pandas sql commands
SQL_Query = pd.read_sql_query(
'''select
product_name,
product_price_per_unit,
units_ordered,
((units_ordered) * (product_price_per_unit)) AS revenue
from tracking_sales''', conn)pandas sql commands
SQL_Query = pd.read_sql_query(
'''select
product_name,
product_price_per_unit,
units_ordered,
((units_ordered) * (product_price_per_unit)) AS revenue
from tracking_sales''', conn)convert sql query to python pandas
select *
from table1 inner join table on table1.cc = table2.cc and table1.kc = table2.kc and table1.nn = table2.nn
where table1.date <> table2.dateconvert sql query to python pandas
select a.passengerId passA,b.passengerId passB,count(*) numflightsTogether from df a inner join df b on (a.flightid=b.flightid and a.date=b.date ) where a.passengerid != b.passengerid group by a.passengerid,b.passengerid having count(*) >3Copyright © 2021 Codeinu
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