gnuplot中的平均列值

Question

我的数据如下

0.5,187713,4.96,0.724973,0.01481065,72.84,15.53
0.6,167717,4.43,0.733582,0.01796329,75.73,24.52
0.7,152797,4.03,0.756354,0.02086922,77.89,31.24
0.8,136517,3.60,0.799969,0.02446527,80.25,38.56
0.9,123985,3.27,0.899915,0.02825937,82.06,44.20
1.0,115901,3.06,0.999732,0.03093004,83.23,47.84
1.1,108449,2.86,1.099942,0.03345339,84.31,51.20
1.2,101089,2.67,1.199958,0.03645456,85.37,54.51
1.3,95801,2.53,1.299897,0.03908459,86.14,56.89
1.4,90617,2.39,1.399975,0.04149375,86.89,59.22
1.5,86261,2.28,1.499799,0.04465310,87.52,61.18
1.6,81665,2.16,1.599730,0.04746546,88.18,63.25
1.7,75541,1.99,1.699975,0.05180608,89.07,66.00
1.8,71753,1.89,1.799943,0.05508243,89.62,67.71
1.9,68641,1.81,1.899839,0.05791313,90.07,69.11
2.0,65809,1.74,1.999994,0.06138851,90.48,70.38
2.1,62457,1.65,2.099834,0.06460564,90.96,71.89
2.2,59921,1.58,2.199455,0.06766316,91.33,73.03
2.3,57153,1.51,2.299838,0.07162909,91.73,74.28
2.4,54133,1.43,2.399758,0.07701663,92.17,75.64
2.5,51997,1.37,2.499986,0.08052349,92.48,76.60
2.6,49929,1.32,2.599958,0.08450297,92.78,77.53
2.7,47749,1.26,2.699994,0.08875672,93.09,78.51
2.8,46117,1.22,2.799693,0.09129460,93.33,79.25
2.9,44541,1.18,2.899123,0.09506496,93.56,79.96
3.0,42449,1.12,2.999615,0.10022962,93.86,80.90
0.5,363958,4.99,0.893074,0.00910343,68.40,-7.52
0.6,327814,4.49,0.885607,0.01095668,71.54,3.16
0.7,293146,4.02,0.854532,0.01319982,74.55,13.40
0.8,262754,3.60,0.825171,0.01558911,77.19,22.38
0.9,228338,3.13,0.899962,0.01902715,80.18,32.54
1.0,209250,2.87,0.999932,0.02151380,81.83,38.18
1.1,191994,2.63,1.099992,0.02434067,83.33,43.28
1.2,176146,2.42,1.199958,0.02678609,84.71,47.96
1.3,163674,2.24,1.299986,0.02972868,85.79,51.65
1.4,150718,2.07,1.399852,0.03245382,86.92,55.47
1.5,140770,1.93,1.499975,0.03466649,87.78,58.41
1.6,131222,1.80,1.599923,0.03772851,88.61,61.23
1.7,123078,1.69,1.699973,0.04065058,89.31,63.64
1.8,115958,1.59,1.799857,0.04318717,89.93,65.74
1.9,108574,1.49,1.899959,0.04667913,90.57,67.92
2.0,102922,1.41,1.999690,0.04887618,91.06,69.59
2.1,97694,1.34,2.099395,0.05191641,91.52,71.14
2.2,92662,1.27,2.199871,0.05443381,91.96,72.63
2.3,88414,1.21,2.299978,0.05684952,92.32,73.88
2.4,84422,1.16,2.399668,0.05921618,92.67,75.06
2.5,80010,1.10,2.499896,0.06153083,93.05,76.36
2.6,76902,1.05,2.599916,0.06406729,93.32,77.28
2.7,74738,1.02,2.699690,0.06577387,93.51,77.92
2.8,71402,0.98,2.799920,0.06812163,93.80,78.91
2.9,69494,0.95,2.899854,0.07040185,93.97,79.47
3.0,67802,0.93,2.999359,0.07110504,94.11,79.97
0.5,534550,4.14,0.734336,0.00835252,76.01,0.14
0.6,476090,3.69,0.720035,0.00992851,78.63,11.06
0.7,428958,3.33,0.725414,0.01170297,80.75,19.86
0.8,380154,2.95,0.799996,0.01400433,82.94,28.98
0.9,346950,2.69,0.899954,0.01620170,84.43,35.18
1.0,322358,2.50,0.999959,0.01831071,85.53,39.78
1.1,298446,2.31,1.099999,0.02039410,86.60,44.25
1.2,277966,2.15,1.199981,0.02250517,87.52,48.07
1.3,260462,2.02,1.299975,0.02448279,88.31,51.34
1.4,243746,1.89,1.399996,0.02647294,89.06,54.46
1.5,229794,1.78,1.499931,0.02863376,89.69,57.07
1.6,216470,1.68,1.599929,0.03059017,90.28,59.56
1.7,201230,1.56,1.699958,0.03353148,90.97,62.41
