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DOC: add an example to PeriodIndex.to_timestamp to clarify the behavior in case len(index)<3 #57384

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Feb 15, 2024
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DOC: add an example to PeriodIndex.to_timestamp to clarify the behavior in case len(index)<3 #57384

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e7ff4ca
add an example to PeriodIndex.to_timestamp
natmokval Feb 12, 2024
a2dc46a
correct to_timestamp docs, add an example
natmokval Feb 14, 2024
760d555
correct the wording in to_timestamp docstring
natmokval Feb 15, 2024
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14 changes: 14 additions & 0 deletions pandas/core/arrays/period.py
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Original file line number Diff line number Diff line change
Expand Up @@ -636,6 +636,20 @@ def to_timestamp(self, freq=None, how: str = "start") -> DatetimeArray:
>>> idx.to_timestamp()
DatetimeIndex(['2023-01-01', '2023-02-01', '2023-03-01'],
dtype='datetime64[ns]', freq='MS')

The frequency will not be inferred if the index contains less than
three elements and values of index are not strictly monotonic:
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the way this is phrased it sounds like (pseudocode):

if len(index) < 3 and not index.is_monotonic():
    dont_infer_frequency(...)

Instead, I think it's more like

if len(index) < 3 or not index.is_monotonic():
    dont_infer_frequency(...)

?

How about

        The frequency will not be inferred if the index contains less than
        three elements, or if the values of index are not strictly monotonic:

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thanks, you are right, my wording isn't correct. I changed it as you suggested.


>>> idx = pd.PeriodIndex(["2023-01", "2023-02"], freq="M")
>>> idx.to_timestamp()
DatetimeIndex(['2023-01-01', '2023-02-01'], dtype='datetime64[ns]', freq=None)

>>> idx = pd.PeriodIndex(
... ["2023-01", "2023-02", "2023-02", "2023-03"], freq="2M"
... )
>>> idx.to_timestamp()
DatetimeIndex(['2023-01-01', '2023-02-01', '2023-02-01', '2023-03-01'],
dtype='datetime64[ns]', freq=None)
"""
from pandas.core.arrays import DatetimeArray

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