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追加された data.frame では、モニターによってファセット化された測定 t 日付を使用して、2 つの距離でデバイスの感度をトレンド分析したいと考えています。これは非常に簡単ですggplot2。reshape2最初にパッケージを使用してデータを溶かします

data.melt <- melt(big_df[,c(1:3,6)],id=c("Date","Monitor"))

次にggplot2を使用します

ggplot(data.melt, aes(x=Date, y=value, col=variable)) + geom_point() + facet_wrap(~Monitor)

これらのポイントにも geom_errorbar を追加したいと思います。私が抱えている問題は、50cm と 100cm の測定値で誤差範囲が異なり、限界を定義する方法がわからないことです. つまりvariable = Sensitivity.100cm、制限をvalue+/-Error.100cmおよび に設定した場合variable = Sensitivity.50cm limits = value+/-Error.50cm。このタスクに最もよく取り組むにはどうすればよいですか?

structure(list(Date = c("18/10/2012", "19/10/2012", "22/10/2012", 
"23/10/2012", "23/10/2012", "26/10/2012", "29/10/2012", "31/10/2012", 
"11/01/2012", "11/02/2012", "11/06/2012", "11/08/2012", "11/09/2012", 
"20/11/2012", "27/11/2012", "18/12/2012", "14/01/2012", "23/01/2013", 
"18/01/2013", "16/02/2013", "23/04/2013", "30/04/2013", "07/05/2013", 
"14/05/2013", "21/05/2013", "17/10/2012", "18/10/2012", "19/10/2012", 
"22/10/2012", "23/10/2012", "24/10/2012", "26/10/2012", "29/10/2012", 
"31/10/2012", "11/01/2012", "11/02/2012", "11/06/2012", "11/08/2012", 
"11/09/2012", "20/11/2012", "27/11/2012", "18/12/2012", "14/01/2013", 
"23/01/2013", "18/02/2013", "16/02/2013", "14/04/2013", "30/04/2013", 
"07/05/2013", "14/05/2013", "21/05/2013", "16/10/2012", "18/10/2012", 
"19/10/2012", "22/10/2012", "23/10/2012", "24/10/2012", "26/10/2012", 
"29/10/2012", "31/10/2012", "31/10/2012", "01/11/2012", "02/11/2012", 
"06/11/2012", "08/11/2012", "09/11/2012", "20/11/2012", "27/11/2012", 
"18/12/2012", "14/01/2013", "23/01/2013", "18/02/2013", "16/04/2013", 
"23/04/2013", "30/04/2013", "07/05/2013", "14/05/2013", "21/05/2013", 
"16/04/2013", "23/04/2013", "30/04/2013", "07/05/2013", "14/05/2013", 
"21/05/2013", "16/04/2013", "23/04/2013", "30/04/2013", "07/05/2013", 
"14/05/2013", "21/05/2013"), Sensitivity.100cm = c(23.9310344827586, 
23.6792452830189, 23.0708661417323, 23.75, 31.3333333333333, 
25.1351351351351, 25.9770114942529, 24.5192307692308, 25.4347826086957, 
22.987012987013, 23.1451612903226, 22.4822695035461, 23.4375, 
23.9495798319328, 23.5245901639344, 24.041095890411, 25.4198473282443, 
23.9097744360902, 25.8536585365854, 26.1940298507463, 28.0794701986755, 
26.4041095890411, 24.3875968992248, 24.7019867549669, 26.4383561643836, 
21.2328767123288, 23.5172413793103, 24.0566037735849, 30.7874015748032, 
23.1111111111111, 29.5, 23.0405405405405, 26.2068965517241, 25, 
24.3478260869565, 23.5064935064935, 22.0161290322581, 23.468085106383, 
22.8125, 25.3781512605042, 22.2131147540984, 24.7945205479452, 
23.6923076923077, 24.1353383458647, 25.2439024390244, 26.9402985074627, 
27.9470198675497, 23.8835616438356, 25.3798449612403, 25.0331125827815, 
25.7534246575342, 31.1627906976744, 30.6896551724138, 28.7735849056604, 
29.7637795275591, 28.5294117647059, 40, 29.7972972972973, 33.448275862069, 
33.4653465346535, 33.4653465346535, 36.9565217391304, 31.4285714285714, 
30.8870967741935, 28.5106382978723, 29.0625, 29.4117647058824, 
31.3934426229508, 33.5616438356164, 29.0151515151515, 30.8270676691729, 
29.6341463414634, 34.3283582089552, 32.7152317880795, 37.2602739726027, 
38.2945736434108, 35.8940397350993, 33.5616438356164, 40.5223880597015, 
36.0264900662252, 33.8356164383562, 34.4186046511628, 36.158940397351, 
33.7671232876712, 36.7910447761194, 36.0264900662252, 33.8356164383562, 
30.5426356589147, 36.158940397351, 33.7671232876712), Sensitivity.50cm = c(89.448275862069, 
89.4339622641509, 88.0314960629921, 88.4558823529412, 94.6666666666667, 
85.9459459459459, 92.2988505747126, 93.6538461538461, 91.5217391304348, 
88.2467532467532, 98.1451612903226, 85.6028368794326, 88.28125, 
90, 85.655737704918, 87.7397260273973, 88.7786259541985, 90.8270676691729, 
92.1341463414634, 89.6268656716418, 96.6887417218543, 91.1986301369863, 
89.7364341085271, 87.0198675496689, 90.4794520547945, 80.8219178082192, 
83.8620689655172, 85.188679245283, 82.992125984252, 88.1481481481482, 
93.3333333333333, 87.9054054054054, 90.6896551724138, 89.3269230769231, 
89.1304347826087, 90.1298701298701, 82.9032258064516, 82.6879432624114, 
87.265625, 88.8235294117647, 87.7868852459016, 90.5479452054795, 
91.7692307692308, 83.5338345864662, 92.0121951219512, 94.1044776119403, 
88.0132450331126, 90.8013698630137, 89.7984496124031, 87.6158940397351, 
88.2191780821918, 116.434108527132, 110, 116.509433962264, 112.44094488189, 
110.147058823529, 123.333333333333, 107.5, 119.655172413793, 
127.524752475248, 127.524752475248, 118.478260869565, 96.3636363636364, 
112.338709677419, 105.815602836879, 116.5625, 116.806722689076, 
118.27868852459, 129.452054794521, 113.106060606061, 115.789473684211, 
115, 133.582089552239, 132.05298013245, 136.575342465753, 154.573643410853, 
118.675496688742, 122.602739726027, 133.805970149254, 132.05298013245, 
136.575342465753, 154.573643410853, 132.185430463576, 136.506849315069, 
