DOC: Fix docstrings for errors

ci/code_checks.sh

@@ -95,9 +95,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.core.resample.Resampler.std SA01" \
         -i "pandas.core.resample.Resampler.transform PR01,RT03,SA01" \
         -i "pandas.core.resample.Resampler.var SA01" \
-        -i "pandas.errors.NullFrequencyError SA01" \
-        -i "pandas.errors.NumbaUtilError SA01" \
-        -i "pandas.errors.PerformanceWarning SA01" \
         -i "pandas.errors.UndefinedVariableError PR01,SA01" \
         -i "pandas.errors.ValueLabelTypeMismatch SA01" \
         -i "pandas.io.json.build_table_schema PR07,RT03,SA01" \

pandas/errors/__init__.py

@@ -45,6 +45,11 @@ class NullFrequencyError(ValueError):
     Particularly ``DatetimeIndex.shift``, ``TimedeltaIndex.shift``,
     ``PeriodIndex.shift``.
 
+    See Also
+    --------
+    Index.shift : Shift values of Index.
+    Series.shift : Shift values of Series.
+
     Examples
     --------
     >>> df = pd.DatetimeIndex(["2011-01-01 10:00", "2011-01-01"], freq=None)
@@ -58,6 +63,12 @@ class PerformanceWarning(Warning):
     """
     Warning raised when there is a possible performance impact.
 
+    See Also
+    --------
+    DataFrame.set_index : Set the DataFrame index using existing columns.
+    DataFrame.loc : Access a group of rows and columns by label(s) \
+    or a boolean array.
+
     Examples
     --------
     >>> df = pd.DataFrame(
@@ -385,17 +396,24 @@ class NumbaUtilError(Exception):
     """
     Error raised for unsupported Numba engine routines.
 
+    See Also
+    --------
+    DataFrame.groupby : Group DataFrame using a mapper or by a Series of columns.
+    Series.groupby : Group Series using a mapper or by a Series of columns.
+    DataFrame.agg : Aggregate using one or more operations over the specified axis.
+    Series.agg : Aggregate using one or more operations over the specified axis.
+
     Examples
     --------
     >>> df = pd.DataFrame(
     ...     {"key": ["a", "a", "b", "b"], "data": [1, 2, 3, 4]}, columns=["key", "data"]
     ... )
     >>> def incorrect_function(x):
     ...     return sum(x) * 2.7
-    >>> df.groupby("key").agg(incorrect_function, engine="numba")
+    >>> df.("key").agg(incorrect_function, engine="numba")
     Traceback (most recent call last):
     NumbaUtilError: The first 2 arguments to incorrect_function
-    must be ['values', 'index']
+    must be ['values', 'index']groupby
     """