Append/Replace a row in a pandas DataFrame [SOLVED]

[Paulo da Silva]

Às 21:10 de 13-04-2016, Paulo da Silva escreveu:
> Hi all.
...

> [6 rows x 4 columns]
> 
>> dft=pd.DataFrame([[1,2,3,4]],
> index=[datetime.date(2016,1,12)],columns=df.columns)
> 
>> dft
>             A  B  C  D
> 2016-01-12  1  2  3  4
> 
> [1 rows x 4 columns]
> 
>> pd.concat([df,dft])
> Out[71]:
>                             A         B         C         D
> 2013-01-01 00:00:00 -0.111621  1.126761 -2.420517  0.660948
> 2013-01-02 00:00:00 -0.243397 -0.975684 -0.679209 -0.656913
> 2013-01-03 00:00:00  0.405816  0.478353  0.621906 -0.262615
> 2013-01-04 00:00:00 -0.380249  0.416711 -0.906286  1.828339
> 2013-01-05 00:00:00  0.772747  0.993784  0.452746  1.665306
> 2013-01-06 00:00:00  0.535011 -0.662874  1.504281  0.543537
> 2016-01-12           1.000000  2.000000  3.000000  4.000000
> 
> [7 rows x 4 columns]
> 
> Why am I getting the second column?!
I need to use for example pd.datetime instead of datetime.date. In fact
there is no extra col but the inclusion of hour in the index.
Still don't understand why!

> 
> How do I do to have a row replaced instead of added if its date (index)
> is an existent one?
df.loc[<the index>]=<the new/replacement list/tuple line>

Paulo