concat in pandas

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showing results for - "concat in pandas"
Luca
16 Jul 2020
1In [1]: s1 = pd.Series([1, 2], index=['A', 'B'], name='s1')
2
3In [2]: s2 = pd.Series([3, 4], index=['A', 'B'], name='s2')
4
5In [3]: pd.concat([s1, s2], axis=1)
6Out[3]:
7   s1  s2
8A   1   3
9B   2   4
10
11In [4]: pd.concat([s1, s2], axis=1).reset_index()
12Out[4]:
13  index  s1  s2
140     A   1   3
151     B   2   4
16
source
Gabriele
20 Feb 2020
1In [1]: df1 = pd.DataFrame(
2   ...:     {
3   ...:         "A": ["A0", "A1", "A2", "A3"],
4   ...:         "B": ["B0", "B1", "B2", "B3"],
5   ...:         "C": ["C0", "C1", "C2", "C3"],
6   ...:         "D": ["D0", "D1", "D2", "D3"],
7   ...:     },
8   ...:     index=[0, 1, 2, 3],
9   ...: )
10   
11In [8]: df4 = pd.DataFrame(
12   ...:     {
13   ...:         "B": ["B2", "B3", "B6", "B7"],
14   ...:         "D": ["D2", "D3", "D6", "D7"],
15   ...:         "F": ["F2", "F3", "F6", "F7"],
16   ...:     },
17   ...:     index=[2, 3, 6, 7],
18   ...: )
19   ...: 
20
21In [9]: result = pd.concat([df1, df4], axis=1)
22# This will merge columns of both the dataframes
source
Soren
20 Jun 2017
1# provide list of dataframes 
2res = pd.concat([df1, df2])
source
Paxton
29 Feb 2019
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
source
April
02 Oct 2016
1In [1]: df1 = pd.DataFrame({'A': ['A0', 'A1', 'A2', 'A3'],
2   ...:                     'B': ['B0', 'B1', 'B2', 'B3'],
3   ...:                     'C': ['C0', 'C1', 'C2', 'C3'],
4   ...:                     'D': ['D0', 'D1', 'D2', 'D3']},
5   ...:                    index=[0, 1, 2, 3])
6   ...: 
7
8In [2]: df2 = pd.DataFrame({'A': ['A4', 'A5', 'A6', 'A7'],
9   ...:                     'B': ['B4', 'B5', 'B6', 'B7'],
10   ...:                     'C': ['C4', 'C5', 'C6', 'C7'],
11   ...:                     'D': ['D4', 'D5', 'D6', 'D7']},
12   ...:                    index=[4, 5, 6, 7])
13   ...: 
14
15In [3]: df3 = pd.DataFrame({'A': ['A8', 'A9', 'A10', 'A11'],
16   ...:                     'B': ['B8', 'B9', 'B10', 'B11'],
17   ...:                     'C': ['C8', 'C9', 'C10', 'C11'],
18   ...:                     'D': ['D8', 'D9', 'D10', 'D11']},
19   ...:                    index=[8, 9, 10, 11])
20   ...: 
21
22In [4]: frames = [df1, df2, df3]
23
24In [5]: result = pd.concat(frames)
25
source
Elena
02 Jun 2018
1In [1]: df1 = pd.DataFrame(
2   ...:     {
3   ...:         "A": ["A0", "A1", "A2", "A3"],
4   ...:         "B": ["B0", "B1", "B2", "B3"],
5   ...:         "C": ["C0", "C1", "C2", "C3"],
6   ...:         "D": ["D0", "D1", "D2", "D3"],
7   ...:     },
8   ...:     index=[0, 1, 2, 3],
9   ...: )
10   ...: 
11
12In [2]: df2 = pd.DataFrame(
13   ...:     {
14   ...:         "A": ["A4", "A5", "A6", "A7"],
15   ...:         "B": ["B4", "B5", "B6", "B7"],
16   ...:         "C": ["C4", "C5", "C6", "C7"],
17   ...:         "D": ["D4", "D5", "D6", "D7"],
18   ...:     },
19   ...:     index=[4, 5, 6, 7],
20   ...: )
21   ...: 
22
23In [3]: df3 = pd.DataFrame(
24   ...:     {
25   ...:         "A": ["A8", "A9", "A10", "A11"],
26   ...:         "B": ["B8", "B9", "B10", "B11"],
27   ...:         "C": ["C8", "C9", "C10", "C11"],
28   ...:         "D": ["D8", "D9", "D10", "D11"],
29   ...:     },
30   ...:     index=[8, 9, 10, 11],
31   ...: )
32   ...: 
33
34In [4]: frames = [df1, df2, df3]
35
36In [5]: result = pd.concat(frames)
37
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