133.805970149254, 132.05298013245, 136.575342465753, 154.573643410853, 
132.185430463576, 136.506849315069), Error.100cm = c(1.3139695781557, 
1.56444565582802, 1.40192864683188, 1.36970117722038, 1.67497927018681, 
1.33092672997245, 1.78068199825628, 1.60608587389328, 1.71862916313499, 
1.29219147676184, 1.40378186980074, 1.29420479368047, 1.39754248593737, 
1.46276430130498, 1.42679468733846, 1.31571045974648, 1.42197984810665, 
1.39046932397796, 1.30208271366236, 1.4335352770372, 1.39230437361779, 
1.37754694254238, 1.41544528946403, 1.3095178763765, 1.37669529056451, 
1.81215843223602, 1.30671002217217, 1.60377358490566, 1.7304929902233, 
1.34969386357693, 1.63724022536571, 1.28022265685787, 1.79545969561073, 
1.60896158948861, 1.69788036432753, 1.30840530387077, 1.36621567307237, 
1.32512183966048, 1.37108818553002, 1.49853399160731, 1.39344262295082, 
1.33165904761805, 1.38033526499434, 1.40462719490747, 1.28772634645993, 
1.45283002492028, 1.38599003552691, 1.31267619160706, 1.44319351564034, 
1.32118790352715, 1.35955022200543, 1.5848874651365, 1.47108475915183, 
1.72669860544558, 1.61753059717907, 1.49248405369003, 1.86338998124982, 
1.44758684362355, 2.02050526795942, 1.88379184063767, 1.88379184063767, 
2.06235499576199, 1.47504112877929, 1.60684345525575, 1.45000342555042, 
1.53888403153064, 1.61641882871188, 1.63318515124355, 1.54679312200496, 
1.50945900342207, 1.55913092882163, 1.38241268887252, 1.63499270897065, 
1.48969826214596, 1.61504467432214, 1.74375533010884, 1.56437242530036, 
1.54679312200496, 1.76125727182178, 1.56156637384789, 1.54071532591808, 
1.65536096930718, 1.55875527098541, 1.54223702043804, 1.68034779838772, 
1.56156637384789, 1.54071532591808, 1.56197222322557, 1.55875527098541, 
1.54223702043804), Error.50cm = c(2.49898909406806, 2.94121835247545, 
2.66090476357729, 2.57562939531426, 2.84312035153866, 2.42491330336843, 
3.28542665010493, 3.03760942287141, 3.183873590408, 2.43051523015752, 
2.83178223646443, 2.48024233333982, 2.64934764965831, 2.77310924369748, 
2.66991761883645, 2.46860565629316, 2.61888806082572, 2.63908703380214, 
2.39518528553687, 2.6055358582233, 2.54601096513127, 2.51706504452232, 
2.65881302492679, 2.41699173389333, 2.50632526897698, 3.38331206444616, 
2.42264387175866, 2.88777884245547, 2.66556076847414, 2.57667068606312, 
2.82842712474619, 2.45392159423444, 3.26120941588761, 2.96210034629795, 
3.15029929264988, 2.45725817252266, 2.60322780509177, 2.44047901652299, 
2.62969260620419, 2.75266207632928, 2.70491803278689, 2.50538919974957, 
2.67245427169849, 2.53752436551672, 2.39363249102323, 2.66888876749965, 
2.42875772462149, 2.51128061073898, 2.6601687552902, 2.42695128500777, 
2.47524808213598, 3.02027282771754, 2.76292767227726, 3.35536212146769, 
3.02099623515762, 2.86858958869576, 3.22748612183951, 2.71029339461238, 
3.74049197592482, 3.5862911438168, 3.5862911438168, 3.62137635846906, 
2.52830160180932, 3.02499989250178, 2.75411175020533, 3.03382622483556, 
3.15545938748212, 3.12874339081841, 2.99339361416605, 2.94091650663359, 
2.96968686588444, 2.66763937246675, 3.1749324456989, 2.96611863265678, 
3.06769803788475, 3.47196832194708, 2.81593266562507, 2.91397909399762, 
3.17230019504959, 2.96611863265678, 3.06769803788475, 3.47196832194708, 
2.96463964047674, 3.06846257323317, 3.17230019504959, 2.96611863265678, 
3.06769803788475, 3.47196832194708, 2.96463964047674, 3.06846257323317
), Monitor = c("Berthold Red", "Berthold Red", "Berthold Red", 
"Berthold Red", "Berthold Red", "Berthold Red", "Berthold Red", 
"Berthold Red", "Berthold Red", "Berthold Red", "Berthold Red", 
"Berthold Red", "Berthold Red", "Berthold Red", "Berthold Red", 
"Berthold Red", "Berthold Red", "Berthold Red", "Berthold Red", 
"Berthold Red", "Berthold Red", "Berthold Red", "Berthold Red", 
"Berthold Red", "Berthold Red", "Berthold Blue", "Berthold Blue", 
"Berthold Blue", "Berthold Blue", "Berthold Blue", "Berthold Blue", 
"Berthold Blue", "Berthold Blue", "Berthold Blue", "Berthold Blue", 
"Berthold Blue", "Berthold Blue", "Berthold Blue", "Berthold Blue", 
"Berthold Blue", "Berthold Blue", "Berthold Blue", "Berthold Blue", 
"Berthold Blue", "Berthold Blue", "Berthold Blue", "Berthold Blue", 
"Berthold Blue", "Berthold Blue", "Berthold Blue", "Berthold Blue", 
"NC 61", "NC 61", "NC 61", "NC 61", "NC 61", "NC 61", "NC 61", 
"NC 61", "NC 61", "NC 61", "NC 61", "NC 61", "NC 61", "NC 61", 
"NC 61", "NC 61", "NC 61", "NC 61", "NC 61", "NC 61", "NC 61", 
"NC 61", "NC 61", "NC 61", "NC 61", "NC 61", "NC 61", "Mini Red", 
"Mini Red", "Mini Red", "Mini Red", "Mini Red", "Mini Red", "Mini Blue", 
"Mini Blue", "Mini Blue", "Mini Blue", "Mini Blue", "Mini Blue"
)), .Names = c("Date", "Sensitivity.100cm", "Sensitivity.50cm", 
"Error.100cm", "Error.50cm", "Monitor"), class = "data.frame", row.names = c(NA, 
90L))
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2 に答える 2