1.8,196614,1.52,1.799805,0.03449286,91.17,63.27
1.9,184150,1.43,1.899865,0.03673122,91.73,65.60
2.0,174902,1.36,1.999945,0.03896826,92.15,67.33
2.1,165938,1.29,2.100006,0.04116238,92.55,69.00
2.2,152798,1.18,2.199811,0.04479913,93.14,71.45
2.3,144942,1.12,2.299993,0.04762763,93.49,72.92
2.4,138230,1.07,2.399992,0.04986823,93.80,74.18
2.5,132038,1.02,2.499928,0.05213663,94.07,75.33
2.6,127214,0.99,2.599795,0.05376293,94.29,76.23
2.7,120298,0.93,2.699970,0.05624358,94.60,77.53
2.8,114262,0.89,2.799894,0.05943829,94.87,78.65
2.9,109318,0.85,2.899960,0.06168545,95.09,79.58
3.0,104310,0.81,2.999739,0.06380893,95.32,80.51
0.5,89890,1.69,0.755600,0.00422898,80.95,18.51
0.6,85038,1.60,0.748339,0.00456993,81.98,22.91
0.7,72838,1.37,0.759211,0.00544418,84.56,33.97
0.8,58858,1.11,0.800069,0.00675947,87.53,46.64
0.9,51682,0.97,0.899958,0.00792572,89.05,53.15
1.0,45974,0.87,0.999927,0.00903898,90.26,58.32
1.1,40886,0.77,1.099930,0.01020669,91.34,62.94
1.2,37006,0.70,1.199869,0.01139348,92.16,66.45
1.3,34054,0.64,1.299873,0.01247451,92.78,69.13
1.4,31186,0.59,1.399789,0.01361101,93.39,71.73
1.5,29202,0.55,1.499947,0.01491799,93.81,73.53
1.6,27118,0.51,1.599840,0.01589767,94.25,75.42
1.7,25534,0.48,1.699513,0.01710643,94.59,76.85
1.8,24302,0.46,1.799406,0.01799776,94.85,77.97
1.9,22534,0.42,1.899377,0.01915440,95.22,79.57
2.0,21586,0.41,1.999911,0.02004283,95.43,80.43
2.1,20946,0.39,2.099712,0.02191064,95.56,81.01
2.2,20170,0.38,2.199660,0.02283212,95.73,81.72
2.3,19134,0.36,2.299889,0.02365377,95.95,82.65
2.4,18362,0.35,2.399900,0.02465888,96.11,83.35
2.5,17638,0.33,2.500004,0.02573230,96.26,84.01
2.6,17282,0.33,2.599989,0.02678808,96.34,84.33
2.7,16334,0.31,2.698711,0.02664875,96.54,85.19
2.8,15910,0.30,2.799017,0.02837672,96.63,85.58
2.9,15514,0.29,2.899958,0.02954554,96.71,85.94
3.0,15234,0.29,2.998002,0.03020222,96.77,86.19
0.5,287898,5.11,0.726749,0.01140151,68.65,3.52
0.6,251562,4.47,0.740393,0.01399680,72.61,15.70
0.7,224914,3.99,0.771689,0.01705783,75.51,24.63
0.8,197218,3.50,0.799995,0.02070237,78.53,33.91
0.9,178274,3.16,0.899829,0.02424657,80.59,40.26
1.0,163942,2.91,0.999974,0.02702463,82.15,45.06
1.1,151798,2.69,1.099961,0.02969011,83.47,49.13
1.2,140698,2.50,1.199965,0.03246072,84.68,52.85
1.3,132298,2.35,1.299974,0.03494901,85.59,55.67
1.4,124078,2.20,1.400006,0.03771346,86.49,58.42
1.5,117798,2.09,1.499890,0.04049115,87.17,60.52
1.6,111338,1.98,1.599910,0.04290295,87.88,62.69
1.7,104162,1.85,1.699918,0.04631012,88.66,65.09
1.8,102090,1.81,1.799761,0.04713748,88.88,65.79
1.9,93682,1.66,1.899958,0.05178072,89.80,68.61
2.0,89590,1.59,1.999850,0.05435155,90.24,69.98
2.1,85438,1.52,2.099739,0.05697525,90.70,71.37
2.2,81782,1.45,2.199392,0.05973938,91.10,72.59
2.3,78194,1.39,2.299670,0.06251692,91.49,73.80
2.4,81362,1.44,2.399894,0.06098039,91.14,72.73
2.5,72966,1.30,2.499983,0.06687551,92.06,75.55
2.6,71042,1.26,2.599894,0.06841763,92.26,76.19
2.7,66342,1.18,2.699802,0.07292893,92.78,77.77
2.8,65978,1.17,2.799538,0.07353166,92.82,77.89
2.9,63942,1.14,2.899680,0.07552722,93.04,78.57
3.0,59486,1.06,2.999513,0.08029330,93.52,80.07

