
-2.97385415360498, -2.96244666805069, -2.95752797222193, -2.96426392038595,
-2.93361303993881, -2.91621877029975, -2.97384869333029, -2.96426392038595,
-2.96826157356433, -2.97653443074828, -2.97023260580068, -2.97653534550966,
-2.9715473503959, -2.96240424133875, -2.97289412424858, -2.9730125951007,
-2.86497897723402, -2.93188917574701, -2.89904800305061, -2.6561144854951,
-2.62935195635151, -2.70174255054932, -2.80922741244202, -2.69350740105694,
-2.68242924921473, -2.79295820376613, -2.32657978700299, -2.718248099245,
-2.90625073580661, -2.88407071600265, -2.93759776247538, -2.95143559806685,
-2.87827902655775, -2.83845377816351, -2.15100018436527, -0.392139380784325,
-1.7590965971582, -2.67400272569948, -2.73540774982849, -2.79741598960129,
-2.62741730304073, -2.322499279269, -2.52681590220219, -2.38514457172383,
-2.541507865502, -2.6935934995898, -2.75082409521646, -2.87570553083222,
-2.94427256930162, -2.86349763526591, -2.88884317216564, -2.80553055841713,
-2.47811758528604, -2.55927025907886), OLS_2 = c(-2.83865555876367,
-2.82203271957637, -2.83865550287755, -2.66277932892391, -2.83073328950317,
-2.8182826854432, -2.81275284604234, -2.83069942358793, -2.27571536741022,
-0.632851535784811, -2.56646067709365, -2.55491098827374, -2.02364579120999,
-2.71420058960775, -2.71564453925406, -2.13442002502496, -2.12343285482248,
-0.385841816, -2.74223576659719, -2.83068449367348, -2.83062014186059,
-1.95158880862936, -2.83135434505306, -2.81870405841395, -2.70456098525177,
-2.68251016192609, -1.35080974869909, -1.91966655284606, -1.53026524143009,
-0.821029648, -2.29619548286091, -2.83042962848176, -2.82271365766308,
-2.78489427206998, -2.81254809712918, -2.69700817487578, -2.71212546804251,
-1.78585373408616, -1.87276085874404, -2.45184700668681, -2.37183555552258,
-2.41889982491589, -2.73848954857785, -2.65553364194069, -2.74924637290594,
-2.8354502300085, -2.82614423798244, -2.82167034953476, -2.82594242161564,
-2.7962902949221, -2.77959589724382, -2.83544467118397, -2.82594242161564,
-2.82986834510621, -2.83829410413293, -2.83315419155684, -2.83829521382395,
-2.83312719078141, -2.82412509152621, -2.83447802392599, -2.83561001727694,
-2.73614728712302, -2.79813447119318, -2.76776591170989, -2.54140667394362,
-2.5163996858597, -2.58402223424852, -2.68427373122372, -2.57633280462435,
-2.56598731123967, -2.66911582708562, -2.23311605677819, -2.59943103595799,
-2.7744383205277, -2.75387620457868, -2.80339428073398, -2.81610308322424,
-2.74850042856033, -2.71148276169435, -2.06864445166113, -0.418358709691658,
-1.7012556906544, -2.558117011201, -2.61544592452239, -2.67326984561107,
-2.5145916492569, -2.22929491666958, -2.42052887445801, -2.28795076147412,
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-2.80953310903525, -2.73477077084888, -2.75830410348864, -2.68083005992821,
-2.37496906485549, -2.4508827380889), OLS_3 = c(-2.58083646581942,
-2.5683178338716, -2.58084089114316, -2.41826149362172, -2.57232965672457,
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-2.30551521644622, -2.36423571438323, -2.45098235381054, -2.35756515622,
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-2.52834152993493, -2.51080007744427, -2.55283331443161, -2.56343418632904,
-2.50620082129485, -2.47442497328161, -1.91488441727801, -0.467310795744689,
-1.59326539683083, -2.34175573481226, -2.39147445613669, -2.44148615865099,
-2.30394357612981, -2.05528024243402, -2.22208856552246, -2.10648769733616,
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-2.55797145858227, -2.49443477420494, -2.51458468009137, -2.44801138045477,
-2.18238842077399, -2.24852076027753), OLS_4 = c(-2.4289478285331,
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-1.57289978140148, -1.64407512538075, -2.11744278294415, -2.05217911016675,
-2.09057710272701, -2.35019495754122, -2.28311871426765, -2.35885543710246,
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-2.420544236609, -2.42841594588832, -2.4253216199613, -2.42841722040367,
-2.42347169955882, -2.41547562547196, -2.42470587973943, -2.4271143253132,
-2.34830761179908, -2.39799094116799, -2.37373288731684, -2.19039487337143,
-2.17003793409615, -2.22505776553193, -2.30640152341961, -2.21880622042115,
