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DOC: fix SA01,ES01 for pandas.infer_freq #60441

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Dec 2, 2024
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DOC: fix SA01,ES01 for pandas.infer_freq #60441

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1 change: 0 additions & 1 deletion ci/code_checks.sh
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Original file line number Diff line number Diff line change
Expand Up @@ -114,7 +114,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
-i "pandas.errors.PerformanceWarning SA01" \
-i "pandas.errors.UndefinedVariableError PR01,SA01" \
-i "pandas.errors.ValueLabelTypeMismatch SA01" \
-i "pandas.infer_freq SA01" \
-i "pandas.io.json.build_table_schema PR07,RT03,SA01" \
-i "pandas.io.stata.StataWriter.write_file SA01" \
-i "pandas.plotting.andrews_curves RT03,SA01" \
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12 changes: 12 additions & 0 deletions pandas/tseries/frequencies.py
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Expand Up @@ -89,6 +89,11 @@ def infer_freq(
"""
Infer the most likely frequency given the input index.

This method attempts to deduce the most probable frequency (e.g., 'D' for daily,
'H' for hourly) from a sequence of datetime-like objects. It is particularly useful
when the frequency of a time series is not explicitly set or known but can be
inferred from its values.

Parameters
----------
index : DatetimeIndex, TimedeltaIndex, Series or array-like
Expand All @@ -106,6 +111,13 @@ def infer_freq(
ValueError
If there are fewer than three values.

See Also
--------
date_range : Return a fixed frequency DatetimeIndex.
timedelta_range : Return a fixed frequency TimedeltaIndex with day as the default.
period_range : Return a fixed frequency PeriodIndex.
DatetimeIndex.freq : Return the frequency object if it is set, otherwise None.

Examples
--------
>>> idx = pd.date_range(start="2020/12/01", end="2020/12/30", periods=30)
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