如何从Python词典列表中访问某些键

问题描述

我正在使用几种评分方法使用cross_validate。 results变量是字典列表。我正在尝试使用results['test_f1_score']访问不同型号的F1分数，但是却得到了TypeError: list indices must be integers or slices,not tuple。从列表中获取F1分数的最佳方法是什么？

这是从结果变量生成的列表：

[{'fit_time': array([3.25437379,3.31360006,4.55807948,4.13171291,4.19844866,5.00323677,4.02107215,4.18458176,4.82133555,4.25998092,3.76690507,3.97073889,4.82378697,4.32887745,4.66021585,4.54414296,5.0830574,4.85126257,5.40511918,5.04520845,5.11681008,4.93635201,4.74664378,5.08661175,4.32240748,4.10375977,4.31480002,4.04965734,3.78688979,3.88911653]),'score_time': array([0.14319539,0.12677526,0.10101032,0.09385777,0.06942415,0.11760497,0.06548786,0.05601525,0.07890821,0.07988477,0.06272411,0.07337427,0.07825518,0.04193068,0.04330111,0.04155302,0.05201483,0.0699327,0.05248165,0.04978824,0.05156302,0.05214596,0.07210374,0.06283927,0.04857302,0.05679178,0.04323983,0.04890585,0.04407573,0.05073118]),'test_f1_score': array([0.03381643,0.06428571,0.01939058,0.02870813,0.05673759,0.05128205,0.06306306,0.01066667,0.08275862,0.0180791,0.03755869,0.04013378,0.04255319,0.07619048,0.04494382,0.08181818,0.02181818,0.02171291,0.03367003,0.04195804,0.01532567,0.05687204,0.0591716,0.05825243,0.07659574,0.04848485,0.01724138,0.02247191,0.01233046,0.01920439]),'test_f05_measure': array([0.02168525,0.04174397,0.01229796,0.01840491,0.03683241,0.03355705,0.04137116,0.00676133,0.05576208,0.01143511,0.02386635,0.02599653,0.02873563,0.05012531,0.02985075,0.05369928,0.01390176,0.01374465,0.02181501,0.02722323,0.00967586,0.03740648,0.03816794,0.03836317,0.05011136,0.0312989,0.01089918,0.01447178,0.00780762,0.01217815]),'test_sensitivity': array([0.5,0.64285714,0.5,0.42857143,0.57142857,0.28571429,0.85714286,0.21428571,0.35714286,0.71428571,0.5       ]),'test_specificity': array([0.96783961,0.9789689,0.94263502,0.96743044,0.97872166,0.98248629,0.98355021,0.9400933,0.98977003,0.92937229,0.94983633,0.97716858,0.9898527,0.98461538,0.98690564,0.98387757,0.95662493,0.93403716,0.97724855,0.97823062,0.91636661,0.98436989,0.97430442,0.98477905,0.98264997,0.97479335,0.92585318,0.97233816,0.93518291,0.94205745])},{'fit_time': array([266.90850329,276.56025481,286.16302919,277.08430457,286.8862102,288.08904719,288.04218554,272.11777163,275.47355413,272.80465865,277.46604395,264.88494945,276.60775948,279.0381875,277.55336189,279.63098645,259.44465542,258.57707739,262.15785336,263.71264052,270.20684457,269.78548741,269.23725843,265.4925046,221.50381541,220.98780727,224.46779513,212.47151136,219.48664856,215.95075083]),'score_time': array([10.18801832,8.01537871,3.33346009,7.78975368,2.98581243,2.70479202,2.86861777,8.02667737,9.41659141,10.13697696,6.73046923,9.69650173,4.27995682,3.4434793,3.63535523,4.40075231,10.22509551,10.44048429,9.14734888,7.9576447,3.13996601,4.10830784,2.80078673,2.92972565,6.48999166,6.47848701,3.41430521,6.733845,1.51497555,2.96808743]),'test_f1_score': array([0.63636364,0.92307692,0.96296296,0.75,0.92857143,0.83333333,0.72727273,0.8,0.88,0.88888889,0.96551724,0.66666667]),'test_f05_measure': array([0.76086957,0.96774194,0.98484848,0.92592593,0.86956522,0.86206897,0.94827586,0.90909091,0.94594595,0.83333333]),0.78571429,1.,'test_specificity': array([0.99991817,0.99991817,0.99991816,1.        ])},{'fit_time': array([174.20313787,198.07899594,184.28722906,178.60294867,199.02107191,179.50637341,174.12752724,178.98297739,154.63025308,167.98617458,178.08862185,168.87556529,154.76291323,163.30928159,142.50800228,165.50385952,168.07484317,161.5811913,157.46719265,153.52208304,171.98308134,158.28413796,141.83335066,168.22751117,143.11924505,133.29637599,141.15710378,150.20137,149.12544584,130.72285938]),'score_time': array([10.3494947,18.17751551,7.69723105,14.2464962,19.54308391,7.40629816,13.88110065,14.76199102,11.11700416,9.4580555,12.19720626,11.57381821,15.72216558,10.20245957,10.69855881,13.65211844,14.3795464,16.48296714,10.02136064,11.43304801,15.07670116,12.36216903,9.41213584,11.64626813,8.78664351,11.56165099,8.66782999,7.65322256,8.58487797,8.68105125]),'test_f1_score': array([0.00107335,0.00068248,0.00094757,0.00183083,0.00252127,0.00114827,0.00064725,0.00101868,0.00189095,0.00243717,0.00251467,0.00230814,0.00161264,0.00114833,0.00164609,0.00261584,0.00213311,0.00060588,0.00067877,0.00191205,0.00125274,0.00163043,0.00184945,0.00174004,0.00291333,0.00147438,0.00357782,0.00063331,0.00130506,0.00108421]),'test_f05_measure': array([0.0006721,0.00042731,0.00059321,0.00114647,0.00157841,0.00071875,0.00040591,0.00063781,0.00118381,0.00152567,0.00157398,0.00144697,0.00100961,0.00071915,0.00103029,0.00163812,0.00133618,0.00037988,0.00042499,0.00119904,0.00078425,0.00102194,0.00115816,0.00108951,0.00182432,0.00092328,0.00224316,0.00039714,0.00081706,0.00067892]),'test_sensitivity': array([0.21428571,0.14285714,0.07142857,0.21428571]),'test_specificity': array([0.54394435,0.52168576,0.48322422,0.55458265,0.48244537,0.43129552,0.74834274,0.5193551,0.48228169,0.46452247,0.41612111,0.71783961,0.49410802,0.57381342,0.40502496,0.56371225,0.61789017,0.73107456,0.51902774,0.74457812,0.47888707,0.7002455,0.55908347,0.53126023,0.55233653,0.55741059,0.72714625,0.74277764,0.4997954,0.54849006])}]

