{"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_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"import jo_wilder\nenv = jo_wilder.make_env()","metadata":{"execution":{"iopub.status.busy":"2023-05-08T06:58:39.332572Z","iopub.execute_input":"2023-05-08T06:58:39.332945Z","iopub.status.idle":"2023-05-08T06:58:39.381289Z","shell.execute_reply.started":"2023-05-08T06:58:39.332900Z","shell.execute_reply":"2023-05-08T06:58:39.380157Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"iter_test = env.iter_test()","metadata":{"execution":{"iopub.status.busy":"2023-05-08T06:58:49.540236Z","iopub.execute_input":"2023-05-08T06:58:49.540640Z","iopub.status.idle":"2023-05-08T06:58:49.546093Z","shell.execute_reply.started":"2023-05-08T06:58:49.540605Z","shell.execute_reply":"2023-05-08T06:58:49.545007Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"from random import random\nimport pandas as pd\n\nprobs = [0.7240003395874013,\n 0.9787757874182867,\n 0.9321674165888445,\n 0.7993038458273198,\n 0.5463961287036251,\n 0.7720519568724,\n 0.7292639443076662,\n 0.6143136089651074,\n 0.7354614143815265,\n 0.5003820358264708,\n 0.6441973002801596,\n 0.857458188301214,\n 0.27048136514135324,\n 0.7100772561337975,\n 0.482978181509466,\n 0.7378385261906784,\n 0.6852873758383564,\n 0.9505900331097716]\n\nfor (test, sample_submission) in iter_test:\n    \n    test_df = test\n    d = []\n\n    for sesh in test_df['session_id'].unique():\n        for i in range(1,19):\n            if not (f'{sesh}_q{i}' in sample_submission['session_id'].values):\n                continue\n            d.append(\n                {\n                    \"session_id\": f'{sesh}_q{i}',\n                    \"correct\": 1 if probs[i-1] > .6375 else 0\n                }        \n            )\n\n\n    predict = pd.DataFrame(d)\n    env.predict(predict)","metadata":{"execution":{"iopub.status.busy":"2023-05-04T03:47:47.053701Z","iopub.execute_input":"2023-05-04T03:47:47.054848Z","iopub.status.idle":"2023-05-04T03:47:47.196351Z","shell.execute_reply.started":"2023-05-04T03:47:47.054798Z","shell.execute_reply":"2023-05-04T03:47:47.194910Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"!head submission.csv","metadata":{"execution":{"iopub.status.busy":"2023-04-26T19:09:03.956254Z","iopub.execute_input":"2023-04-26T19:09:03.956728Z","iopub.status.idle":"2023-04-26T19:09:05.063075Z","shell.execute_reply.started":"2023-04-26T19:09:03.956689Z","shell.execute_reply":"2023-04-26T19:09:05.060547Z"},"trusted":true},"execution_count":null,"outputs":[]}]}