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

ci/code_checks.sh

@@ -109,7 +109,6 @@ 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.plotting.andrews_curves RT03,SA01" \
         -i "pandas.plotting.scatter_matrix PR07,SA01" \

pandas/tseries/frequencies.py

@@ -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
@@ -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)