根据python中的cut来排序pandas数据帧？

Question

如果我pandas.cut用来生成垃圾箱标签[0.3, 0.5), ...,我怎样才能按照升序对这些垃圾箱进行排序？例如,[-0.4, -0.2)应该来[-0.2, 0.0),等等.例如:

df = pandas.DataFrame({"a": np.random.randn(10)})
# bin according to cut
df["bins"] = pandas.cut(df.a, np.linspace(-2,2,6))

现在如何根据cut(df["bins"]列)生成的标签对df进行排序？

Answer 1

如果您首先按列'a'排序df,那么您不需要对'bins'列进行排序

import pandas as pd
import numpy as np
df = pd.DataFrame({"a": np.random.randn(10)})
# for versions older than 0.17.0
df.sort(by=['a'],inplace=True)
# if running a newer version 0.17.0 or newer then you need
df.sort_values(by=['a'],inplace=True)
# bin according to cut
df["bins"] = pd.cut(df.a, np.linspace(-2,2,6))
df

Out[37]:
          a          bins
6 -1.273335    (-2, -1.2]
7 -0.604780  (-1.2, -0.4]
1 -0.467994  (-1.2, -0.4]
8  0.028114   (-0.4, 0.4]
9  0.032250   (-0.4, 0.4]
3  0.138368   (-0.4, 0.4]
0  0.541577    (0.4, 1.2]
5  0.838290    (0.4, 1.2]
2  1.171387    (0.4, 1.2]
4  1.770752      (1.2, 2]