我想对数据做一个平均值（基于第一列），然后绘制平均值的第3和第4列。

注意：这里只有第1，第3和第4列很重要

例如0.5：

0.5,187713,4.96,0.724973,0.01481065,72.84,15.53
0.5,363958,4.99,0.893074,0.00910343,68.40,-7.52
0.5,534550,4.14,0.734336,0.00835252,76.01,0.14
0.5,89890,1.69,0.755600,0.00422898,80.95,18.51
0.5,287898,5.11,0.726749,0.01140151,68.65,3.52

离群值： 0.5,89890,1.69,0.755600,0.00422898,80.95,18.51

由于可能存在异常值，我认为中位数会比平均值更好（可以随意提出改进）以忽略异常值。

作为0.5的结果，我们将得到如下的单行：0.5,4.96,0.734336

我想重复数据中的每一点并绘制第3和第4列。它将是(4.96,0.734336)为0.5

如何使用gnuplot自动化它？

修改： 在考虑之后，意味着更好，因为数据是针对图像的，对于大型语料库，异常值可能会消失

此致

Answer 1

如果我正确理解您的问题，您想对过滤后的数据进行统计。 您可以使用三元运算符定义函数（检查 help ternary）

myFilter(colData,colFilter,valueFilter) = column(colFilter) == valueFilter ? column(colData) : NaN

如果另一列 (colData) 等于 colFilter，则返回特定数据列 (valueFilter) 的值，否则返回 NaN。

此外，您需要在 column1 中创建一个唯一的值列表，您希望将其用作过滤器和绘图中的 x 值。您可以通过将数据绘制到表格中并使用 smooth 选项（请参阅 help smooth）来实现这一点，例如frequency 或 unique，在这种情况下无关紧要。

如果您对作为表格值的中位数感兴趣，您需要对过滤的列执行 stats。 您不一定需要这部分来绘制情节，因为据我所知，绘图样式 with boxplot 可以为您完成所有这些工作。

