The multidimensional matrix calculate package, you can handle three-dimensional data just like pd.DataFrame handle two-dimensional data Usually for financial quantification timeseries data
多维矩阵计算库，它能像pd.DataFrame处理二维数据那样处理三维数据，常用于金融量化时序类数据
pip install ematrix
from ematrix import Matrix
dm = Matrix()
print('data_matrix:', dm)
res = dm[dm['code'] == '000001']
print('data_matrix_slice:\n', res)
data_matrix:
['close', 'high', 'low', 'open', 'ret']
100
000001 [0.80676805 0.30489957...0.83385824 0.56749199]
000002 [0.0158474 0.65408549...0.14293321 0.76696439]
......
200
000001 [0.62020139 0.96969446...0.76984185 0.14326731]
000002 [0.82182821 0.10924971...0.9967727 0.51963606]
......
......
400
...
000003 [0.15914842 0.99641071...0.15914842 0.99641071]
Dimension: ['timestamp', 'code', 'features'], Shape: (4, 3, 5), dtype: matrix
data_matrix_slice:
close high low open ret
100 0.806768 0.304900 0.210918 0.833858 0.567492
200 0.620201 0.969694 0.754948 0.769842 0.143267
300 0.008385 0.087556 0.994873 0.706558 0.752703
400 0.388965 0.946414 0.967339 0.567995 0.071485