Particularly now that shift only works on datetime-like indexes (#11211)
They look almost the same, although not exactly:
In [11]: df=pd.DataFrame(pd.np.random.rand(5,2), index=pd.date_range(periods=5, start='2000'))
In [12]: df
Out[12]:
0 1
2000-01-01 0.640148 0.781291
2000-01-02 0.261649 0.652372
2000-01-03 0.642422 0.734348
2000-01-04 0.582657 0.601868
2000-01-05 0.848645 0.078437
In [13]: df.shift()
Out[13]:
0 1
2000-01-01 NaN NaN
2000-01-02 0.640148 0.781291
2000-01-03 0.261649 0.652372
2000-01-04 0.642422 0.734348
2000-01-05 0.582657 0.601868
In [14]: df.tshift()
Out[14]:
0 1
2000-01-02 0.640148 0.781291
2000-01-03 0.261649 0.652372
2000-01-04 0.642422 0.734348
2000-01-05 0.582657 0.601868
2000-01-06 0.848645 0.078437
In [15]: df.shift(freq='D')
Out[15]:
0 1
2000-01-02 0.640148 0.781291
2000-01-03 0.261649 0.652372
2000-01-04 0.642422 0.734348
2000-01-05 0.582657 0.601868
2000-01-06 0.848645 0.078437
In [16]: df.tshift(freq='D')
Out[16]:
0 1
2000-01-02 0.640148 0.781291
2000-01-03 0.261649 0.652372
2000-01-04 0.642422 0.734348
2000-01-05 0.582657 0.601868
2000-01-06 0.848645 0.078437
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