Document constant check in series

Closes pandas-dev#54033

Author: sbrugman

doc/source/user_guide/cookbook.rst

@@ -1488,3 +1488,35 @@ of the data values:
        {"height": [60, 70], "weight": [100, 140, 180], "sex": ["Male", "Female"]}
    )
    df
+
+Constant series
+---------------
+
+To assess if a series has a constant value, we can check if ``series.nunique() == 1``.
+However, a more performant approach, that does not count all unique values first, is:
+
+.. ipython:: python
+
+   v = s.values
+   is_constant = v.shape[0] > 0 and (s[0] == s).all()
+
+This approach assumes that the series does not contain missing values.
+For the case that we would drop NA values, we can simply remove those values first:
+
+.. ipython:: python
+
+   from pandas.core.dtypes.missing import remove_na_arraylike
+
+   v = s.values
+   v = remove_na_arraylike(v)
+   is_constant = v.shape[0] > 0 and (s[0] == s).all()
+
+If missing values are considered distinct from any other value, then one could use:
+
+.. ipython:: python
+
+   v = s.values
+   is_constant = v.shape[0] > 0 and ((s[0] == s).all() or not pd.notna(v).any())
+
+(Note that this example does not disambiguate between `np.nan`, `pd.NA` and `None`)
+