pandas-dev/pandas · error · ValueError

cannot supply both a tz and a dtype with a tz

Error message

cannot supply both a tz and a dtype with a tz

What it means

Raised by _validate_tz_from_dtype when the user supplies both an explicit tz= argument and a dtype that itself carries a tz, and the two disagree. The two tz sources conflict, so pandas refuses to guess. ValueError.

Source

Thrown at pandas/core/arrays/datetimes.py:3046

    Raises
    ------
    ValueError : on tzinfo mismatch
    """
    if dtype is not None:
        if isinstance(dtype, str):
            try:
                dtype = DatetimeTZDtype.construct_from_string(dtype)
            except TypeError:
                # Things like `datetime64[ns]`, which is OK for the
                # constructors, but also nonsense, which should be validated
                # but not by us. We *do* allow non-existent tz errors to
                # go through
                pass
        dtz = getattr(dtype, "tz", None)
        if dtz is not None:
            if tz is not None and not timezones.tz_compare(tz, dtz):
                raise ValueError("cannot supply both a tz and a dtype with a tz")
            if explicit_tz_none:
                raise ValueError("Cannot pass both a timezone-aware dtype and tz=None")
            tz = dtz

        if tz is not None and lib.is_np_dtype(dtype, "M"):
            # We also need to check for the case where the user passed a
            #  tz-naive dtype (i.e. datetime64[ns])
            if tz is not None and not timezones.tz_compare(tz, dtz):
                raise ValueError(
                    "cannot supply both a tz and a "
                    "timezone-naive dtype (i.e. datetime64[ns])"
                )

    return tz


def _infer_tz_from_endpoints(
    start: Timestamp, end: Timestamp, tz: tzinfo | None

View on GitHub (pinned to 71959b8cb9)

Solutions

1. Provide the tz in exactly one place — prefer the dtype string and omit tz=.
2. Or pass a tz-naive dtype plus tz= and let pandas build the aware dtype.
3. Make sure when both are present they reference the same zone.

Example fix

# before
pd.DatetimeIndex(data, dtype='datetime64[ns, UTC]', tz='US/Eastern')
# after
pd.DatetimeIndex(data, dtype='datetime64[ns, UTC]')

def resolve_tz(dtype=None, tz=None):
    dt_tz = getattr(dtype, 'tz', None)
    if dt_tz is not None and tz is not None and str(dt_tz) != str(tz):
        raise ValueError('conflict between dtype tz and tz= argument')
    return tz or dt_tz

When it happens

Trigger: pd.DatetimeIndex(data, dtype='datetime64[ns, UTC]', tz='US/Eastern'); constructing a Series/DatetimeIndex with both a tz-aware dtype string and a tz kwarg pointing at different zones.

Common situations: Building dtype strings dynamically and also passing tz; refactor that left both parameters populated.

Related errors

• Cannot pass both a timezone-aware dtype and tz=None
• cannot supply both a tz and a timezone-naive dtype (i.e. dat
• Cannot compare tz-naive and tz-aware datetime-like objects.
• Cannot compare tz-naive and tz-aware datetime-like objects
• Cannot convert tz-naive timestamps, use tz_localize to local

AI-assisted analysis of pandas-dev/pandas@71959b8cb9 (2026-08-07). Data as JSON: /api/errors/10eeed4c42c7c3d2. Report an issue: GitHub.