Example 1: join on column pandas
df1.merge(df2,on='columnName',how='left')
Example 2: pandas left join
df.merge(df2, left_on = "doc_id", right_on = "doc_num", how = "left")
Example 3: joins in pandas
pd.merge(product,customer,on='Product_ID')
Example 4: python dataframe left join
>>> left.merge(right, on='user_id', how='left')
Example 5: union 2 dataframe pandas
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)