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我有一个复杂的SQL Server查询，我需要从python执行。从Python复杂的SQL Server查询
SQL查询看起来像：
SELECT *
FROM(
SELECT DATEADD(HOUR, CONVERT(INT, SUBSTRING(hour_id, 2, 2)), CAST(FECHA as DATETIME)) as 'Time_', value
FROM
(
SELECT * FROM [MyTable]
) as sel
UNPIVOT(value for hour_id in (H01, H02, H03, H04, H05, H06, H07, H08, H09, H10, H11, H12, H13, H14, H15, H16, H17, H18, H19, H20, H21, H22, H23, H24)) as unpvte
) as Q1;
我创建运行查询和转结局大熊猫功能：
import pandas as pd
import numpy as np
import datetime
import pypyodbc
def execute_sql_command(database_name, server_name, user, password, SQLCommand, index_col=0):
"""
Executed a query in an SQL Server database and returns a Pandas DataFrame
:param database_name: Name of the Database
:param SQLCommand: SQL command with no comments
:param index_col: Index of the column
:return: Pandas DataFrame
"""
connection_string = 'DRIVER={SQL Server};Database=' + database_name \
+ ';SERVER=' + server_name \
+ ';UID=' + user \
+ ';PWD=' + password
connection = pypyodbc.connect(connection_string)
cursor = connection.cursor()
data = list()
idx = list()
cursor.execute(SQLCommand)
hdr = [tuple[0] for tuple in cursor.description]
hdr.pop(index_col)
results = cursor.fetchone()
if results is not None:
results = list(results)
while results:
idx.append(results[index_col]) # add the index
results.pop(index_col) # remove the index from the row (we already accounted for it)
data.append(results) #
results = cursor.fetchone()
if results is not None:
results = list(results)
connection.close()
data = np.array(data)
df = pd.DataFrame(data=data, columns=hdr, index=idx)
return df
我收到此错误：
pypyodbc.ProgrammingError: ('42000', "[42000] [Microsoft][ODBC SQL Server Driver][SQL Server]Incorrect syntax close to 'L'.")
我的代码适用于简单的查询，如SELECT * FROM Table，但无法处理这个复杂的查询。该查询在Microsoft SQL Server Management Studio中可用。