TYP: expand acceptable types for pd.to_datetime() #46273
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This reverts commit 84b119f.
twoertwein
reviewed
Mar 8, 2022
jbrockmendel
reviewed
Mar 9, 2022
pandas/core/tools/datetimes.py
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| @@ -663,7 +668,7 @@ def to_datetime( | |||
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| @overload | |||
| def to_datetime( | |||
| arg: list | tuple | np.ndarray, | |||
| arg: list | tuple | np.ndarray | Index | ExtensionArray, | |||
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No, can't use Sequence, because a string is a sequence, and that has to match the scalar type above this.
Keeping unchanged.
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Could replace np.ndarray | ExtensionArray with ArrayLike.
about Sequence and str: Does to_datetime require certain list/tuple elements? I'm sure that str isn't part of Sequence[datetime.time]
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to_datetime can take mixed lists/tuples of different kinds of scalars (datetimes, ints, floats, strings at a minimum), and I'm a bit hesitant to figure them all out to avoid making this too narrow. So I'm leaving this as list | tuple for now.
jbrockmendel
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Mar 9, 2022
twoertwein
reviewed
Mar 10, 2022
twoertwein
reviewed
Mar 10, 2022
twoertwein
approved these changes
Mar 10, 2022
|
thanks @Dr-Irv |
yehoshuadimarsky
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Jul 13, 2022
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We document that
pd.to_datetime()can accept aDataFrameor "dict-like" as an argument, but the overloads did not specify that. This PR adds that.In addition, there was no overload for
IndexorExtensionArrayas an input type that converts toDatetimeIndexAlso, changed the overload for
pd.to_datetime()on a scalar to only returnTimestampto make user code easier to write. E.g.,with the current version where
pd.to_datetime()can returnTimestamp | NaTType, users would have to do acast