混乱的实验室：Te-s-r-act，是 TensorAct，还是 Tesseract ?
找到了一本书：利用Python进行数据分析：
README
from tensorflow import keras
import numpy as np
import pandas as pd
import matplotlib.pyplot as pltIn [143]: df.to_csv('foo.csv')In [144]: pd.read_csv('foo.csv')In [147]: df.to_excel('foo.xlsx', sheet_name='Sheet1')In [148]: pd.read_excel('foo.xlsx', 'Sheet1', index_col=None, na_values=['NA'])import numpy as np
import pandas as pdmy_series = pd.Series(data, index)pd.DataFrame(data,index)df = pd.DataFrame(data,index) In [135]: ts = pd.Series(np.random.randn(1000),
.....: index=pd.date_range('1/1/2000', periods=1000))
.....:
In [136]: ts = ts.cumsum()
In [137]: ts.plot()
Out[137]: <matplotlib.axes._subplots.AxesSubplot at 0x7f2b5771ac88>In [138]: df = pd.DataFrame(np.random.randn(1000, 4), index=ts.index,
.....: columns=['A', 'B', 'C', 'D'])
.....:
In [139]: df = df.cumsum()
In [140]: plt.figure()
Out[140]: <Figure size 640x480 with 0 Axes>
In [141]: df.plot()
Out[141]: <matplotlib.axes._subplots.AxesSubplot at 0x7f2b53a2d7f0>
In [142]: plt.legend(loc='best')
Out[142]: <matplotlib.legend.Legend at 0x7f2b539728d0>import numpy as np
from scipy import stats # 其他的子模块类似