Concatenate rows of two dataframes in pandas

call concat and pass param axis=1 to concatenate column-wise:

In [5]:

pd.concat([df_a,df_b], axis=1)
Out[5]:
        AAseq Biorep  Techrep Treatment     mz      AAseq1 Biorep1  Techrep1  \
0  ELVISLIVES      A        1         C  500.0  ELVISLIVES       A         1   
1  ELVISLIVES      A        1         C  500.5  ELVISLIVES       A         1   
2  ELVISLIVES      A        1         C  501.0  ELVISLIVES       A         1   

  Treatment1  inte1  
0          C   1100  
1          C   1050  
2          C   1010  

There is a useful guide to the various methods of merging, joining and concatenating online.

For example, as you have no clashing columns you can merge and use the indices as they have the same number of rows:

In [6]:

df_a.merge(df_b, left_index=True, right_index=True)
Out[6]:
        AAseq Biorep  Techrep Treatment     mz      AAseq1 Biorep1  Techrep1  \
0  ELVISLIVES      A        1         C  500.0  ELVISLIVES       A         1   
1  ELVISLIVES      A        1         C  500.5  ELVISLIVES       A         1   
2  ELVISLIVES      A        1         C  501.0  ELVISLIVES       A         1   

  Treatment1  inte1  
0          C   1100  
1          C   1050  
2          C   1010  

And for the same reasons as above a simple join works too:

In [7]:

df_a.join(df_b)
Out[7]:
        AAseq Biorep  Techrep Treatment     mz      AAseq1 Biorep1  Techrep1  \
0  ELVISLIVES      A        1         C  500.0  ELVISLIVES       A         1   
1  ELVISLIVES      A        1         C  500.5  ELVISLIVES       A         1   
2  ELVISLIVES      A        1         C  501.0  ELVISLIVES       A         1   

  Treatment1  inte1  
0          C   1100  
1          C   1050  
2          C   1010