32234b97cd894b0849f5d151601ea4051cd1b123,pynets/core/utils.py,,collect_pandas_df_make,#Any#Any#Any#Any#,912

Before Change

    if len(net_mets_csv_list) > 1:
        print("%s%s%s" % ("\n\nList of result files to concatenate:\n", str(net_mets_csv_list), "\n\n"))
        subject_path = op.dirname(op.dirname(net_mets_csv_list[0]))
        name_of_network_pickle = "%s%s" % ("net_mets_", net_mets_csv_list[0].split("_0.")[0].split("net_mets_")[1])
        net_mets_csv_list.sort()

        models = []
        for file_ in net_mets_csv_list:

After Change

                                                   np.array(df_summary_nonan["thr"]).astype("float64"))
            meta[thr_set]["auc_dataframe"] = df_summary_auc

            auc_outfile = auc_dir + list(set([re.sub(r"thr\-\d+\.*\d+", "", i).replace("neat", "auc") for i in models_grouped[thr_set]]))[0]
            df.to_csv(auc_outfile, index=False)

        try:

Instances