In [1]:
import pandas as pd

In [2]:
df1 = pd.DataFrame({
    'name':['john','mary'],
    'age':[24,45]
})
df1


Out[2]:
age name
0 24 john
1 45 mary

In [23]:
df2 = pd.DataFrame({
    'name':['mary','john'],
    'age':[45,89]
})
df2


Out[23]:
age name
0 45 mary
1 89 john

union-all


In [25]:
pd.concat([
    df1,df2
],ignore_index=True)


Out[25]:
age name
0 24 john
1 45 mary
2 45 mary
3 89 john

union


In [24]:
pd.concat([
    df1,df2
],ignore_index=True).drop_duplicates().reset_index(drop=True)


Out[24]:
age name
0 24 john
1 45 mary
2 89 john

In [ ]:

concatenate side-by-side


In [30]:
pd.concat([
    df1,df2
],axis=1)


Out[30]:
age name age name
0 24 john 45 mary
1 45 mary 89 john

In [31]:
pd.concat([
    df1,df2
],axis=1).reset_index(drop=True)['age']


Out[31]:
age age
0 24 45
1 45 89

In [ ]: