PYTHON

join on column pandas

# df1 as main df and use the feild from df2 and map it into df1

df1.merge(df2,on='columnName',how='left')

join pandas dataframe by column

df_outer = pd.merge(df1, df2, on='id', how='outer')
df_inner = pd.merge(df1, df2, on='id', how='inner')

joins in pandas

pd.merge(product,customer,left_on='Product_name',right_on='Purchased_Product')

joining pandas dataframes

df1 = pd.DataFrame(
    {
        "A": ["A0", "A1", "A2", "A3"],
        "B": ["B0", "B1", "B2", "B3"],
    }
)
df2 = pd.DataFrame(
    {
        "A": ["A4", "A5", "A6", "A7"],
        "B": ["B4", "B5", "B6", "B7"],
    }
)


df3 = pd.DataFrame(
    {
        "A": ["A8", "A9", "A10", "A11"],
        "B": ["B8", "B9", "B10", "B11"],
    }
)
frames = [df1, df2, df3]
result = pd.concat(frames, ignore_index=True)
"""
result = pd.DataFrame(
    {
        "A": ["A0", "A1", "A2", "A3", "A4", "A5", "A6", "A7", "A8", "A9", "A10", "A11"],
        "B": ["B0", "B1", "B2", "B3", "B4", "B5", "B6", "B7", "B8", "B9", "B10", "B11"],
    },
    index=[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11],
)
"""

join tables pandas

In [99]: result = left.join(right, on=['key1', 'key2'], how='inner')

joins in pandas

pd.merge(product,customer,how='inner',left_on=['Product_ID','Seller_City'],right_on=['Product_ID','City'])

joins in pandas

pd.merge(product,customer,on='Product_ID')

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

pandas join dataframe

#https://pandas.pydata.org/docs/user_guide/merging.html

pd df join

df.join(other.set_index('key'), on='key')

join tables pandas

In [88]: result = left.join(right, how='inner')