Python绘制KS曲线的实现方法

python/' target='_blank'>python实现KS曲线，相关使用方法请参考上篇博客-R语言实现KS曲线

代码如下：

####################### PlotKS ##########################def PlotKS(preds, labels, n, asc):    # preds is score: asc=1  # preds is prob: asc=0    pred = preds # 预测值  bad = labels # 取1为bad, 0为good  ksds = DataFrame({'bad': bad, 'pred': pred})  ksds['good'] = 1 - ksds.bad    if asc == 1:    ksds1 = ksds.sort_values(by=['pred', 'bad'], ascending=[True, True])  elif asc == 0:    ksds1 = ksds.sort_values(by=['pred', 'bad'], ascending=[False, True])  ksds1.index = range(len(ksds1.pred))  ksds1['cumsum_good1'] = 1.0*ksds1.good.cumsum()/sum(ksds1.good)  ksds1['cumsum_bad1'] = 1.0*ksds1.bad.cumsum()/sum(ksds1.bad)    if asc == 1:    ksds2 = ksds.sort_values(by=['pred', 'bad'], ascending=[True, False])  elif asc == 0:    ksds2 = ksds.sort_values(by=['pred', 'bad'], ascending=[False, False])  ksds2.index = range(len(ksds2.pred))  ksds2['cumsum_good2'] = 1.0*ksds2.good.cumsum()/sum(ksds2.good)  ksds2['cumsum_bad2'] = 1.0*ksds2.bad.cumsum()/sum(ksds2.bad)    # ksds1 ksds2 -> average  ksds = ksds1[['cumsum_good1', 'cumsum_bad1']]  ksds['cumsum_good2'] = ksds2['cumsum_good2']  ksds['cumsum_bad2'] = ksds2['cumsum_bad2']  ksds['cumsum_good'] = (ksds['cumsum_good1'] + ksds['cumsum_good2'])/2  ksds['cumsum_bad'] = (ksds['cumsum_bad1'] + ksds['cumsum_bad2'])/2    # ks  ksds['ks'] = ksds['cumsum_bad'] - ksds['cumsum_good']  ksds['tile0'] = range(1, len(ksds.ks) + 1)  ksds['tile'] = 1.0*ksds['tile0']/len(ksds['tile0'])    qe = list(np.arange(0, 1, 1.0/n))  qe.append(1)  qe = qe[1:]    ks_index = Series(ksds.index)  ks_index = ks_index.quantile(q = qe)  ks_index = np.ceil(ks_index).astype(int)  ks_index = list(ks_index)    ksds = ksds.loc[ks_index]  ksds = ksds[['tile', 'cumsum_good', 'cumsum_bad', 'ks']]  ksds0 = np.array([[0, 0, 0, 0]])  ksds = np.concatenate([ksds0, ksds], axis=0)  ksds = DataFrame(ksds, columns=['tile', 'cumsum_good', 'cumsum_bad', 'ks'])    ks_value = ksds.ks.max()  ks_pop = ksds.tile[ksds.ks.idxmax()]  print ('ks_value is ' + str(np.round(ks_value, 4)) + ' at pop = ' + str(np.round(ks_pop, 4)))    # chart  plt.plot(ksds.tile, ksds.cumsum_good, label='cum_good',             color='blue', linestyle='-', linewidth=2)               plt.plot(ksds.tile, ksds.cumsum_bad, label='cum_bad',            color='red', linestyle='-', linewidth=2)              plt.plot(ksds.tile, ksds.ks, label='ks',          color='green', linestyle='-', linewidth=2)              plt.axvline(ks_pop, color='gray', linestyle='--')  plt.axhline(ks_value, color='green', linestyle='--')  plt.axhline(ksds.loc[ksds.ks.idxmax(), 'cumsum_good'], color='blue', linestyle='--')  plt.axhline(ksds.loc[ksds.ks.idxmax(),'cumsum_bad'], color='red', linestyle='--')  plt.title('KS=%s ' %np.round(ks_value, 4) +         'at Pop=%s' %np.round(ks_pop, 4), fontsize=15)    return ksds####################### over ##########################

作图效果如下：

以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持脚本之家。