pandas-dev/pandas · error · IndexError

Indexing with a float is no longer supported. Manually conve

Error message

Indexing with a float is no longer supported. Manually convert to an integer key instead.

What it means

Raised by cast_scalar_indexer (pandas/core/common.py:181) when a scalar float that is a whole number (e.g. 3.0) is used as an index key. Historically pandas allowed 3.0 to be coerced to 3, which hid indexing bugs and was inconsistent with Python's strict int/float distinction; since the deprecation finalized (GH#34193) float keys are rejected.

Source

Thrown at pandas/core/common.py:181

    return False


def cast_scalar_indexer(val: Any) -> Any:
    """
    Disallow indexing with a float key, even if that key is a round number.

    Parameters
    ----------
    val : scalar

    Returns
    -------
    outval : scalar
    """
    # assumes lib.is_scalar(val)
    if lib.is_float(val) and val.is_integer():
        raise IndexError(
            # GH#34193
            "Indexing with a float is no longer supported. Manually convert "
            "to an integer key instead."
        )
    return val


def not_none(*args: object) -> Generator[object]:
    """
    Returns a generator consisting of the arguments that are not None.
    """
    return (arg for arg in args if arg is not None)


def any_none(*args: object) -> bool:
    """
    Returns a boolean indicating if any argument is None.
    """

View on GitHub (pinned to 71959b8cb9)

Solutions

1. Convert the key to int explicitly: `s[int(3.0)]` or `s[int(key)]`.
2. Fix the arithmetic producing the float: use integer division `//` or `math.ceil`/`floor`.
3. If the index genuinely holds float labels, index with the exact float that is NOT a whole number, or cast the index to int/str.

Example fix

# before
key = n / step      # float
s[key]

# after
key = n // step     # int
s[key]

def as_int_key(key):
    if isinstance(key, float) and key.is_integer():
        return int(key)
    return key

s[as_int_key(key)]

def is_safe_indexer(key) -> bool:
    import numbers
    if isinstance(key, float):
        return not key.is_integer()
    return True

try:
    val = s[key]
except IndexError as e:
    if 'float' in str(e):
        val = s[int(key)]
    else:
        raise

When it happens

Trigger: `s[3.0]`, `df.loc[3.0]`, `df.iloc[3.0]`, or `df[3.0]` where the float is a round integer. Also triggered when a key comes from division (`i / 1`) or numpy float scalars (np.float64(2.0)).

Common situations: Keys produced by arithmetic that yields float (e.g. `len//n` vs `len/n`), JSON/config values parsed as float, numpy float64 scalars from reductions, or code migrated from older pandas that silently coerced.

Related errors

• only integers, slices (`:`), ellipsis (`...`), numpy.newaxis
• key must be an int or slice, got {type(key).__name__}
• name_or_index must be an int, str, bytes, pyarrow.compute.Ex
• Only integers, slices and integer or boolean arrays are vali
• only integers, slices (`:`), ellipsis (`...`), numpy.newaxis

AI-assisted analysis of pandas-dev/pandas@71959b8cb9 (2026-08-07). Data as JSON: /api/errors/21ac28d2a9593c94. Report an issue: GitHub.