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wesm avatar wesm commented on May 13, 2024

This can be done now in DataMatrix:

In [8]: dm
Out[8]: 
                       A           B           C           D           
2000-01-03 00:00:00    0.6304     -1.382      -0.242      -1.268      
2000-01-04 00:00:00    0.8243     -0.7684      0.177       0.8974     
2000-01-05 00:00:00    0.9411     -1.207       0.5106      0.9171     
2000-01-06 00:00:00   -2.778       0.9804     -0.4023      0.8694     
2000-01-07 00:00:00    0.09416    -0.4447     -1.29        0.9119     
2000-01-10 00:00:00    0.1413     -0.09031    -2.086       0.5024     
2000-01-11 00:00:00    0.1153     -0.6895     -0.06137     0.4239     
2000-01-12 00:00:00   -1.076      -1.304      -0.01166    -0.3801     
2000-01-13 00:00:00    0.5593     -0.8308     -1.671      -0.4757     
2000-01-14 00:00:00   -0.7621      0.04529     0.8069      0.2096     


In [9]: dm.xs(dm.index[5], copy=False)[:] = 10

In [10]: dm
Out[10]: 
                       A           B           C           D           
2000-01-03 00:00:00    0.6304     -1.382      -0.242      -1.268      
2000-01-04 00:00:00    0.8243     -0.7684      0.177       0.8974     
2000-01-05 00:00:00    0.9411     -1.207       0.5106      0.9171     
2000-01-06 00:00:00   -2.778       0.9804     -0.4023      0.8694     
2000-01-07 00:00:00    0.09416    -0.4447     -1.29        0.9119     
2000-01-10 00:00:00    10          10          10          10         
2000-01-11 00:00:00    0.1153     -0.6895     -0.06137     0.4239     
2000-01-12 00:00:00   -1.076      -1.304      -0.01166    -0.3801     
2000-01-13 00:00:00    0.5593     -0.8308     -1.671      -0.4757     
2000-01-14 00:00:00   -0.7621      0.04529     0.8069      0.2096

Not possible (yet) in DataFrame, but on the todo list in the fancy indexing category

from pandas.

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