creating a pandas dataframe from a database query that uses bind variables

2024/9/26 0:25:29

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

    import pandas as pdimport pandas.io.sql as psqlimport cx_Oracle as odbconn = odb.connect(_user +'/'+ _pass +'@'+ _dbenv)sqlStr = "SELECT * FROM customers"df = psql.frame_query(sqlStr, conn)

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

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

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)

The following works:

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

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?

Answer

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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