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Refactor mean and inferred_freq methods documentation
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pandas/core/indexes/datetimelike.py

Lines changed: 3 additions & 51 deletions
Original file line numberDiff line numberDiff line change
@@ -89,7 +89,7 @@ class DatetimeIndexOpsMixin(NDArrayBackedExtensionIndex, ABC):
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_data: DatetimeArray | TimedeltaArray | PeriodArray
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def mean(self, *, skipna: bool = True, axis: int | None = 0):
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"""
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"""
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Return the mean value of the Array.
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Parameters
@@ -103,25 +103,9 @@ def mean(self, *, skipna: bool = True, axis: int | None = 0):
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-------
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scalar
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Timestamp or Timedelta.
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See Also
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--------
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DatetimeIndex.median : Return the median of the index.
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DatetimeIndex.sum : Sum of the values in the index.
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DatetimeIndex.inferred_freq : Attempt to infer frequency from values.
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Examples
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--------
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>>> import pandas as pd
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>>> idx = pd.date_range("2020-01-01", periods=3)
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>>> idx
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DatetimeIndex(['2020-01-01', '2020-01-02', '2020-01-03'],
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dtype='datetime64[ns]', freq='D')
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>>> idx.mean()
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Timestamp('2020-01-02 00:00:00')
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"""
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return self._data.mean(skipna=skipna, axis=axis)
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@property
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def freq(self) -> BaseOffset | None:
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"""
@@ -165,24 +149,6 @@ def asi8(self) -> npt.NDArray[np.int64]:
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def freqstr(self) -> str:
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"""
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Return the frequency string if it is set, otherwise None.
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Returns
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-------
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str or None
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Frequency string such as 'D', 'H', etc., or None.
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See Also
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--------
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DatetimeIndex.freq : The offset object for the frequency.
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PeriodIndex.freq : Return the frequency object for PeriodIndex.
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DatetimeIndex.inferred_freq : Attempt to infer frequency from values.
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Examples
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--------
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>>> import pandas as pd
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>>> idx = pd.date_range("2020-01-01", periods=3, freq="D")
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>>> idx.freqstr
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'D'
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"""
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from pandas import PeriodIndex
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@@ -617,28 +583,14 @@ def shift(self, periods: int = 1, freq=None) -> Self:
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)
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return type(self)._simple_new(result, name=self.name)
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@cache_readonly
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@cache_readonly
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def inferred_freq(self) -> str | None:
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"""
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Tries to return a string representing a frequency guess generated by infer_freq.
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Returns
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-------
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str or None
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Inferred frequency string (e.g. 'D', 'H') or None if it cannot be inferred.
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See Also
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--------
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DatetimeIndex.freqstr : Readable frequency string.
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DatetimeIndex.freq : The offset object for the frequency.
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pandas.infer_freq : Lower-level frequency inference utility.
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Examples
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--------
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>>> import pandas as pd
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>>> idx = pd.to_datetime(['2020-01-01', '2020-01-02', '2020-01-03'])
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>>> idx.inferred_freq
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'D'
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"""
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return self._data.inferred_freq
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