qcut 中 bin 的对称数量在零附近

Symmetric number of bins in qcut around zero

我有一个 pandas 数据框,每行有不同数量的整数和 NaNs。我想将每行中的值分配到 8 个箱子中 - 每行 4 个箱子用于负值,4 个箱子用于正值。因此,每行的每个 bin 中将有不同数量的值。关于如何为此调整 qcut 功能的任何提示?谢谢!

如果我没理解错的话,你可以只对正值做 qcut,对负值做 qcut

例如,给定数据帧:

>>> df
        vals
0  -0.456460
1   0.448368
2   0.186750
3   1.056617
4  -0.035620
5  -0.609843
6   0.126376
7   0.160817
8  -1.495441
9   0.730763
10 -0.005071
11  0.677918
12 -0.779553
13  0.717374
14  2.250258
15 -0.801028
16  0.306408
17  0.538970
18 -2.120528
19  1.066903

使用 2 qcuts,一个为正,一个为负。

df.loc[df.vals > 0,'bin'] = pd.qcut(df.loc[df.vals > 0,'vals'], q=4)

df.loc[df.vals < 0,'bin'] = pd.qcut(df.loc[df.vals < 0,'vals'], q=4)

因此,它们被分为 8 个独特的箱子,4 个用于阳性,4 个用于阴性:

>>> df
        vals                 bin
0  -0.456460    (-0.695, -0.351]
1   0.448368      (0.276, 0.608]
2   0.186750      (0.125, 0.276]
3   1.056617       (0.812, 2.25]
4  -0.035620  (-0.351, -0.00507]
5  -0.609843    (-0.695, -0.351]
6   0.126376      (0.125, 0.276]
7   0.160817      (0.125, 0.276]
8  -1.495441    (-2.122, -0.975]
9   0.730763      (0.608, 0.812]
10 -0.005071  (-0.351, -0.00507]
11  0.677918      (0.608, 0.812]
12 -0.779553    (-0.975, -0.695]
13  0.717374      (0.608, 0.812]
14  2.250258       (0.812, 2.25]
15 -0.801028    (-0.975, -0.695]
16  0.306408      (0.276, 0.608]
17  0.538970      (0.276, 0.608]
18 -2.120528    (-2.122, -0.975]
19  1.066903       (0.812, 2.25]

您可以对 bin 进行排序以像这样可视化它们,这样您就可以看到 4 个正值 bin 和 4 个负值 bin:

np.sort(df['bin'].unique())

array([Interval(-2.1219999999999999, -0.97499999999999998, closed='right'),
       Interval(-0.97499999999999998, -0.69499999999999995, closed='right'),
       Interval(-0.69499999999999995, -0.35099999999999998, closed='right'),
       Interval(-0.35099999999999998, -0.0050699999999999999, closed='right'),
       Interval(0.125, 0.27600000000000002, closed='right'),
       Interval(0.27600000000000002, 0.60799999999999998, closed='right'),
       Interval(0.60799999999999998, 0.81200000000000006, closed='right'),
       Interval(0.81200000000000006, 2.25, closed='right')], dtype=object)