Question

我的数据框如下所示：

            timestamp              topAsk       topBid     CPA          midprice    CPB      spread   gamma_perc
    72554   2018-11-17 18:43:00 0.00307084  0.00306366  0.00307085  0.00306725  0.00306725  0.00000718  0.000000
    35867   2018-10-23 02:06:00 0.00445542  0.00444528  0.00445542  0.00445035  0.00445035  0.00001014  0.000000
    65021   2018-11-12 10:28:00 0.00327366  0.00326954  0.00327160  0.00327160  0.00327160  0.00000412  0.000000
    65020   2018-11-12 10:27:00 0.00327246  0.00326834  0.00327100  0.00327040  0.00327040  0.00000412  0.000000
    65017   2018-11-12 10:24:00 0.00327756  0.00327341  0.00327548  0.00327548  0.00327548  0.00000415  0.000000
    35872   2018-10-23 02:11:00 0.00445192  0.00444249  0.00445192  0.00444721  0.00444721  0.00000943  0.000000
    65016   2018-11-12 10:23:00 0.00327756  0.00327341  0.00327548  0.00327548  0.00327548  0.00000415  0.000000
    65015   2018-11-12 10:22:00 0.00327756  0.00327341  0.00327548  0.00327548  0.00327548  0.00000415  0.000000
    65014   2018-11-12 10:21:00 0.00327756  0.00327341  0.00327548  0.00327548  0.00327548  0.00000415  0.000000
    65013   2018-11-12 10:20:00 0.00327756  0.00327341  0.00327548  0.00327548  0.00327548  0.00000415  0.000000
    ... ... ... ... ... ... ... ... ...
    82213   2018-11-24 11:43:00 0.00324989  0.00324561  0.00325211  0.00324775  0.00324114  0.00000428  154.439252
    88427   2018-11-28 19:17:00 0.00342308  0.00341001  0.00342256  0.00341654  0.00339635  0.00001307  154.475899
    63023   2018-11-11 01:10:00 0.00336728  0.00336673  0.00336701  0.00336701  0.00336616  5.5E-7  154.545455
    17294   2018-10-10 04:32:00 0.00334544  0.00333056  0.00333802  0.00333800  0.00331500  0.00001488  154.569892
    34890   2018-10-22 09:49:00 0.00437069  0.00436719  0.00436894  0.00436894  0.00436353  0.00000350  154.571429
    30957   2018-10-19 16:16:00 0.00438949  0.00438403  0.00439011  0.00438676  0.00437832  0.00000546  154.578755
    23556   2018-10-14 12:55:00 0.00371373  0.00370981  0.00371279  0.00371177  0.00370571  0.00000392  154.591837
    38583   2018-10-24 23:22:00 0.00417979  0.00417406  0.00417915  0.00417692  0.00416806  0.00000573  154.624782
    62668   2018-11-10 19:15:00 0.00339415  0.00339102  0.00339259  0.00339259  0.00338775  0.00000313  154.632588

我需要做的是添加一个新列pread_bin并将散布的观察结果分类为大小相等的容器（A，B和C）。到目前为止，我尝试的是对数据框进行排序并将其切成3个数组，这些数组将成为我的垃圾箱，就像这样：

df_new_sample = df_new_sample.sort_values(by='spread')
sorted_array = np.sort(df_new_sample['spread'])
split_spreads = np.array_split(sorted_array, 3)

df_new_sample['spread_bin'] = df_new_sample['spread'].apply(lambda x: 'A' if x <= split_spreads[0][-1] else ( 'B' if split_spreads[0][-1] < x <= split_spreads[1][-1] else 'C'))

spread                bin
39478          1E-8   A
42804          1E-8   A
42411          1E-8   A
21897          1E-8   A
27103          1E-8   A
51190          1E-8   A
42452          1E-8   A
42288          1E-8   A
717            1E-8   A
23948          1E-8   A
            ...    
68148    0.00004299   C
76725    0.00004568   C
19495    0.00004706   C
19530    0.00004737   C
77057    0.00004761   C
17368    0.00005202   C
24590    0.00005365   C
19528    0.00006249   C
19489    0.00007012   C
19484    0.00011030   C

但是当我仔细检查每个箱柜中是否有相同数量的观测值时，我会有所不同……结果如何？

Answer 1

您看过qcut吗？

df_new_sample['spread_bin'] = pd.qcut(df_new_sample['spread'], 3, labels=['A', 'B', 'C'])

您的数据集恰好在边缘有重复项，因此，不可能将数据集存储到相等大小的bin中。但是，如果您不关心spread值是否渗入另一个bin中，则可以人为地创建一个排名列。

# first sort your df by `spread`
df_new_sample = df_new_sample.sort_values('spread')

# reset index
df_new_sample = df_new_sample.reset_index(drop=True)

# now qcut on the index
df_new_sample['spread_bin'] = pd.qcut(df_new_sample.index, 3, labels=['A', 'B', 'C']

注意：如果您希望每个bin中的观察数相同，则必须将df中的观察数除以3。

Answer 2

Pandas具有内置功能cut来做到这一点：

df_new_sample['spread_bin'] = pd.cut(df_new_sample['spread'], 3)

需要将一列拆分为三个不同的A-B-C箱，每个箱中的观察数相同

2 个答案: