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