Dataframes concatenation with pd.concat in Pandas

Pandas pd.concat

pd.concat method in Pandas appends either rows or columns of Dataframes, if axis=0 is given in pd.conact rows would be appended and with axis=1, columns would be appended. Lets take an example to understand pd.concat

Create two Dataframes


import pandas as pd

df1 = pd.DataFrame({'col1': ['one', 'two', 'one', 'test', 'three','test2'],
                   'col2': ['aaa', 'bbb', 'ccc', 'eec', 'gggg', 'ggkk'],
                   'col3': [11, 23, 34, 46, 56, 66]})



df2 = pd.DataFrame({'col1': [56, 78, 78 , 89],
                   'col2': ['aaa', 'bbb', 'ccc', 'ddd'],
                   'col3': [11, 23, 34, 46]})

print(df1)
print(df2)

Output:


    col1  col2  col3
0    one   aaa    11
1    two   bbb    23
2    one   ccc    34
3   test   eec    46
4  three  gggg    56
5  test2  ggkk    66


   col1 col2  col3
0    56  aaa    11
1    78  bbb    23
2    78  ccc    34
3    89  ddd    46

Apply `pd.concat` along axis=0


df3 = pd.concat([df1, df2])

print("Concat along axis=0, i.e increased number of rows ")
print(df3)

Output:


Concat along axis=0, i.e increased number of rows
    col1  col2  col3
0    one   aaa    11
1    two   bbb    23
2    one   ccc    34
3   test   eec    46
4  three  gggg    56
5  test2  ggkk    66
0     56   aaa    11
1     78   bbb    23
2     78   ccc    34
3     89   ddd    46

Apply `pd.concat` along axis=1


df4 = pd.concat([df1, df2], axis=1)
print("Concat along axis=1, i.e increased number of Columns ")
print(df4)

Output:


Concat along axis=1, i.e increased number of Columns
    col1  col2  col3  col1 col2  col3
0    one   aaa    11  56.0  aaa  11.0
1    two   bbb    23  78.0  bbb  23.0
2    one   ccc    34  78.0  ccc  34.0
3   test   eec    46  89.0  ddd  46.0
4  three  gggg    56   NaN  NaN   NaN
5  test2  ggkk    66   NaN  NaN   NaN