如何在R中绘制x轴上的多列Z

Question

我是R新手。 我有一个数据框，其部分看起来像this。 （原始数据大小为20 x 50）

我需要在X轴上绘制所有V1〜V20列的图。我期待一个简单的线条图，如this（没有传说）。

我试着在网站上实现类似问题的答案，但是我无法让它们工作。

任何帮助将不胜感激！先谢谢你。

编辑： 我尝试使用dput（）复制我的数据（对不起很长），希望它有助于使我的问题可以理解。

structure(c(2.99982, 3.999675, 3.33302, 3.24972, 2.799696, 2.49968, 
2.571129, 2.624715, 2.666393, 2.699736, 2.908808, 3.166378, 3.845871, 
3.714002, 3.466402, 3.249752, 3.35268, 3.277515, 3.315537, 3.249746, 
3.380693, 3.317921, 3.347573, 3.333084, 3.279749, 3.268982, 3.184931, 
3.142602, 3.206634, 3.166403, 3.128768, 3.124738, 3.151259, 3.146805, 
3.114031, 3.055297, 3.107844, 3.026058, 2.999742, 2.974741, 2.95096, 
2.952123, 2.97649, 2.954291, 2.955303, 2.934529, 2.935918, 2.937249, 
2.979337, 3.039743, 1.99971, 2.99982, 2.33308, 2.249738, 2.199732, 
2.33308, 2.571201, 2.624779, 2.88864, 2.799747, 2.999727, 2.916393, 
2.768947, 2.785438, 2.79973, 2.999724, 3.11736, 3.055268, 2.947075, 
2.999718, 2.999723, 2.954268, 2.869282, 2.999714, 2.959714, 2.884325, 
2.851561, 2.856856, 2.930741, 3.066375, 3.031966, 3.062215, 3.030018, 
2.999715, 3.028293, 3.083049, 3.05377, 3.05235, 3.051003, 3.124719, 
3.146066, 3.094959, 3.092747, 3.090635, 3.066392, 3.064945, 3.084838, 
3.041396, 3.020137, 3.01973, 0, 0.999855, 2.66645, 2.749792, 
2.799798, 2.833135, 2.856947, 2.499829, 2.777573, 2.599776, 2.727063, 
2.749793, 3.076712, 3.356929, 3.199774, 3.062263, 2.99976, 3.055325, 
2.999766, 2.949764, 3.047371, 3.09067, 3.173663, 3.083078, 2.999738, 
2.961276, 2.962703, 3.071165, 3.068705, 3.166403, 3.193291, 3.218498, 
3.181565, 3.08799, 3.114045, 3.027544, 3.026795, 3.052404, 3.025412, 
2.974766, 2.950984, 2.952147, 3.023019, 3.09067, 3.088651, 3.08672, 
3.169976, 3.124759, 3.101799, 3.09976, 1.999965, 2.999973, 3.333309, 
3.499977, 3.399976, 2.999973, 3.142831, 2.874972, 3.222197, 3.499977, 
3.545432, 3.333309, 3.076901, 3.071406, 2.999976, 2.874975, 2.705859, 
2.777755, 2.947346, 3.049979, 3.142836, 3.136342, 3.086935, 3.166645, 
3.159978, 3.115362, 3.148126, 3.10712, 3.103426, 3.166644, 3.12901, 
3.093727, 3.060583, 2.970565, 2.999977, 2.972199, 2.918895, 2.868397, 
2.871771, 2.899976, 2.829245, 2.83331, 2.953465, 2.931794, 2.911087, 
2.89128, 2.914869, 2.895809, 2.857118, 2.879975, 2.999973, 1.499986, 
1.666646, 2.499982, 2.799982, 2.666645, 2.714264, 2.499975, 2.333307, 
2.499974, 2.454519, 2.249975, 2.461515, 2.642835, 2.599977, 2.624976, 
2.647035, 2.777755, 2.842082, 2.949978, 2.952358, 2.909068, 2.826063, 
2.749975, 2.799975, 2.769206, 2.740715, 2.821404, 2.827561, 2.933309, 
3.032235, 2.968726, 2.969673, 2.970564, 2.942833, 2.972198, 2.918894, 
2.894712, 2.871769, 2.824974, 2.829242, 2.880927, 2.883695, 2.931793, 
