Using Join in python [closed]

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I am converting an SQL code, that has a join function, to Python.

This is the SQL code:

INSERT INTO tropical_fruits
SELECT DISTINCT A.* 
FROM fruits A LEFT OUTER JOIN tropical_fruits B 
ON A.[fruit1] = B.[fruit1] AND A.[fruit2] = B.[fruit2];

Python conversion code is:

data = pd.merge(
    fruits, tropical_fruits,
    left_on=['fruit1','fruit2'], 
    right_on=['fruit1','fruit2'], 
    how='left'
)

But I haven't got the desired result. Is the Python code correct?

Python code is creating a new column with _x and _y suffix of these two columns 'fruit1','fruit2'. — Angel
– Angel, Commented Mar 2, 2024 at 15:18
out = fruits.merge(tropical_fruits, on=['fruit1','fruit2'], how='left') — Panda Kim
– Panda Kim, Commented Mar 2, 2024 at 15:22
read this post : pandas-merging-101 and If this is not enough, please read the following notice and provide minimal reproducible example — Panda Kim
– Panda Kim, Commented Mar 2, 2024 at 15:42

L Tyrone · Accepted Answer · 2024-03-03 00:31:34Z

1

Try this:

data = fruits.merge(tropical_fruits, on=['fruit1','fruit2'], how='left')

edited Mar 3, 2024 at 0:31

L Tyrone

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answered Mar 2, 2024 at 20:42

Hallvard

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so.n · Accepted Answer · 2024-03-04 08:35:18Z

1

if you want to avoid _x and _y suffix you should determine the columns that you want in merge for each dataframe.

import pandas as pd
fruits = pd.DataFrame({'fruit1':['apple', 'banana', 'cherry'],'fruit2':['d','f','h'],'id':[1,2,3]  })
tropical_fruits = pd.DataFrame({'fruit1':['apple', 'banana', 'mango'],'fruit2':['d','n','h'],'id':[1,2,4]})
result=pd.merge(fruits[['fruit1','fruit2','id']], tropical_fruits[['fruit1','fruit2']],  how='left', left_on=['fruit1','fruit2'],right_on=['fruit1','fruit2'])

answered Mar 4, 2024 at 8:35

so.n

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