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[X] I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import math
import uuid
import pandas
import sqlalchemy.engine
input = {
1: {('A', 'X'): math.nan, ('A', 'Y'): math.nan, ('B', 'X'): math.nan, ('B', 'Y'): math.nan},
2: {('A', 'X'): math.nan, ('A', 'Y'): math.nan, ('B', 'X'): math.nan, ('B', 'Y'): math.nan},
3: {('A', 'X'): math.nan, ('A', 'Y'): math.nan, ('B', 'X'): math.nan, ('B', 'Y'): math.nan},
4: {('A', 'X'): math.nan, ('A', 'Y'): math.nan, ('B', 'X'): math.nan, ('B', 'Y'): math.nan},
5: {('A', 'X'): math.nan, ('A', 'Y'): math.nan, ('B', 'X'): math.nan, ('B', 'Y'): math.nan},
}
df = pandas.DataFrame.from_dict(input, "index")
conn_url = sqlalchemy.engine.URL.create("mssql+pyodbc", query={"odbc_connect": "DRIVER={ODBC Driver 18 for SQL Server};SERVER=.;Trusted_Connection=yes;TrustServerCertificate=yes"})
engine = sqlalchemy.create_engine(conn_url, echo=True)
with engine.connect() as conn:
with conn.begin():
df.to_sql(f"not_set_{str(uuid.uuid4())}", conn, index=True)
conn.rollback()
Issue Description
When calling pandas.DataFrame.to_sql with index set to True, it will create the column for the index but never populates it with data, so it's always null
Below is the output from sql alchemy
2024-06-26 14:54:31,050 INFO sqlalchemy.engine.Engine SELECT CAST(SERVERPROPERTY('ProductVersion') AS VARCHAR)
2024-06-26 14:54:31,051 INFO sqlalchemy.engine.Engine [raw sql] ()
2024-06-26 14:54:31,052 INFO sqlalchemy.engine.Engine SELECT schema_name()
2024-06-26 14:54:31,052 INFO sqlalchemy.engine.Engine [generated in 0.00015s] ()
2024-06-26 14:54:31,052 INFO sqlalchemy.engine.Engine SELECT CAST('test max support' AS NVARCHAR(max))
2024-06-26 14:54:31,053 INFO sqlalchemy.engine.Engine [generated in 0.00013s] ()
2024-06-26 14:54:31,053 INFO sqlalchemy.engine.Engine SELECT 1 FROM fn_listextendedproperty(default, default, default, default, default, default, default)
2024-06-26 14:54:31,053 INFO sqlalchemy.engine.Engine [generated in 0.00011s] ()
2024-06-26 14:54:31,054 INFO sqlalchemy.engine.Engine BEGIN (implicit)
2024-06-26 14:54:31,065 INFO sqlalchemy.engine.Engine SELECT [INFORMATION_SCHEMA].[TABLES].[TABLE_NAME]
FROM [INFORMATION_SCHEMA].[TABLES]
WHERE ([INFORMATION_SCHEMA].[TABLES].[TABLE_TYPE] = CAST(? AS NVARCHAR(max)) OR [INFORMATION_SCHEMA].[TABLES].[TABLE_TYPE] = CAST(? AS NVARCHAR(max))) AND [INFORMATION_SCHEMA].[TABLES].[TABLE_NAME] = CAST(? AS NVARCHAR(max)) AND [INFORMATION_SCHEMA].[TABLES].[TABLE_SCHEMA] = CAST(? AS NVARCHAR(max))
2024-06-26 14:54:31,065 INFO sqlalchemy.engine.Engine [generated in 0.00037s] ('BASE TABLE', 'VIEW', 'not_set_125fd112-f19f-44ad-9c49-82be65893ed2', 'dbo')
2024-06-26 14:54:31,067 INFO sqlalchemy.engine.Engine
CREATE TABLE [not_set_125fd112-f19f-44ad-9c49-82be65893ed2] (
[('A', 'X')] FLOAT(53) NULL,
[('A', 'Y')] FLOAT(53) NULL,
[('B', 'X')] FLOAT(53) NULL,
[('B', 'Y')] FLOAT(53) NULL
)
2024-06-26 14:54:31,067 INFO sqlalchemy.engine.Engine [no key 0.00017s] ()
2024-06-26 14:54:31,071 INFO sqlalchemy.engine.Engine INSERT INTO [not_set_125fd112-f19f-44ad-9c49-82be65893ed2] ([('A', 'X')], [('A', 'Y')], [('B', 'X')], [('B', 'Y')]) VALUES (?, ?, ?, ?), (?, ?, ?, ?), (?, ?, ?, ?), (?, ?, ?, ?), (?, ?, ?, ?)
2024-06-26 14:54:31,071 INFO sqlalchemy.engine.Engine [generated in 0.00016s (insertmanyvalues) 1/1 (unordered)] (None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None)
2024-06-26 14:54:31,073 INFO sqlalchemy.engine.Engine ROLLBACK
Expected Behavior
The index column should be populated with data
Installed Versions
import pandas as pd
pd.show_versions()
INSTALLED VERSIONS
------------------
commit : d9cdd2ee5a58015ef6f4d15c7226110c9aab8140
python : 3.12.1.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19044
machine : AMD64
processor : Intel64 Family 6 Model 165 Stepping 2, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252
pandas : 2.2.2
numpy : 1.26.4
pytz : 2024.1
dateutil : 2.9.0.post0
setuptools : 70.1.0
pip : 24.1
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : 3.2.0
lxml.etree : 5.2.2
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.1.4
IPython : None
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.3
bottleneck : None
dataframe-api-compat : None
fastparquet : 2024.5.0
fsspec : 2024.6.0
gcsfs : None
matplotlib : 3.8.4
numba : None
numexpr : None
odfpy : None
openpyxl : 3.1.3
pandas_gbq : None
pyarrow : 16.1.0
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : 1.11.4
sqlalchemy : 2.0.30
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2024.1
qtpy : None
pyqt5 : None
Comment From: Siddharth-Latthe-07
@hb2638 The root cause is that the index column is not correctly specified in the SQL table creation and data insertion process. Theto_sql method needs to include the index in the INSERT statement and ensure it is populated with the correct values.
You can try by ensuring that the to_sql method includes the index column in the SQL table creation and data insertion process.
import math
import uuid
import pandas as pd
import sqlalchemy.engine
input_data = {
1: {('A', 'X'): math.nan, ('A', 'Y'): math.nan, ('B', 'X'): math.nan, ('B', 'Y'): math.nan},
2: {('A', 'X'): math.nan, ('A', 'Y'): math.nan, ('B', 'X'): math.nan, ('B', 'Y'): math.nan},
3: {('A', 'X'): math.nan, ('A', 'Y'): math.nan, ('B', 'X'): math.nan, ('B', 'Y'): math.nan},
4: {('A', 'X'): math.nan, ('A', 'Y'): math.nan, ('B', 'X'): math.nan, ('B', 'Y'): math.nan},
5: {('A', 'X'): math.nan, ('A', 'Y'): math.nan, ('B', 'X'): math.nan, ('B', 'Y'): math.nan},
}
df = pd.DataFrame.from_dict(input_data, "index")
df.index.name = 'index' # Ensure the index has a name
conn_url = sqlalchemy.engine.URL.create("mssql+pyodbc", query={"odbc_connect": "DRIVER={ODBC Driver 18 for SQL Server};SERVER=.;Trusted_Connection=yes;TrustServerCertificate=yes"})
engine = sqlalchemy.create_engine(conn_url, echo=True)
with engine.connect() as conn:
with conn.begin():
df.to_sql(f"not_set_{str(uuid.uuid4())}", conn, index=True)
conn.rollback()
plz let me know, if the above handling works Thanks