def METHOD_NAME(x: da.Array, data: da.Array) -> da.Array:
    _, ncols = data.shape
    datamask = da.isnan(data)
    xmask = da.isnan(x)[:, 0]
    corrs = []
    for j in range(ncols):
        y = data[:, [j]]
        mask = ~(xmask | datamask[:, j])
        corr = da.from_delayed(kendalltau(x[mask], y[mask]), dtype=float, shape=())
        corrs.append(corr)
    return da.stack(corrs)