concat pandas python

1# Concating Means putting frames on bottom of one another
2#              ---   ---
3#              |  df1  |
4#              |  df2  |
5# Concating => |   .   |
6#              |   .   |
7#              |  dfn  |
8#              ---   ---
9# Command : pd.concat([df1,df2,...,dfn])   ; df = a dataframe
10
11				 	''':::Eaxmple;::'''
12df1 = pd.DataFrame({'A': ['A0', 'A1', 'A2', 'A3'],
13                    'B': ['B0', 'B1', 'B2', 'B3'],
14                    'C': ['C0', 'C1', 'C2', 'C3'],
15                    'D': ['D0', 'D1', 'D2', 'D3']},
16                     index=[0, 1, 2, 3])
17
18df2 = pd.DataFrame({'A': ['A4', 'A5', 'A6', 'A7'],
19                    'B': ['B4', 'B5', 'B6', 'B7'],
20                    'C': ['C4', 'C5', 'C6', 'C7'],
21                    'D': ['D4', 'D5', 'D6', 'D7']},
22                     index=[4, 5, 6, 7])
23
24df3 = pd.DataFrame({'A': ['A8', 'A9', 'A10', 'A11'],
25                    'B': ['B8', 'B9', 'B10', 'B11'],
26                    'C': ['C8', 'C9', 'C10', 'C11'],
27                    'D': ['D8', 'D9', 'D10', 'D11']},
28                     index=[8, 9, 10, 11])
29
30frames = [df1, df2, df3]
31
32result = pd.concat(frames)
33
34# Note : use ignore_index=True if you need it in pd.concat

1# provide list of dataframes 
2res = pd.concat([df1, df2])

1>>> s1 = pd.Series(['a', 'b'])
2>>> s2 = pd.Series(['c', 'd'])
3>>> pd.concat([s1, s2])
40    a
51    b
60    c
71    d
8dtype: object
9

1# Pandas for Python
2
3df['col1 & col2'] = df['col1']+df['col2']
4
5#Output
6#col1	col2	col1 & col2
7#A1		A2		A1A2
8#B1		B2		B1B2