pandas 大熊猫到sql server
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pandas to sql server
提问by JOHN
I got following code. The problem is I could read data use panda.read_sql, but I could not use the DataFrame.to_sql() function.
我得到了以下代码。问题是我可以使用 panda.read_sql 读取数据，但我无法使用 DataFrame.to_sql() 函数。
%matplotlib inline
import pandas as pd
import pyodbc
from datetime import datetime
import numpy as np
import matplotlib.pyplot as plt
pd.set_option('display.max_rows', 50)
pd.set_option('display.max_columns', 15)
pd.set_option('precision', 4)
conn = pyodbc.connect(r"Driver={SQL Server};Server=dev;Database=test1")
data = pd.read_sql_query(
"""
SELECT *
FROM sys.tables
"""
, con = conn)
print data
data.to_sql('test', con = conn)
the error is the following:
错误如下：
Execution failed on sql 'SELECT name FROM sqlite_master WHERE type='table' AND name=?;': ('42S02', "[42S02] [Microsoft][ODBC SQL Server Driver][SQL Server]Invalid object name 'sqlite_master'. (208) (SQLExecDirectW); [42000] [Microsoft][ODBC SQL Server Driver][SQL Server]Statement(s) could not be prepared. (8180)")
sql 'SELECT name FROM sqlite_master WHERE type='table' AND name=?;' 执行失败：('42S02', "[42S02] [Microsoft][ODBC SQL Server Driver][SQL Server]无效的对象名称'sqlite_master' . (208) (SQLExecDirectW); [42000] [Microsoft][ODBC SQL Server 驱动程序][SQL Server]无法准备语句。(8180)")
Is there a way to get around?
有没有办法绕过？
回答by Parfait
Consider creating a sqlalchemy MSSQL engineand use that in pandas to_sql()con argument:
考虑创建一个 sqlalchemy MSSQL 引擎并在 pandas to_sql()con 参数中使用它：
import sqlalchemy
...
engine = sqlalchemy.create_engine(
"mssql+pyodbc://user:pwd@server/database",
echo=False)
data.to_sql('test', con=engine, if_exists='replace')
