Question

我有一个numpy数组df，我为此使用该数组计算了10个分位数：

np.quantile(df, np.arange(0.1, 1.1, 0.1))

给出：

array([0.73518751, 0.73774966, 0.7415471 , 0.74462405, 0.74640229, 0.74952848, 0.7522163 , 0.75820953, 0.76289489, 0.76954299])

但是我也想知道这10个值（或最接近的值）的索引。基本上，哪个值反映了分位数与原始数组中最接近的分位数。

我该怎么做？

df

array([[0.74472344, 0.72122723, 0.75860745, 0.76498497, 0.70747197,
        0.74813282, 0.74042159, 0.74722695, 0.73554462, 0.75064671,
        0.74331897, 0.74716657, 0.73778194, 0.74615586, 0.76285201,
        0.75964642, 0.73241562, 0.75377691, 0.75396305, 0.75909799,
        0.73139387, 0.74406022, 0.7466802 , 0.74904978, 0.76954299,
        0.74861521, 0.73639923, 0.72030777, 0.76361781, 0.74158204,
        0.75146145, 0.7445026 , 0.75811005, 0.72869432, 0.74437159,
        0.73829693, 0.73757732, 0.75386381, 0.75234902, 0.76638651,
        0.75146788, 0.74095088, 0.72755104, 0.74487853, 0.74637753,
        0.73871291, 0.76512724, 0.75878656, 0.76340133, 0.75192058,
        0.74568671, 0.75875962, 0.74529624, 0.73688561, 0.75444639,
        0.74146557, 0.71298224, 0.76272094, 0.73547828, 0.73585916,
        0.73830914, 0.7449885 , 0.74602336, 0.75998384, 0.7620157 ,
        0.75025225, 0.75024652, 0.74897128, 0.736911  , 0.75200063,
        0.75215942, 0.75381088, 0.74398333, 0.74050236, 0.75152248,
        0.7435388 , 0.75403506, 0.76490963, 0.73895139, 0.74835008,
        0.76352328, 0.74488378, 0.75088626, 0.74712956, 0.76071763,
        0.75406158, 0.73689425, 0.73673624, 0.76328081, 0.73762053,
        0.74111873, 0.74642706, 0.76343733, 0.74263775, 0.73242599,
        0.74470502, 0.74260616, 0.74389631, 0.75280219, 0.73257053]])

Answer 1

您np.abs()和argmin()：

quantiles = np.quantile(df, np.arange(0.1, 1.1, 0.1))

[(np.abs(df - i)).argmin() for i in quantiles]

返回：

[58, 12, 29, 95, 44, 23, 70, 32, 14, 24]

如何找到数组分位数的索引？

1 个答案: