def df_drop_nan_rows(df, verbose=False):
    """Remove entries in dataframe where all rows (besides 'time')
    have nan values.
    """

    N_init = df.shape[0]
    colnames = [c for c in df.columns if c not in ['time', 'turbid', 'index']]
    df = df.dropna(axis=0, subset=colnames, how='all')

    if verbose:
        print("Reduced dataframe from %d to %d rows." % (N_init, df.shape[0]))

    return df