BUG: pandas.api.types.is_datetime64_any_dtype returns True for 'M' str

[ScottWilliamAnderson]

Pandas version checks

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Reproducible Example

import pandas
pandas.api.types.is_datetime64_any_dtype('M')  # True

Issue Description

The string 'M' cannot be converted to a datetime using pandas.to_datetime(). It raises the error

Given date string M not likely a datetime present at position 0

I'm unsure what 'M' is supposed to represent? 'Y', 'D' all return False, so I don't think it's strftime strings, perhaps there's another significance I'm missing?

Expected Behavior

I think the 'M' char on its own, should return False

Installed Versions

INSTALLED VERSIONS ------------------ commit : 0f43794 python : 3.11.7.final.0 python-bits : 64 OS : Windows OS-release : 10 Version : 10.0.26100 machine : AMD64 processor : Intel64 Family 6 Model 186 Stepping 3, GenuineIntel byteorder : little LC_ALL : None LANG : en_US.UTF-8 LOCALE : English_United Kingdom.1252

pandas : 2.0.3
numpy : 1.26.4
pytz : 2024.1
dateutil : 2.9.0.post0
setuptools : 68.2.2
pip : 23.3.1
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.4
IPython : 8.26.0
pandas_datareader: None
bs4 : 4.12.3
bottleneck : None
brotli : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
snappy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2024.1
qtpy : None
pyqt5 : None

[asishm]

The docs for the method lists:

Check whether the provided array or dtype is of the datetime64 dtype

When you're passing "M", it assumes that it's a dtype getting passed and not an array. You can validate this by checking pandas.api.types.pandas_dtype("M") which returns dtype('<M8') which is indeed a datetime type.

As far as why M returns datetime and others don't, it derives from numpy . See the Array-protocol type strings section at https://numpy.org/doc/2.1/reference/arrays.dtypes.html#arrays-dtypes-constructing

[QuentinFuxa]

Technical Root Cause

The issue originates from the following line in the Pandas source code (core/dtypes/common.py, line 1640):

np.dtype(dtype)

Here’s the behavior observed with NumPy:

• np.dtype('Y') raises a TypeError: data type 'Y' not understood (expected behavior for invalid input).
• However, np.dtype('M') unexpectedly returns dtype('<M8'), which indicates that 'M' is interpreted as a valid data type (datetime64[ns]). This result is incorrect and likely unintended.

This invalid interpretation propagates through the logic, leading to the erroneous True result from is_datetime64_any_dtype.

EDIT: That's an expected behavior as mentioned by @asishm

[rhshadrach]

Thanks for the report. Agreed @asishm - closing.