解决方法

您必须遍历列表：

def get_values(res,k)
  out = []
  for v in res:
    if k in v
      out.append(v[k])
  return out

out = get_values(results,'test_f1_score')

或单行：

out = [v['test_f1_score'] for v in results if 'test_f1_score' in v]

,

使用列表理解来遍历列表项，并为每个字典获取'test_f1_score'：

1. 遍历结果：for item in results
   
2. 正在验证当前结果的键为“ test_f1_score”：if 'test_f1_score' in item.keys()
   2.1。如果它具有“ test_f1_score”，则将其添加到列表中：item['test_f1_score']
   

f1_scores = [item['test_f1_score'] for item in results if 'test_f1_score' in item.keys()]

输出：

[array([0.03381643,0.06428571,0.01939058,0.02870813,0.05673759,0.05128205,0.06306306,0.01066667,0.08275862,0.0180791,0.03755869,0.04013378,0.04255319,0.07619048,0.04494382,0.08181818,0.02181818,0.02171291,0.03367003,0.04195804,0.01532567,0.05687204,0.0591716,0.05825243,0.07659574,0.04848485,0.01724138,0.02247191,0.01233046,0.01920439]),array([0.63636364,0.92307692,0.96296296,0.75,0.92857143,0.83333333,0.72727273,0.8,0.88,0.88888889,0.96551724,0.66666667]),array([0.00107335,0.00068248,0.00094757,0.00183083,0.00252127,0.00114827,0.00064725,0.00101868,0.00189095,0.00243717,0.00251467,0.00230814,0.00161264,0.00114833,0.00164609,0.00261584,0.00213311,0.00060588,0.00067877,0.00191205,0.00125274,0.00163043,0.00184945,0.00174004,0.00291333,0.00147438,0.00357782,0.00063331,0.00130506,0.00108421])]