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1 つの解決策は、2 つの融解したデータ フレームを作成することです。1 つは値用、もう 1 つはエラー用です。2 番目のmelt()関数では、別の名前を持つように変更value.name=されました。value2

data.melt1 <- melt(big_df[,c(1:3,6)],id=c("Date","Monitor"))
data.melt2 <- melt(big_df[,c(1,4,5,6)],id=c("Date","Monitor"),value.name="value2")

value2次に、最初のデータ フレームと2 番目のデータ フレームの列をまとめます。

data.tog<-cbind(data.melt1,data.melt2["value2"])

head(data.tog)
        Date      Monitor          variable    value   value2
1 18/10/2012 Berthold Red Sensitivity.100cm 23.93103 1.313970
2 19/10/2012 Berthold Red Sensitivity.100cm 23.67925 1.564446
3 22/10/2012 Berthold Red Sensitivity.100cm 23.07087 1.401929
4 23/10/2012 Berthold Red Sensitivity.100cm 23.75000 1.369701
5 23/10/2012 Berthold Red Sensitivity.100cm 31.33333 1.674979
6 26/10/2012 Berthold Red Sensitivity.100cm 25.13514 1.330927

geom_errorbar()使用中とvalue+value2セットvalue-value2するymaxとymin.

ggplot(data.tog, aes(x=Date, y=value, col=variable)) + 
  geom_point() + 
  geom_errorbar(aes(ymin=value-value2,ymax=value+value2))+facet_wrap(~Monitor)
于 2013-05-22T10:16:34.320 に答える