pandas left join

1df.merge(df2, left_on = "doc_id", right_on = "doc_num", how = "left")

1# df1 as main df and use the feild from df2 and map it into df1
2
3df1.merge(df2,on='columnName',how='left')

1# Joins with another DataFrame
2
3df.join(df2, df.name == df2.name, 'outer').select(
4  df.name, df2.height).collect()
5# [Row(name=None, height=80), Row(name=u'Bob', height=85), Row(
6#   name=u'Alice', height=None)]
7
8df.join(df2, 'name', 'outer').select('name', 'height').collect()
9# [Row(name=u'Tom', height=80), Row(name=u'Bob', height=85), Row(
10#   name=u'Alice', height=None)]
11
12cond = [df.name == df3.name, df.age == df3.age]
13df.join(df3, cond, 'outer').select(df.name, df3.age).collect()
14# [Row(name=u'Alice', age=2), Row(name=u'Bob', age=5)]
15
16df.join(df2, 'name').select(df.name, df2.height).collect()
17# Row(name=u'Bob', height=85)]
18
19df.join(df4, ['name', 'age']).select(df.name, df.age).collect()
20# [Row(name=u'Bob', age=5)]

1>>> left.merge(right, on='user_id', how='left')  

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