pandas-dev/pandas · error · TypeError

Cannot convert {self.dtype} to {dtype}; subtypes are incompa

Error message

Cannot convert {self.dtype} to {dtype}; subtypes are incompatible

What it means

Raised as a TypeError by `IntervalArray.astype` when the current subtype is a float dtype and the target IntervalDtype's subtype is an i8-convertible datetime-like (e.g., `datetime64[ns]` or `timedelta64[ns]`). Casting float NaN positions into i8 datetimes would silently corrupt NaT, so it is disallowed on the array even though `Index.astype` permits it. Fires at pandas/core/arrays/interval.py:947.

Source

Thrown at pandas/core/arrays/interval.py:947

            ExtensionArray or NumPy ndarray with 'dtype' for its dtype.
        """
        from pandas import Index

        if dtype is not None:
            dtype = pandas_dtype(dtype)

        if isinstance(dtype, IntervalDtype):
            if dtype == self.dtype:
                return self.copy() if copy else self

            if is_float_dtype(self.dtype.subtype) and needs_i8_conversion(
                dtype.subtype
            ):
                # This is allowed on the Index.astype but we disallow it here
                msg = (
                    f"Cannot convert {self.dtype} to {dtype}; subtypes are incompatible"
                )
                raise TypeError(msg)

            # need to cast to different subtype
            try:
                # We need to use Index rules for astype to prevent casting
                #  np.nan entries to int subtypes
                new_left = Index(self._left, copy=False).astype(dtype.subtype)
                new_right = Index(self._right, copy=False).astype(dtype.subtype)
            except IntCastingNaNError:
                # e.g test_subtype_integer
                raise
            except (TypeError, ValueError) as err:
                # e.g. test_subtype_integer_errors f8->u8 can be lossy
                #  and raises ValueError
                msg = (
                    f"Cannot convert {self.dtype} to {dtype}; subtypes are incompatible"
                )
                raise TypeError(msg) from err
            return self._shallow_copy(new_left, new_right)

View on GitHub (pinned to 71959b8cb9)

Solutions

1. Cast the underlying Index to datetime first: `left = pd.to_datetime(pd.Index(ia.left)); right = pd.to_datetime(pd.Index(ia.right))` then rebuild.
2. Convert epoch floats via `pd.to_datetime(ia.left, unit='s')`.
3. Build a fresh `pd.IntervalIndex.from_arrays(left_ts, right_ts, closed=ia.closed)`.

Example fix

// before
ia.astype('interval[datetime64[ns]]')
// after
left = pd.to_datetime(pd.Index(ia.left), unit='s')
right = pd.to_datetime(pd.Index(ia.right), unit='s')
pd.IntervalIndex.from_arrays(left, right, closed=ia.closed)

import pandas as pd

def interval_to_datetime(ia):
    left = pd.to_datetime(pd.Index(ia.left))
    right = pd.to_datetime(pd.Index(ia.right))
    return pd.IntervalIndex.from_arrays(left, right, closed=ia.closed)

import pandas as pd
from pandas.core.dtypes.common import is_float_dtype

def is_float_subtype(ia) -> bool:
    return is_float_dtype(ia.dtype.subtype)

try:
    out = ia.astype('interval[datetime64[ns]]')
except TypeError as e:
    if "subtypes are incompatible" in str(e):
        left = pd.to_datetime(pd.Index(ia.left))
        right = pd.to_datetime(pd.Index(ia.right))
        out = pd.IntervalIndex.from_arrays(left, right, closed=ia.closed)
    else:
        raise

When it happens

Trigger: `ia.astype('interval[datetime64[ns]]')` where `ia.dtype.subtype` is float64.

Common situations: Trying to reinterpret numeric interval bounds (e.g., epoch floats) as datetime intervals in one step.

Related errors

• Cannot cast {type(self).__name__} to dtype {dtype}
• Converting from {self.dtype} to {dtype} is not supported. Do
• Cannot cast {type(self).__name__} to dtype {dtype}
• value should be a '{self._scalar_type.__name__}', 'NaT', or
• {dtype=} does not have a resolution.

AI-assisted analysis of pandas-dev/pandas@71959b8cb9 (2026-08-07). Data as JSON: /api/errors/0b1e16469b67165f. Report an issue: GitHub.