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-2.37908034073483, -2.36257901260101, -2.4021644964107, -2.41218787827608,
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-2.407018936, -2.34719820268328, -2.36613768370737, -2.30361375259329,
-2.05473632620086, -2.11665669129059), OLS_5 = c(-2.2911912568638,
-2.28123967681215, -2.29119683586224, -2.14805590207021, -2.28325670505768,
-2.27261386268403, -2.268006850245, -2.28322682471889, -1.84560662105751,
-0.576090713535621, -2.0945064647732, -2.0859234999636, -1.68828464788266,
-2.20368547406672, -2.18986194988925, -1.73587625378362, -1.72735189094969,
-0.385841816, -2.21101101562234, -2.28700200417098, -2.28696051646281,
-1.63411554699496, -2.28380625780731, -2.27896044246845, -2.19661244829441,
-2.18039652225164, -1.18146437845759, -1.6101070827248, -1.31682391434599,
-0.781364138557704, -1.89278224977018, -2.28683751979873, -2.28170279433502,
-2.25507742887343, -2.27469315563211, -2.19106352335337, -2.20216376634672,
-1.50940418054145, -1.57481865165838, -2.00915316980509, -1.94938461398854,
-1.98455653642811, -2.22145418758665, -2.1605019074557, -2.22929361026136,
-2.28754415075922, -2.28401553991566, -2.28099274980288, -2.2790962708342,
-2.25448944582185, -2.24095826297856, -2.28753886744317, -2.2790962708342,
-2.28249611688223, -2.29051254450738, -2.28856644852124, -2.29051401027405,
-2.28539476406181, -2.27754391464367, -2.28663199585719, -2.29003809100396,
-2.21974449731936, -2.26453458741267, -2.24273365564754, -2.0758820670505,
-2.05727208640147, -2.1075473897372, -2.18169509790509, -2.10183883759691,
-2.0941547862828, -2.17052540371127, -1.84552009498619, -2.11897925887711,
-2.2475539961602, -2.23266092019845, -2.26826235385205, -2.27716458812284,
-2.22875067319638, -2.20169236013157, -1.72209385129724, -0.476893951190187,
-1.44569200778405, -2.08830648613957, -2.13084935049209, -2.17358829667077,
-2.05592583172644, -1.84265559786228, -1.98577321824112, -1.88660772323127,
-1.99603456442263, -2.10189853669134, -2.14149931364702, -2.22701080101746,
-2.27258448425562, -2.21873931960315, -2.23587705524471, -2.17915915787995,
-1.95172754860073, -2.00843362344438), OLS_6 = c(-2.14615029819501,
-2.1274826763545, -2.14613692884822, -2.038363166, -2.14482079785526,
-2.13839956793073, -2.1352633011825, -2.14480554064275, -1.77137087834078,
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-0.596198212559954, -1.7115906309286, -2.13555900800151, -2.12811588444992,
-2.09509015766854, -2.11889016916752, -2.02341958358771, -2.03553614239934,
-1.32305159796573, -1.38891263096519, -1.83141440901763, -1.76969899713653,
-1.80596583024281, -2.05682837956465, -1.99043348930533, -2.06558998487816,
-2.14664801486533, -2.13135448546891, -2.1271468279034, -2.14250449627423,
-2.12545741758249, -2.11509475538252, -2.1466464083569, -2.14250449627423,
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-1.92007377040746, -2.00120005643771, -1.66327168223962, -1.94624457366434,
-2.08634430885867, -2.06937728900294, -2.11086434271986, -2.12206882778948,
-2.06498074945642, -2.03501978622706, -1.5377512452434, -0.29431817292714,
-1.25902518147068, -1.91393009686737, -1.95881793980313, -2.00449939786682,
-1.88004274517372, -1.66034827254381, -1.80722288608151, -1.70526848086161,
-1.81783189921089, -1.92822084254891, -1.97013652098612, -2.0630309651189,
-2.1162243283256, -2.0538104595074, -2.07300962091288, -2.0105124912345,
-1.7721107506457, -1.83066883021211)), .Names = c("Y", "X", "Null",
"OLS_1", "OLS_2", "OLS_3", "OLS_4", "OLS_5", "OLS_6"), row.names = c(NA,
99L), class = "data.frame")
My scatter plot will consist of the first column (Y) and the second column (X).
The third column i will not use.
From the fourth column are the curves that are fitted values of OLS regressions.
How do I include them using the plot function?
i am doing this, but its not working
plot(data[,2],data[,1])
for(i in 4:9){
lines(data[,i])
}
What am i doing wrong?
Basically you want
data <- data[order(data$X), ] ## reordering so that `X` is increasing
plot(data$X, data$Y)
for (i in 4:9) {
lines(data$X, data[,i], col = i) ## remember to set `x-coordinates`
}
legend("topright", legend = names(data)[4:9], col = 4:9, lty = 1) ## add legend