R 在ggplot中绘制多条线性回归线
我正试图用ggplot为几个数据集绘制一系列带有回归线的散点图。我从以下数据集开始，“OneSpectCo2Median”。此数据集的数据如下所示：R 在ggplot中绘制多条线性回归线,r,ggplot2,linear-regression,R,Ggplot2,Linear Regression,我正试图用ggplot为几个数据集绘制一系列带有回归线的散点图。我从以下数据集开始，“OneSpectCo2Median”。此数据集的数据如下所示： 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 6.634913
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
lm<-ggplot(onepctCO2MEDIAN) +
geom_jitter(aes(RCP1pctCO2cumulativeMedian[1:138], departurea),
colour="blue") + geom_smooth(aes(RCP1pctCO2cumulativeMedian[1:138],
departurea), method=lm)
这有什么原因吗？我将感谢任何帮助 您应该能够通过执行以下操作获得带有回归线的散点图：
库（tidyverse）
#>已注册的S3方法被“ggplot2”覆盖：
#>方法自
#>[.quosures rlang
#>c.quosures rlang
#>print.quosures rlang
onepctCO2MEDIAN%
ggplot（aes（x=x，y=y））+
几何点（）+
xlab（“x”）+
ylab（“y”）+
几何光滑（方法=“lm”）
>（v0.3.0）在代码中有很多未知变量。尝试向我们展示你是如何从数据集到这些变量的。如果你想让我们能够使用你的数据集，你可以考虑使用<代码> dPT（OnEntCCO2中值）。。这将给我们一个命令，我们可以运行它来复制您的数据集。@dylanvanw感谢您的回复-我刚刚在上面添加了dput（onepctCO2MEDIAN）。非常感谢您的回复！是否可以压缩“tribble”部分中的内容？我试着放置“onepctCO2MEDIAN”，但我在这样做时收到了一个错误。再次感谢您的回复。我刚刚用“onepctCO2MEDIAN”替换了“df”，但我收到了我在上一篇帖子中提到的相同错误。也就是说，我现在确实在上面的帖子中包含了“dput”的结果.Hi larsoevlisen-另外，这是我收到的阻止回归线出现的错误（散点图很好）：警告消息：在
stat_smooth（）中计算失败lm<-ggplot(onepctCO2MEDIAN) +
geom_jitter(aes(RCP1pctCO2cumulativeMedian[1:138], departurea),
colour="blue") + geom_smooth(aes(RCP1pctCO2cumulativeMedian[1:138],
departurea), method=lm)
Warning message:
Computation failed in `stat_smooth()`:
'what' must be a function or character string