2.999975, 3.043454, 3.042529, 3.062476, 3.122425, 3.099976, 6.99975, 
6.99975, 6.66638, 6.249668, 5.399676, 4.66633, 4.285384, 4.249703, 
4.333017, 4.199697, 4.181536, 4.249703, 4.230489, 4.49973, 4.46641, 
4.312241, 4.17621, 4.277512, 4.36815, 4.299734, 4.333057, 4.226996, 
4.260584, 4.249724, 4.239732, 4.268955, 4.184909, 4.106866, 3.999719, 
4.066383, 3.999716, 3.968469, 3.999714, 3.970305, 3.914002, 3.860827, 
3.837557, 3.947091, 3.922802, 3.899728, 3.853386, 3.904487, 3.929953, 
3.863354, 3.910827, 3.869281, 3.850782, 3.853889, 3.836459, 3.859721, 
3.99993, 3.499875, 2.99982, 3.499748, 3.19974, 2.999735, 3.14262, 
2.874743, 3.11083, 2.999718, 2.727016, 2.583065, 2.384368, 2.428329, 
2.399754, 2.499765, 2.41152, 2.33308, 2.262897, 2.249738, 2.33308, 
2.272467, 2.391035, 2.416401, 2.359729, 2.307417, 2.407124, 2.606865, 
2.654902, 2.766393, 2.83843, 2.81222, 2.908808, 2.88207, 2.999718, 
2.97194, 3.0808, 3.05235, 3.025359, 2.999718, 3.024113, 3.047347, 
3.022983, 2.999727, 2.977505, 2.97799, 2.935896, 2.874732, 2.897695, 
2.899738, 3.999981, 3.999981, 3.333309, 3.499977, 3.199975, 3.666645, 
3.428548, 3.499977, 3.555533, 3.19998, 3.090887, 2.999977, 2.84613, 
3.142831, 3.133307, 3.249975, 3.411741, 3.388865, 3.368397, 3.299975, 
3.23807, 3.181793, 3.304323, 3.249975, 3.239975, 3.307668, 3.259234, 
3.178546, 3.172388, 3.099974, 3.161265, 3.156224, 3.151489, 3.147033, 
3.142831, 3.194419, 3.216191, 3.289449, 3.333309, 3.349976, 3.317049, 
3.380928, 3.348813, 3.318157, 3.333309, 3.326063, 3.361678, 3.312475, 
3.28569, 3.339976, 1.999965, 2.999973, 3.999981, 4.249983, 4.399984, 
4.499985, 4.428556, 4.249983, 4.111093, 3.999981, 3.818161, 3.583311, 
3.538439, 3.78569, 3.866643, 3.687475, 3.647034, 3.55553, 3.52629, 
3.499974, 3.333309, 3.272702, 3.304323, 3.291642, 3.199975, 3.230744, 
3.111087, 3.142833, 3.03446, 3.066644, 3.096751, 3.124977, 3.151492, 
3.117624, 3.085691, 2.999977, 2.97295, 2.947345, 2.897412, 2.899976, 
2.853634, 2.833309, 2.860441, 2.863612, 2.888864, 2.86954, 2.872316, 
2.895809, 2.938751, 2.899975, 0.999957, 1.499961, 2.999973, 2.499969, 
2.59997, 3.166641, 3.28569, 3.249975, 3.444421, 3.499977, 3.545432, 
3.499977, 3.461515, 3.428548, 3.599978, 3.624978, 3.470565, 3.555533, 
3.473661, 3.499977, 3.428548, 3.590885, 3.521714, 3.541642, 3.559975, 
3.461513, 3.703679, 3.642832, 3.655147, 3.733309, 3.645136, 3.624975, 
3.606035, 3.558798, 3.485688, 3.444418, 3.378352, 3.368394, 3.384589, 
3.399974, 3.390218, 3.357116, 3.372067, 3.386337, 3.377752, 3.3478, 
3.319122, 3.29164, 3.265279, 3.319974, 2.999973, 2.499969, 1.999965, 
2.499969, 2.59997, 2.666637, 2.999973, 2.624976, 2.888867, 2.799976, 