现在，只需将 with boxplot 与过滤后的数据一起使用。

代码：

### filtered statistics
reset session

$Data <<EOD
0.5,187713,4.96,0.724973,0.01481065,72.84,15.53
0.6,167717,4.43,0.733582,0.01796329,75.73,24.52
0.7,152797,4.03,0.756354,0.02086922,77.89,31.24
0.8,136517,3.60,0.799969,0.02446527,80.25,38.56
0.9,123985,3.27,0.899915,0.02825937,82.06,44.20
1.0,115901,3.06,0.999732,0.03093004,83.23,47.84
1.1,108449,2.86,1.099942,0.03345339,84.31,51.20
1.2,101089,2.67,1.199958,0.03645456,85.37,54.51
1.3,95801,2.53,1.299897,0.03908459,86.14,56.89
1.4,90617,2.39,1.399975,0.04149375,86.89,59.22
1.5,86261,2.28,1.499799,0.04465310,87.52,61.18
1.6,81665,2.16,1.599730,0.04746546,88.18,63.25
1.7,75541,1.99,1.699975,0.05180608,89.07,66.00
1.8,71753,1.89,1.799943,0.05508243,89.62,67.71
1.9,68641,1.81,1.899839,0.05791313,90.07,69.11
2.0,65809,1.74,1.999994,0.06138851,90.48,70.38
2.1,62457,1.65,2.099834,0.06460564,90.96,71.89
2.2,59921,1.58,2.199455,0.06766316,91.33,73.03
2.3,57153,1.51,2.299838,0.07162909,91.73,74.28
2.4,54133,1.43,2.399758,0.07701663,92.17,75.64
2.5,51997,1.37,2.499986,0.08052349,92.48,76.60
2.6,49929,1.32,2.599958,0.08450297,92.78,77.53
2.7,47749,1.26,2.699994,0.08875672,93.09,78.51
2.8,46117,1.22,2.799693,0.09129460,93.33,79.25
2.9,44541,1.18,2.899123,0.09506496,93.56,79.96
3.0,42449,1.12,2.999615,0.10022962,93.86,80.90
0.5,363958,4.99,0.893074,0.00910343,68.40,-7.52
0.6,327814,4.49,0.885607,0.01095668,71.54,3.16
0.7,293146,4.02,0.854532,0.01319982,74.55,13.40
0.8,262754,3.60,0.825171,0.01558911,77.19,22.38
0.9,228338,3.13,0.899962,0.01902715,80.18,32.54
1.0,209250,2.87,0.999932,0.02151380,81.83,38.18
1.1,191994,2.63,1.099992,0.02434067,83.33,43.28
1.2,176146,2.42,1.199958,0.02678609,84.71,47.96
1.3,163674,2.24,1.299986,0.02972868,85.79,51.65
1.4,150718,2.07,1.399852,0.03245382,86.92,55.47
1.5,140770,1.93,1.499975,0.03466649,87.78,58.41
1.6,131222,1.80,1.599923,0.03772851,88.61,61.23
1.7,123078,1.69,1.699973,0.04065058,89.31,63.64
1.8,115958,1.59,1.799857,0.04318717,89.93,65.74
1.9,108574,1.49,1.899959,0.04667913,90.57,67.92
2.0,102922,1.41,1.999690,0.04887618,91.06,69.59
2.1,97694,1.34,2.099395,0.05191641,91.52,71.14
2.2,92662,1.27,2.199871,0.05443381,91.96,72.63
2.3,88414,1.21,2.299978,0.05684952,92.32,73.88
2.4,84422,1.16,2.399668,0.05921618,92.67,75.06
2.5,80010,1.10,2.499896,0.06153083,93.05,76.36
2.6,76902,1.05,2.599916,0.06406729,93.32,77.28
2.7,74738,1.02,2.699690,0.06577387,93.51,77.92
2.8,71402,0.98,2.799920,0.06812163,93.80,78.91
2.9,69494,0.95,2.899854,0.07040185,93.97,79.47
3.0,67802,0.93,2.999359,0.07110504,94.11,79.97
0.5,534550,4.14,0.734336,0.00835252,76.01,0.14
0.6,476090,3.69,0.720035,0.00992851,78.63,11.06
0.7,428958,3.33,0.725414,0.01170297,80.75,19.86
0.8,380154,2.95,0.799996,0.01400433,82.94,28.98
0.9,346950,2.69,0.899954,0.01620170,84.43,35.18
1.0,322358,2.50,0.999959,0.01831071,85.53,39.78
1.1,298446,2.31,1.099999,0.02039410,86.60,44.25
1.2,277966,2.15,1.199981,0.02250517,87.52,48.07
1.3,260462,2.02,1.299975,0.02448279,88.31,51.34
1.4,243746,1.89,1.399996,0.02647294,89.06,54.46
1.5,229794,1.78,1.499931,0.02863376,89.69,57.07
1.6,216470,1.68,1.599929,0.03059017,90.28,59.56
