ENH: arithmetic between DatetimeArray and list

[cmp0xff]

Feature Type

• Adding new functionality to pandas

• Changing existing functionality in pandas

• Removing existing functionality in pandas

Problem Description

I wish Pandas could implement arithmetic operations for DatetimeArrays and Python native lists.

Feature Description

I wish the following code could run.

from datetime import datetime
import pandas as pd

arr = pd.to_datetime(["2020-01-01", "2020-01-02"]).array
assert isinstance(arr, pd.arrays.DatetimeArray)

arr - [datetime(2019, 12, 31), datetime(2020, 1, 1)]  # TypeError: unsupported operand type(s) for -: 'DatetimeArray' and 'list'

Alternative Solutions

from datetime import datetime
import pandas as pd

arr = pd.to_datetime(["2020-01-01", "2020-01-02"]).array
assert isinstance(arr, pd.arrays.DatetimeArray)

arr - pd.to_datetime([datetime(2019, 12, 31), datetime(2020, 1, 1)]).array

Additional Context

No response

[cmp0xff]

Following this comment, The following code snippet runs fine:

from datetime import datetime
import pandas as pd

arr = pd.to_datetime(["2020-01-01", "2020-01-02"]).array
assert isinstance(arr, pd.arrays.DatetimeArray)

pd.Series(arr).sub([datetime(2019, 12, 31), datetime(2020, 1, 1)])

[jbrockmendel]

Not supporting this is an intentional decision. We do all wrapping-lists-in-arrays at a higher level before getting to the DTA method.

[cmp0xff]

Hi @jbrockmendel , thank you for the quick reply. I am not an expert in Pandas internals, but the following code works, which might be related:

import pandas as pd

pd.Series([1]).array - [1]  # no error at run time

[Dr-Irv]

Also, pandas is inconsistent because you can subtract a single datetime but not a list of datetime. You can also subtract a DatetimeIndex and a Series.

from datetime import datetime
import pandas as pd

arr = pd.to_datetime(["2020-01-01", "2020-01-02"]).array
assert isinstance(arr, pd.arrays.DatetimeArray)

arr - datetime(2019, 12, 31)  # This works

[jbrockmendel]

Scalars are supported intentionally.

[Dr-Irv]

Scalars are supported intentionally.

Sure, but I think it's inconsistent that we support the operation on a scalar, but not on a list of scalars, but we do support if it is a DatetimeIndex or a Series with datetimes or a numpy array.

Why differentiate the list case?

[jbrockmendel]

Because doing the wrapping-in-an-array and length-checks in every single EA subclass would be a hassle, duplicative, a perf penalty etc. We do that upfront at the beginning of the Index/Series/DataFrame method, and support only scalars and right-length-ArrayLike at the EA level

[Dr-Irv]

We also have this kind of inconsistency:

left = pd.Series([pd.Timestamp(2025, 8, 20)])
s = [datetime(2025, 8, 20)]
left - s   # fails
left.sub(s)   # works

So why should the operator fail, but the sub() method work?

[jbrockmendel]

id expect both Series operations to work