BUG: FutureWarning: Inferring datetime64[ns] when using pd.pivot_table(..., margins=True) and datetime64[ns] · Issue #48683 · pandas-dev/pandas (original) (raw)

Pandas version checks

• I have checked that this issue has not already been reported.
• I have confirmed this bug exists on the latest version of pandas.
• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd import numpy as np

df = pd.DataFrame( { "state": ["CA", "WA", "CO", "AZ"] * 3, "office_id": list(range(1, 7)) * 2, "date": [pd.Timestamp.now().date() - pd.Timedelta(days=d) for d in range(6)] * 2, "sales": [np.random.randint(100_000, 999_999) for _ in range(12)] } ).astype( { "sales": np.float64, "date": pd.api.types.pandas_dtype("datetime64[ns]") } )

df.pivot_table(index=["office_id", "date"], columns="state", margins=True, aggfunc="sum")

Issue Description

Following on from this issue, when the .dtype of a column in the aggregation is datetime64[ns] a warning is emitted. The warning is not emitted when using the non-Pandas native dtype.

Expected Behavior

import pandas as pd import numpy as np

df = pd.DataFrame( { "state": ["CA", "WA", "CO", "AZ"] * 3, "office_id": list(range(1, 7)) * 2, "date": [pd.Timestamp.now().date() - pd.Timedelta(days=d) for d in range(6)] * 2, "sales": [np.random.randint(100_000, 999_999) for _ in range(12)] } ).astype( { "sales": np.float64, "date": pd.api.types.pandas_dtype("O") # works, no warning } )

df.pivot_table(index=["office_id", "date"], columns="state", margins=True, aggfunc="sum")

Installed Versions

INSTALLED VERSIONS

commit : 87cfe4e
python : 3.10.4.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19044
machine : AMD64
processor : Intel64 Family 6 Model 165 Stepping 3, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United Kingdom.1252

pandas : 1.5.0
numpy : 1.23.1
pytz : 2022.1
dateutil : 2.8.2
setuptools : 63.4.1
pip : 22.1.2
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.3
IPython : 8.4.0
pandas_datareader: None
bs4 : 4.11.1
bottleneck : None
brotli :
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.5.2
numba : None
numexpr : None
odfpy : None
openpyxl : 3.0.10
pandas_gbq : None
pyarrow : 9.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.9.1
snappy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : None
tzdata : None