1.7,201230,1.56,1.699958,0.03353148,90.97,62.41
1.8,196614,1.52,1.799805,0.03449286,91.17,63.27
1.9,184150,1.43,1.899865,0.03673122,91.73,65.60
2.0,174902,1.36,1.999945,0.03896826,92.15,67.33
2.1,165938,1.29,2.100006,0.04116238,92.55,69.00
2.2,152798,1.18,2.199811,0.04479913,93.14,71.45
2.3,144942,1.12,2.299993,0.04762763,93.49,72.92
2.4,138230,1.07,2.399992,0.04986823,93.80,74.18
2.5,132038,1.02,2.499928,0.05213663,94.07,75.33
2.6,127214,0.99,2.599795,0.05376293,94.29,76.23
2.7,120298,0.93,2.699970,0.05624358,94.60,77.53
2.8,114262,0.89,2.799894,0.05943829,94.87,78.65
2.9,109318,0.85,2.899960,0.06168545,95.09,79.58
3.0,104310,0.81,2.999739,0.06380893,95.32,80.51
0.5,89890,1.69,0.755600,0.00422898,80.95,18.51
0.6,85038,1.60,0.748339,0.00456993,81.98,22.91
0.7,72838,1.37,0.759211,0.00544418,84.56,33.97
0.8,58858,1.11,0.800069,0.00675947,87.53,46.64
0.9,51682,0.97,0.899958,0.00792572,89.05,53.15
1.0,45974,0.87,0.999927,0.00903898,90.26,58.32
1.1,40886,0.77,1.099930,0.01020669,91.34,62.94
1.2,37006,0.70,1.199869,0.01139348,92.16,66.45
1.3,34054,0.64,1.299873,0.01247451,92.78,69.13
1.4,31186,0.59,1.399789,0.01361101,93.39,71.73
1.5,29202,0.55,1.499947,0.01491799,93.81,73.53
1.6,27118,0.51,1.599840,0.01589767,94.25,75.42
1.7,25534,0.48,1.699513,0.01710643,94.59,76.85
1.8,24302,0.46,1.799406,0.01799776,94.85,77.97
1.9,22534,0.42,1.899377,0.01915440,95.22,79.57
2.0,21586,0.41,1.999911,0.02004283,95.43,80.43
2.1,20946,0.39,2.099712,0.02191064,95.56,81.01
2.2,20170,0.38,2.199660,0.02283212,95.73,81.72
2.3,19134,0.36,2.299889,0.02365377,95.95,82.65
2.4,18362,0.35,2.399900,0.02465888,96.11,83.35
2.5,17638,0.33,2.500004,0.02573230,96.26,84.01
2.6,17282,0.33,2.599989,0.02678808,96.34,84.33
2.7,16334,0.31,2.698711,0.02664875,96.54,85.19
2.8,15910,0.30,2.799017,0.02837672,96.63,85.58
2.9,15514,0.29,2.899958,0.02954554,96.71,85.94
3.0,15234,0.29,2.998002,0.03020222,96.77,86.19
0.5,287898,5.11,0.726749,0.01140151,68.65,3.52
0.6,251562,4.47,0.740393,0.01399680,72.61,15.70
0.7,224914,3.99,0.771689,0.01705783,75.51,24.63
0.8,197218,3.50,0.799995,0.02070237,78.53,33.91
0.9,178274,3.16,0.899829,0.02424657,80.59,40.26
1.0,163942,2.91,0.999974,0.02702463,82.15,45.06
1.1,151798,2.69,1.099961,0.02969011,83.47,49.13
1.2,140698,2.50,1.199965,0.03246072,84.68,52.85
1.3,132298,2.35,1.299974,0.03494901,85.59,55.67
1.4,124078,2.20,1.400006,0.03771346,86.49,58.42
1.5,117798,2.09,1.499890,0.04049115,87.17,60.52
1.6,111338,1.98,1.599910,0.04290295,87.88,62.69
1.7,104162,1.85,1.699918,0.04631012,88.66,65.09
1.8,102090,1.81,1.799761,0.04713748,88.88,65.79
1.9,93682,1.66,1.899958,0.05178072,89.80,68.61
2.0,89590,1.59,1.999850,0.05435155,90.24,69.98
2.1,85438,1.52,2.099739,0.05697525,90.70,71.37
2.2,81782,1.45,2.199392,0.05973938,91.10,72.59
2.3,78194,1.39,2.299670,0.06251692,91.49,73.80
2.4,81362,1.44,2.399894,0.06098039,91.14,72.73
2.5,72966,1.30,2.499983,0.06687551,92.06,75.55
2.6,71042,1.26,2.599894,0.06841763,92.26,76.19
2.7,66342,1.18,2.699802,0.07292893,92.78,77.77
2.8,65978,1.17,2.799538,0.07353166,92.82,77.89
2.9,63942,1.14,2.899680,0.07552722,93.04,78.57
3.0,59486,1.06,2.999513,0.08029330,93.52,80.07
EOD

