Pandas: Appending a row to a dataframe and specify its index label

The name of the Series becomes the index of the row in the DataFrame:

In [99]: df = pd.DataFrame(np.random.randn(8, 4), columns=['A','B','C','D'])

In [100]: s = df.xs(3)

In [101]: s.name = 10

In [102]: df.append(s)
Out[102]: 
           A         B         C         D
0  -2.083321 -0.153749  0.174436  1.081056
1  -1.026692  1.495850 -0.025245 -0.171046
2   0.072272  1.218376  1.433281  0.747815
3  -0.940552  0.853073 -0.134842 -0.277135
4   0.478302 -0.599752 -0.080577  0.468618
5   2.609004 -1.679299 -1.593016  1.172298
6  -0.201605  0.406925  1.983177  0.012030
7   1.158530 -2.240124  0.851323 -0.240378
10 -0.940552  0.853073 -0.134842 -0.277135

df.loc will do the job :

>>> df = pd.DataFrame(np.random.randn(3, 2), columns=['A','B'])
>>> df
          A         B
0 -0.269036  0.534991
1  0.069915 -1.173594
2 -1.177792  0.018381
>>> df.loc[13] = df.loc[1]
>>> df
           A         B
0  -0.269036  0.534991
1   0.069915 -1.173594
2  -1.177792  0.018381
13  0.069915 -1.173594