2.636338, 2.583307, 2.461511, 2.357114, 2.399972, 2.499972, 2.411736, 
2.444416, 2.526288, 2.449971, 2.428542, 2.499971, 2.608668, 2.624972, 
2.799971, 2.846126, 2.777749, 2.785686, 2.758592, 2.766638, 2.87094, 
2.812472, 2.818153, 2.823501, 2.857115, 2.916639, 2.864837, 2.947341, 
2.897408, 2.924972, 2.951192, 2.976163, 2.90695, 2.863609, 2.844417, 
2.934755, 3.042525, 3.104139, 3.14283, 3.119973, 1.999965, 3.499977, 
3.999981, 3.249975, 2.59998, 2.833313, 2.714264, 2.999979, 3.333315, 
3.499982, 3.454527, 3.416647, 3.230748, 3.071406, 3.133311, 3.124977, 
3.117624, 3.055532, 3.10524, 3.099976, 3.047595, 3.13634, 3.043454, 
2.999975, 3.119976, 3.230746, 3.296274, 3.321406, 3.379288, 3.399978, 
3.451591, 3.374978, 3.42422, 3.441154, 3.485693, 3.499978, 3.459438, 
3.473662, 3.461516, 3.399977, 3.414612, 3.35712, 3.348814, 3.409068, 
3.377755, 3.347803, 3.425508, 3.374976, 3.346915, 3.339976, 4.999989, 
2.499995, 2.333318, 2.999986, 2.799982, 3.666645, 3.999981, 3.999981, 
3.999981, 3.999981, 4.545435, 4.333313, 4.153824, 4.285694, 4.333314, 
4.31248, 4.294098, 4.333314, 4.263138, 4.14998, 3.952362, 3.999981, 
3.913024, 3.833313, 3.87998, 3.76921, 3.666645, 3.67855, 3.551703, 
3.566646, 3.516108, 3.468728, 3.42422, 3.411742, 3.399978, 3.4722, 
3.405383, 3.499977, 3.512798, 3.549977, 3.512172, 3.476167, 3.441837, 
3.38634, 3.333309, 3.282584, 3.297848, 3.249975, 3.265281, 3.239975, 
1.999965, 2.499969, 2.999973, 2.499969, 2.399968, 2.166633, 2.142823, 
2.249967, 2.222189, 2.299967, 2.181785, 2.083299, 2.230736, 2.285682, 
2.666634, 2.812468, 2.882322, 2.833302, 2.842074, 2.799969, 2.904732, 
2.863606, 2.826056, 2.791636, 2.67997, 2.615355, 2.6296, 2.642827, 
2.655143, 2.699971, 2.709648, 2.624972, 2.696942, 2.676442, 2.685686, 
2.749972, 2.675649, 2.631552, 2.640998, 2.624973, 2.829241, 2.880926, 
2.860438, 2.818155, 2.822195, 2.847799, 2.851037, 2.895807, 2.918341, 
2.859974, 5.999997, 3.499977, 3.666645, 2.999973, 2.999973, 3.166641, 
3.28569, 3.374976, 3.222197, 3.099974, 2.818158, 2.833309, 2.84613, 
2.785689, 2.799975, 2.812475, 2.941152, 2.888864, 2.789448, 2.849974, 
2.857117, 2.727248, 2.826063, 2.874976, 2.879976, 2.923053, 2.999977, 
2.964262, 2.965493, 3.03331, 3.032235, 3.031226, 2.939371, 2.941153, 
2.971406, 2.999977, 2.97295, 3.236818, 3.230745, 3.299977, 3.34144, 
3.33331, 3.325558, 3.295431, 3.288865, 3.282585, 3.340402, 3.374977, 
3.428549, 3.479978, 6.999954, 3.999955, 4.666636, 4.749974, 4.999979, 
4.499976, 4.142832, 3.624978, 3.333309, 3.599978, 3.727252, 3.499977, 
3.84613, 3.714261, 3.599974, 3.499974, 3.470562, 3.444418, 3.52629, 
3.599975, 3.619023, 3.54543, 3.39128, 3.374976, 3.279975, 3.192282, 
