Example 1: join on column pandas
df1.merge(df2,on='columnName',how='left')
Example 2: join tables pandas
In [99]: result = left.join(right, on=['key1', 'key2'], how='inner')
Example 3: merge dataframe pandas
>>> df1.merge(df2, left_on='lkey', right_on='rkey')
lkey value_x rkey value_y
0 foo 1 foo 5
1 foo 1 foo 8
2 foo 5 foo 5
3 foo 5 foo 8
4 bar 2 bar 6
5 baz 3 baz 7
Example 4: merge dataframe in python
In [1]: df1 = pd.DataFrame({'A': ['A0', 'A1', 'A2', 'A3'],
...: 'B': ['B0', 'B1', 'B2', 'B3'],
...: 'C': ['C0', 'C1', 'C2', 'C3'],
...: 'D': ['D0', 'D1', 'D2', 'D3']},
...: index=[0, 1, 2, 3])
...:
In [2]: df2 = pd.DataFrame({'A': ['A4', 'A5', 'A6', 'A7'],
...: 'B': ['B4', 'B5', 'B6', 'B7'],
...: 'C': ['C4', 'C5', 'C6', 'C7'],
...: 'D': ['D4', 'D5', 'D6', 'D7']},
...: index=[4, 5, 6, 7])
...:
In [3]: df3 = pd.DataFrame({'A': ['A8', 'A9', 'A10', 'A11'],
...: 'B': ['B8', 'B9', 'B10', 'B11'],
...: 'C': ['C8', 'C9', 'C10', 'C11'],
...: 'D': ['D8', 'D9', 'D10', 'D11']},
...: index=[8, 9, 10, 11])
...:
In [4]: frames = [df1, df2, df3]
In [5]: result = pd.concat(frames)
Example 5: join in pandas
import pandas as pd
clients = {'Client_ID': [111,222,333,444,555],
'Client_Name': ['Jon Snow','Maria Green', 'Bill Jones','Rick Lee','Pamela Lopez']
}
df1 = pd.DataFrame(clients, columns= ['Client_ID','Client_Name'])
countries = {'Client_ID': [111,222,333,444,777],
'Client_Country': ['UK','Canada','Spain','China','Brazil']
}
df2 = pd.DataFrame(countries, columns= ['Client_ID', 'Client_Country'])
Inner_Join = pd.merge(df1, df2, how='inner', on=['Client_ID', 'Client_ID'])
print(Inner_Join)
Example 6: join to dataframes pandas
>>> df.join(other.set_index('key'), on='key')
key A B
0 K0 A0 B0
1 K1 A1 B1
2 K2 A2 B2
3 K3 A3 NaN
4 K4 A4 NaN
5 K5 A5 NaN