Append/Replace a row in a pandas DataFrame

[Paulo da Silva]

Hi all.
I am learning pandas DataFrame and I want to add (eventually replace by
index) some rows.
For adding here is what I tried:

>df = pd.DataFrame(np.random.randn(6,4), index=dates, columns=list('ABCD'))

>df
                   A         B         C         D
2013-01-01 -0.111621  1.126761 -2.420517  0.660948
2013-01-02 -0.243397 -0.975684 -0.679209 -0.656913
2013-01-03  0.405816  0.478353  0.621906 -0.262615
2013-01-04 -0.380249  0.416711 -0.906286  1.828339
2013-01-05  0.772747  0.993784  0.452746  1.665306
2013-01-06  0.535011 -0.662874  1.504281  0.543537

[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?!

How do I do to have a row replaced instead of added if its date (index)
is an existent one?

Thanks for any help or comments.
Paulo