Question

我想使用groupby从Pandas DataFrame列中获取在WHERE子句中包含多个参数的SQL查询字符串输出。最好的方法是什么？

import pandas as pd

df = pd.DataFrame({
    'Contact Name':['John Doe','John Doe','Jane Doe','Jim Doe','Jim Doe'],
    'Email Address': ['john.doe@gmail.com','john.doe@gmail.com','jane.doe@gmail.com','jim.doe@gmail.com','jim.doe@gmail.com'],
    'Contract No':['2851','2852','2853','2854','2855'],
})

从上面的示例中，我需要获取3个不同的SQL查询，如下所示：

SELECT * FROM TABLE WHERE [Contract No] IN ('2851', '2852')
SELECT * FROM TABLE WHERE [Contract No] IN ('2853')
SELECT * FROM TABLE WHERE [Contract No] IN ('2854', '2855')

Answer 1

让我们use parametrized sql少给黑客entryway into our databases：

sqls = []
args = []
for key, grp in df.groupby(['Contact Name', 'Email Address']):
    arg = tuple(grp['Contract No'])
    sql = 'SELECT * FROM TABLE WHERE [Contract No] IN ({})'.format(','.join(['%s']*len(arg)))
    sqls.append(sql)
    args.append(arg)

for sql, arg in zip(sqls, args):
    print(sql, arg)
    # SELECT * FROM TABLE WHERE [Contract No] IN (%s) ('2853',)
    # SELECT * FROM TABLE WHERE [Contract No] IN (%s,%s) ('2854', '2855')
    # SELECT * FROM TABLE WHERE [Contract No] IN (%s,%s) ('2851', '2852')

要执行参数化的sql，请使用2-argument form of cursor.execute：

for sql, arg in zip(sqls, args):
    cursor.execute(sql, arg)

Answer 2

找出解决方案。我只需要与groupby一起使用lambda函数。

import pandas as pd

df1 = pd.DataFrame({
    'Contact Name':['John Doe','John Doe','Jane Doe','Jim Doe','Jim Doe'],
    'Email Address':['john.doe@gmail.com','john.doe@gmail.com','jane.doe@gmail.com','jim.doe@gmail.com','jim.doe@gmail.com'],
    'Contract No':['2851','2852','2853','2854','2855'],
})

df2 = df1.groupby(['Contact Name','Email Address'])['Contract No'].apply(lambda x: ','.join('\'' + x + '\'')).reset_index()

for index, row in df2.iterrows():
    print('SELECT * FROM TABLE WHERE [Contract No] IN (' + row['Contract No'] + ')')

Pandas GroupBy和SQL Where子句参数

2 个答案: