Function comparison_op

pandas/core/ops/array_ops.py:294–361

Evaluate a comparison operation `=`, `!=`, `>=`, `>`, `<=`, or `<`. Note: the caller is responsible for ensuring that numpy warnings are suppressed (with np.errstate(all="ignore")) if needed. Parameters ---------- left : np.ndarray or ExtensionArray right : object

(left: ArrayLike, right: Any, op)

def comparison_op(left: ArrayLike, right: Any, op) -> ArrayLike:
    """
    Evaluate a comparison operation `=`, `!=`, `>=`, `>`, `<=`, or `<`.

    Note: the caller is responsible for ensuring that numpy warnings are
    suppressed (with np.errstate(all="ignore")) if needed.

    Parameters
    ----------
    left : np.ndarray or ExtensionArray
    right : object
        Cannot be a DataFrame, Series, or Index.
    op : {operator.eq, operator.ne, operator.gt, operator.ge, operator.lt, operator.le}

    Returns
    -------
    ndarray or ExtensionArray
    """
    # NB: We assume extract_array has already been called on left and right
    lvalues = ensure_wrapped_if_datetimelike(left)
    rvalues = ensure_wrapped_if_datetimelike(right)

    rvalues = lib.item_from_zerodim(rvalues)

    # Special handling needed if rvalues is a zerodim np.ndarray subclass, see GH#63205
    rvalues_is_zerodim: bool = getattr(rvalues, "ndim", None) == 0

    if isinstance(rvalues, list):
        # We don't catch tuple here bc we may be comparing e.g. MultiIndex
        #  to a tuple that represents a single entry, see test_compare_tuple_strs
        rvalues = sanitize_array(rvalues, None)
    rvalues = ensure_wrapped_if_datetimelike(rvalues)

    if isinstance(rvalues, (np.ndarray, ABCExtensionArray)) and not rvalues_is_zerodim:
        # TODO: make this treatment consistent across ops and classes.
        #  We are not catching all listlikes here (e.g. frozenset, tuple)
        #  The ambiguous case is object-dtype.  See GH#27803
        if len(lvalues) != len(rvalues):
            raise ValueError(
                "Lengths must match to compare", lvalues.shape, rvalues.shape
            )

    if should_extension_dispatch(lvalues, rvalues) or (
        (isinstance(rvalues, (Timedelta, BaseOffset, Timestamp)) or right is NaT)
        and lvalues.dtype != object
    ):
        # Call the method on lvalues
        res_values = op(lvalues, rvalues)

    # TODO: but not pd.NA?
    elif (is_scalar(rvalues) or rvalues_is_zerodim) and isna(rvalues):
        # numpy does not like comparisons vs None
        if op is operator.ne:
            res_values = np.ones(lvalues.shape, dtype=bool)
        else:
            res_values = np.zeros(lvalues.shape, dtype=bool)

    elif is_numeric_v_string_like(lvalues, rvalues):