pandas-dev/pandas · error · ValueError

items in new_categories are not the same as in old categorie

Error message

items in new_categories are not the same as in old categories

What it means

Raised by reorder_categories when the supplied new_categories differ in length or in members from the current categories. reorder_categories only permutes existing categories; it cannot add, drop, or rename them. The check uses both length equality and difference() to catch any deviation.

Source

Thrown at pandas/core/arrays/categorical.py:1362

        3   a
        dtype: category
        Categories (3, str): ['c' < 'b' < 'a']

        For :class:`pandas.CategoricalIndex`:

        >>> ci = pd.CategoricalIndex(["a", "b", "c", "a"])
        >>> ci
        CategoricalIndex(['a', 'b', 'c', 'a'], categories=['a', 'b', 'c'],
                         ordered=False, dtype='category')
        >>> ci.reorder_categories(["c", "b", "a"], ordered=True)
        CategoricalIndex(['a', 'b', 'c', 'a'], categories=['c', 'b', 'a'],
                         ordered=True, dtype='category')
        """
        if (
            len(self.categories) != len(new_categories)
            or not self.categories.difference(new_categories).empty
        ):
            raise ValueError(
                "items in new_categories are not the same as in old categories"
            )
        return self.set_categories(new_categories, ordered=ordered)

    def add_categories(self, new_categories) -> Self:
        """
        Add new categories.

        `new_categories` will be included at the last/highest place in the
        categories and will be unused directly after this call.

        Parameters
        ----------
        new_categories : category or list-like of category
            The new categories to be included.

        Returns
        -------

View on GitHub (pinned to 71959b8cb9)

Solutions

1. Pass exactly the current categories in the new order: `cat.reorder_categories(cat.categories[::-1])`.
2. To rename use `rename_categories(...)`; to change membership use `set_categories(...)`.
3. Verify `set(new_categories) == set(cat.categories)` before calling reorder_categories.

Example fix

# before
cat = pd.Categorical(['a','b','c'], categories=['a','b','c'])
cat.reorder_categories(['c','b','a','d'])
# after
cat = pd.Categorical(['a','b','c'], categories=['a','b','c'])
cat.reorder_categories(['c','b','a'])

def safe_reorder(cat, new_categories):
    if set(new_categories) != set(cat.categories) or len(new_categories) != len(cat.categories):
        raise ValueError("new_categories must be a permutation of current categories")
    return cat.reorder_categories(new_categories)

def is_permutation_of_categories(cat, new_categories) -> bool:
    return set(new_categories) == set(cat.categories) and len(new_categories) == len(cat.categories)

try:
    cat = cat.reorder_categories(new_cats)
except ValueError as e:
    if 'not the same as in old categories' in str(e):
        cat = cat.set_categories(new_cats)
    else:
        raise

When it happens

Trigger: `cat.reorder_categories(['b','a','d'])` where 'd' is not an existing category, or where one is missing, or where extra items are included.

Common situations: Confusing reorder with rename or set_categories; passing a reordered list that was built from a superset (e.g. all unique values rather than current categories).

Related errors

• Lengths must match.
• Cannot convert float NaN to integer
• Cannot cast {self.categories.dtype} dtype to {dtype}
• The categories must be provided in 'categories' or 'dtype'.
• new categories need to have the same number of items as the

AI-assisted analysis of pandas-dev/pandas@71959b8cb9 (2026-08-07). Data as JSON: /api/errors/5f84a4b62f5cebc3. Report an issue: GitHub.