3.07405, 3.107119, 3.137907, 3.133309, 3.129008, 3.124976, 3.121188, 
3.029388, 3.057119, 2.999976, 3.027003, 3.026292, 3.025617, 3.049976, 
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3.166643, 3.122425, 3.079976, 0.999957, 0.999957, 1.333293, 1.249959, 
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2.947338, 3.049971, 3.285685, 3.409063, 3.347797, 3.416639, 3.359972, 
3.307664, 3.296268, 3.357115, 3.275834, 3.299972, 3.322553, 3.374973, 
3.363609, 3.352914, 3.371402, 3.333306, 3.270243, 3.315762, 3.256383, 
3.224972, 3.146314, 3.16664, 3.162764, 3.204519, 3.266641, 3.260844, 
3.234016, 3.187473, 3.163239, 3.159973, 2.999973, 3.999981, 2.999973, 
3.499977, 3.799979, 3.333309, 3.142831, 2.999973, 3.444415, 3.199969, 
3.090878, 2.916635, 2.692278, 2.499973, 2.466639, 2.499972, 2.47056, 
2.499972, 2.473656, 2.549972, 2.666639, 2.909063, 2.869537, 2.999973, 
3.039973, 3.115359, 3.074048, 3.035688, 3.034456, 3.099974, 3.096748, 
3.093724, 3.030276, 2.999973, 2.971401, 2.944417, 2.945919, 2.947341, 
2.897408, 2.949973, 2.951192, 2.880926, 2.883694, 2.999973, 3.022195, 
3.021712, 2.999973, 2.999973, 2.979565, 3.019973, 0.999957, 2.999973, 
3.666645, 3.499977, 3.399976, 2.833313, 2.857122, 2.874978, 2.999979, 
2.999978, 2.999978, 3.083311, 2.923053, 2.928547, 3.066644, 2.937476, 
2.823504, 2.888864, 2.894712, 2.899975, 2.904737, 2.909066, 2.869539, 
2.916641, 3.039975, 2.999975, 2.9259, 2.928546, 2.999975, 2.933308, 
3.096748, 3.093724, 3.121186, 3.058797, 2.999973, 2.999973, 3.027, 
3.078921, 3.076897, 3.074974, 3.073144, 3.047592, 3.069741, 3.090883, 
3.044418, 3.043452, 3.042527, 3.062473, 3.102015, 3.059973, 6.999954, 
4.49996, 4.3333, 3.249975, 2.799971, 2.666637, 2.571398, 2.499969, 
2.666637, 2.499969, 2.727244, 2.916639, 2.769202, 2.857115, 2.866639, 
2.999973, 2.999973, 3.222194, 3.157866, 3.049971, 3.04759, 2.999971, 
3.086928, 2.999971, 2.999971, 2.961509, 2.925896, 2.999971, 2.965488, 
2.966638, 3.03223, 3.031222, 2.969668, 2.999971, 3.028543, 3.13886, 
3.081052, 3.078918, 3.051253, 3.024971, 3.024361, 3.02378, 2.999971, 
3.022698, 3.022193, 3.02171, 3.042524, 2.999971, 3.040788, 3.039971), .Dim = c(50L, 20L)) 

Answer 1

假设您在数据的每一列都有随机散步，并且您想将它们绘制在同一图上。基本绘图功能matplot可让您轻松完成此操作。

首先创建数据

mat <- matrix(sample(c(1,-1),1000, replace = T), nrow = 100,10) 
df <- data.frame(1:100, mat) 

然后累积求和每一列制作一个简单的随机游走

df[,2:11] <- apply(df[,2:11], 2, cumsum) 
names(df) <- c("index", paste0("Var",1:10)) 

然后用传说绘制。 df[,-1]告诉您从matplot中排除索引变量。

matplot(df[1], df[,-1], type="l", 
      xlab = "index", lty = 1) 
legend("right", legend = names(df)[-1], inset= .01) 

还有许多其他的方式来可视化数据的列，这只是其中的一个。