def _iterate_columns(X, columns=None):
    if columns is None:
        columns = range(X.shape[1])

    if issparse(X):
        for i in columns:
            x = np.zeros(X.shape[0])
            start_ptr, end_ptr = X.indptr[i], X.indptr[i + 1]
            x[X.indices[start_ptr:end_ptr]] = X.data[start_ptr:end_ptr]
            yield x
    else:
        for i in columns:
            yield X[:, i]
check the tmux_id (backup name) for show info (-l)
dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/feature_selection/mutual_info_.py/_iterate_columns--crossover with--dataset/ETHPy150Open sk1418/retmux/tmuxbk/controller.py/tmux_id_4_show