从使用绑定变量的数据库查询中创建 pandas 数据框 [英] creating a pandas dataframe from a database query that uses bind variables

问题描述

我正在使用Oracle数据库.我可以做的很多:

I'm working with an Oracle database. I can do this much:

    import pandas as pd
    import pandas.io.sql as psql
    import cx_Oracle as odb
    conn = odb.connect(_user +'/'+ _pass +'@'+ _dbenv)

    sqlStr = "SELECT * FROM customers"
    df = psql.frame_query(sqlStr, conn)

但是我不知道如何处理绑定变量，就像这样:

But I don't know how to handle bind variables, like so:

    sqlStr = """SELECT * FROM customers 
                WHERE id BETWEEN :v1 AND :v2
             """

我尝试了以下变体形式:

I've tried these variations:

   params  = (1234, 5678)
   params2 = {"v1":1234, "v2":5678}

   df = psql.frame_query((sqlStr,params), conn)
   df = psql.frame_query((sqlStr,params2), conn)
   df = psql.frame_query(sqlStr,params, conn)
   df = psql.frame_query(sqlStr,params2, conn)

以下作品:

   curs = conn.cursor()
   curs.execute(sqlStr, params)
   df = pd.DataFrame(curs.fetchall())
   df.columns = [rec[0] for rec in curs.description]

但是这个解决方案只是...优雅.如果可以的话，我希望不创建光标对象就这样做.有没有办法只用熊猫来做整个事情?

but this solution is just...inellegant. If I can, I'd like to do this without creating the cursor object. Is there a way to do the whole thing using just pandas?

推荐答案

尝试使用 pandas.io.sql.read_sql_query .我使用的是熊猫版本0.20.1，我使用了它，结果如下:

Try using pandas.io.sql.read_sql_query. I used pandas version 0.20.1, I used it, it worked out:

import pandas as pd
import pandas.io.sql as psql
import cx_Oracle as odb
conn = odb.connect(_user +'/'+ _pass +'@'+ _dbenv)

sqlStr = """SELECT * FROM customers 
            WHERE id BETWEEN :v1 AND :v2
"""
pars = {"v1":1234, "v2":5678}
df = psql.frame_query(sqlStr, conn, params=pars)

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