{"cells":[{"metadata":{},"cell_type":"markdown","source":"Was my LB Probe kernel correct?  \n[LB probe -> weights, N of positives, scoring](https://www.kaggle.com/kambarakun/lb-probe-weights-n-of-positives-scoring/output)"},{"metadata":{"trusted":true},"cell_type":"code","source":"import pandas as pd","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"df_1 = pd.read_csv('../input/rsna2019-csv/stage_1_sample_submission.csv')\ndf_2 = pd.read_csv('../input/rsna2019-csv/stage_2_train.csv')","execution_count":null,"outputs":[]},{"metadata":{"_cell_guid":"","_uuid":"","trusted":true},"cell_type":"code","source":"set_df_1_id = set(df_1['ID'])\nidx         = [True if id_tmp in set_df_1_id else False for id_tmp in df_2['ID']]","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_2[idx]['Label'].values.reshape(-1, 6).sum(axis=0)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"My LB Probe of stage-1 was correct!!\n\n|N of epidural|N of intraparenchymal|N of intraventricular|N of subarachnoid|N of subdural|N of any|\n|-------------|---------------------|---------------------|-----------------|-------------|--------|\n|          384|                 3554|                 2439|             3553|         4670|   10830|"}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":1}