为什么我会得到这个 python MS sql server 错误？

Question

I keep getting the same error below when trying to write from a pandas data frame to MS sql server. I have triple checked that all my data matches the data types on the table.

Sample Data:

POSTING_DATE	SOURCE	READTYPE	PPTAGID	ETAGID_PLATE	EQUIPID	AGENCY	ENTRY_PLAZA	ENTRY_DATE	EXIT_PLAZA	EXIT_DATE	TOLL_CLASS	MILES	TOLL_AMOUNT	ID
2022-06-06 00:00:00	ELITE	Transponder	777777777	11111111111	5363	KTA	Eastern Entrance	2022-06-04 17:52:39	Southern Entrance	2022-06-04 21:50:25	5	0.00	31.95	111111111111111111111
2022-06-06 00:00:00	EZPass	Transponder	777777777	11111111111	5363	DelDOT	NaN	NaN	D95	2022-06-03 03:08:21	5	0.00	9.00	111111111111111111111
2022-06-06 00:00:00	EZPass	Transponder	777777777	11111111111	5363	NJTP	1	2022-06-03 03:27:38	2	2022-06-03 03:39:56	5	0.00	4.60	111111111111111111111
2022-06-06 00:00:00	ELITE	Transponder	777777777	11111111111	5362	KTA	Wichita: I-135 I-235 47th St	2022-06-04 15:21:21	Southern Entrance	2022-06-04 15:47:57	5	0.00	5.05	111111111111111111111
2022-06-06 00:00:00	ELITE	Transponder	777777777	11111111111	5357	OTA	WR-BGCBN	2022-06-05 02:05:25	WR-STLINE	2022-06-05 02:38:17	5	0.00	9.20	111111111111111111111
2022-06-06 00:00:00	ELITE	Transponder	777777777	11111111111	5355	OTA	HEB-NWCLML	2022-06-03 07:10:36	HEB-NWCLML	2022-06-03 07:10:36	5	0.00	3.95	111111111111111111111

Table Structure:

[PostingDate]  datetime,
[Source]       varchar(50),
[ReadType]     varchar(50),
[PPTagID]      varchar(10),
[ETagID_Plate] varchar(12),
[EquipID]      varchar(4),
[Agency]       varchar(10),
[Entry_Plaza]  varchar(50),
[Entry_Date]   datetime,
[Exit_Plaza]   varchar(50),
[Exit_Date]    datetime,
[Toll_Class]   varchar(5),
[Miles]        numeric(18, 2),
[Toll_Amount]  numeric(18, 2),
[ID]           varchar(50) 

Python Code:

for row in df.itertuples():
    try:
        MsExe.execute("""
            INSERT INTO test_tolls_table_temp (PostingDate, Source, ReadType, PPTagID, ETagID_Plate, EquipID, Agency, Entry_Plaza, Entry_Date, Exit_Plaza, Exit_Date, Toll_Class, Miles, Toll_Amount, ID)
            VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
            """, row[1], row[2], row[3], row[4], row[5], row[6], row[7], row[8], row[9], row[10], row[11], row[12], row[13], row[14], row[15])

except Exception as exception:
    print(exception)
    break

Error:

 ('42000', '[42000] [Microsoft][ODBC SQL Server Driver][SQL Server] The incoming tabular data stream (TDS) remote procedure call (RPC) protocol stream is incorrect. Parameter 9 (""): The supplied value is not a valid instance of data type float. Check the source data for invalid values. An example of an invalid value is data of numeric type with scale greater than precision. (8023) (SQLExecDirectW)')

Answer 1

Neither need to specify each column individually by like row[1] , row[2] ... row[15] , nor a loop

but use directly executemany (which's also more performant for DML operations than execute ) such as

import pyodbc
import pandas as pd

con = pyodbc.connect(
    "DRIVER=ODBC Driver xx for SQL Server;"
    "SERVER=<IP>,<some number>;"
    "DATABASE=DB123;"
    "Trusted_Connection=yes;"
)


data = pd.read_csv(pathToFile,delimiter= ';') # is just a sample delimiter representation, you should replace with yours 
df = data.values.tolist()

MsExe=con.cursor()
try:
    MsExe.fast_executemany = True
    MsExe.executemany("""
                         INSERT INTO test_tolls_table_temp (PostingDate, Source, ReadType, PPTagID, ETagID_Plate, EquipID, Agency, Entry_Plaza, Entry_Date, Exit_Plaza, Exit_Date, Toll_Class, Miles, Toll_Amount, ID)
                         VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
                      """,df)
except Exception as exception:
    print(exception)

MsExe.close()
con.commit()
con.close();