set datafile separator comma

# get unique values of column 1
set table $Dummy
    plot [*:*] $Data u 1:(1) smooth freq
unset table
set datafile separator whitespace
# get unique values to string, then it works also gnuplot 5.0.0
set table $Dummy2
    plot UniqueList='' $Dummy u (UniqueList=UniqueList." ".strcol(1),0) w table
unset table
set datafile separator comma

myFilter(colData,colFilter,valueFilter) = column(colFilter) == valueFilter ? column(colData) : NaN
Unique(i) = real(word(UniqueList,i))

# in case you need a table for the medians
# can be skipped for the boxplot
set print $myStats
    do for [i=1:words(UniqueList)] {
        stats $Data u (myFilter(3,1,Unique(i))) name "A" nooutput
        stats $Data u (myFilter(4,1,Unique(i))) name "B" nooutput
        print sprintf("%.1f, %.2f, %g",Unique(i),A_median, B_median)
    }
set print
print $myStats

plot for [i=1:words(UniqueList)] $Data u (Unique(i)): \
         (myFilter(3,1,Unique(i))):(0.05) w boxplot lc "red" title (i==1?'Column3':''), \
     for [i=1:words(UniqueList)] $Data u (Unique(i)): \
         (myFilter(4,1,Unique(i))):(0.05) w boxplot lc "web-green" title (i==1?'Column4':'')
### end of code

结果：

0.5, 4.96, 0.734336
0.6, 4.43, 0.740393
0.7, 3.99, 0.759211
0.8, 3.50, 0.799996
0.9, 3.13, 0.899954
1.0, 2.87, 0.999932
1.1, 2.63, 1.09996
1.2, 2.42, 1.19996
1.3, 2.24, 1.29997
1.4, 2.07, 1.39997
1.5, 1.93, 1.49993
1.6, 1.80, 1.59991
1.7, 1.69, 1.69996
1.8, 1.59, 1.79981
1.9, 1.49, 1.89986
2.0, 1.41, 1.99991
2.1, 1.34, 2.09974
2.2, 1.27, 2.19966
2.3, 1.21, 2.29989
2.4, 1.16, 2.39989
2.5, 1.10, 2.49998
2.6, 1.05, 2.59992
2.7, 1.02, 2.6998
2.8, 0.98, 2.79969
2.9, 0.95, 2.89985
3.0, 0.93, 2.99951