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 index = pd.DatetimeIndex([pd.to_datetime("2035-01-01 01:00:00"), pd.to_datetime("2036-01-01 00:00:00")]) df = pd.DataFrame(index=index) df.loc[:, "110735"] = 0 print(df)

Issue Description

Under certain situations assignment is broken

• Dataframe has a DatetimeIndex as its index.
• You want to assign to an entire column (either with .loc or directly with [ ])
• The column name you want to assign is a string which can be interpreted as a datetime within the range of datetime values in the datetimeindex. In the example above "110735" is interpreted as 2035-11-07.

If these conditions are met, the assignment fails and the column is not populated. Pandas is interpreting the string as a datetime and seems to think you are attempting to access the row "110735".

In recent versions a warning is produced, but the script does not crash. This warning indicates that pandas thinks we have tried to use indexing like frame[string], however we have used frame.loc[:, string] which should not have this issue.
This FutureWarning is not valid as the assignment fails completely and no changes are made to the dataframe.

FutureWarning: Indexing a DataFrame with a datetimelike index using a single string to slice the rows, like frame[string], is deprecated and will be removed in a future version. Use frame.loc[string] instead.
self.obj[key] = value

In recent versions if you run with "df.loc[df.index, "110735"] = 0" you get a crash with this error:

pandas/core/indexing.py:1684: FutureWarning: Indexing a DataFrame with a datetimelike index using a single string to slice the rows, like frame[string], is deprecated and will be removed in a future version. Use frame.loc[string] instead.
self.obj[key] = infer_fill_value(value)
Traceback (most recent call last):
File "/usr/local/lib/python3.8/dist-packages/pandas/core/indexes/base.py", line 3361, in get_loc
return self._engine.get_loc(casted_key)
File "pandas/_libs/index.pyx", line 76, in pandas._libs.index.IndexEngine.get_loc
File "pandas/_libs/index.pyx", line 108, in pandas._libs.index.IndexEngine.get_loc
File "pandas/_libs/hashtable_class_helper.pxi", line 5198, in pandas._libs.hashtable.PyObjectHashTable.get_item
File "pandas/_libs/hashtable_class_helper.pxi", line 5206, in pandas._libs.hashtable.PyObjectHashTable.get_item
KeyError: '110735'

In older pandas versions it crashes with a KeyError when "df.loc[:, "110735"] = 0" is run :

Traceback (most recent call last):
File "base.py", line 2898, in get_loc
return self._engine.get_loc(casted_key)
File "pandas_libs\index.pyx", line 70, in pandas._libs.index.IndexEngine.get_loc
File "pandas_libs\index.pyx", line 101, in pandas._libs.index.IndexEngine.get_loc
File "pandas_libs\hashtable_class_helper.pxi", line 1675, in pandas._libs.hashtable.PyObjectHashTable.get_item
File "pandas_libs\hashtable_class_helper.pxi", line 1683, in pandas._libs.hashtable.PyObjectHashTable.get_item
KeyError: '110735'

Expected Behavior

Expected behaviour is that a column "110735" is populated with 0 in all rows.

Installed Versions

Remote test with a more recent pandas version:

Local test with an older pandas version: