Sum the elements along an axis ignoring NaNs

    Parameters
    ----------
    values : ndarray[dtype]
    axis: int, optional
    skipna : bool, default True
    min_count: int, default 0
    mask : ndarray[bool], optional
        nan-mask if known

    Returns
    -------
    result : dtype

    Examples
    --------
    >>> import pandas.core.nanops as nanops
    >>> s = pd.Series([1, 2, np.nan])
    >>> nanops.nansum(s)
    3.0

def nansum(values, axis=None, skipna=True, min_count=0, mask=None):
    """
    Sum the elements along an axis ignoring NaNs

    Parameters
    ----------
    values : ndarray[dtype]
    axis: int, optional
    skipna : bool, default True
    min_count: int, default 0
    mask : ndarray[bool], optional
        nan-mask if known

    Returns
    -------
    result : dtype

    Examples
    --------
    >>> import pandas.core.nanops as nanops
    >>> s = pd.Series([1, 2, np.nan])
    >>> nanops.nansum(s)
    3.0
    """
    values, mask, dtype, dtype_max, _ = _get_values(values,
                                                    skipna, 0, mask=mask)
    dtype_sum = dtype_max
    if is_float_dtype(dtype):
        dtype_sum = dtype
    elif is_timedelta64_dtype(dtype):
        dtype_sum = np.float64
    the_sum = values.sum(axis, dtype=dtype_sum)
    the_sum = _maybe_null_out(the_sum, axis, mask, min_count=min_count)

    return _wrap_results(the_sum, dtype)