{"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":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2023-03-19T07:11:41.396252Z","iopub.execute_input":"2023-03-19T07:11:41.396666Z","iopub.status.idle":"2023-03-19T07:11:41.407518Z","shell.execute_reply.started":"2023-03-19T07:11:41.396632Z","shell.execute_reply":"2023-03-19T07:11:41.406688Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import numpy as np\nfrom sklearn.metrics import confusion_matrix, cohen_kappa_score\n","metadata":{"execution":{"iopub.status.busy":"2023-03-19T07:11:43.366223Z","iopub.execute_input":"2023-03-19T07:11:43.366666Z","iopub.status.idle":"2023-03-19T07:11:43.371656Z","shell.execute_reply.started":"2023-03-19T07:11:43.366628Z","shell.execute_reply":"2023-03-19T07:11:43.370831Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"label = pd.read_csv(\"/kaggle/input/predict-student-performance-from-game-play/train_labels.csv\")","metadata":{"execution":{"iopub.status.busy":"2023-03-19T07:11:44.507830Z","iopub.execute_input":"2023-03-19T07:11:44.508230Z","iopub.status.idle":"2023-03-19T07:11:44.757209Z","shell.execute_reply.started":"2023-03-19T07:11:44.508192Z","shell.execute_reply":"2023-03-19T07:11:44.756207Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"label[\"user\"] = label[\"session_id\"].apply(lambda x: int(x.split(\"_\")[0]))\nlabel[\"q\"] = label[\"session_id\"].apply(lambda x: x.split(\"_\")[1])","metadata":{"execution":{"iopub.status.busy":"2023-03-19T07:11:48.521027Z","iopub.execute_input":"2023-03-19T07:11:48.522063Z","iopub.status.idle":"2023-03-19T07:11:48.828803Z","shell.execute_reply.started":"2023-03-19T07:11:48.522024Z","shell.execute_reply":"2023-03-19T07:11:48.827662Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"result_dict = {}\nfor q1 in label[\"q\"].unique():\n    for q2 in label[\"q\"].unique():\n        if q1 > q2:\n            A = list(label[label[\"q\"] == q1][\"correct\"])\n            B = list(label[label[\"q\"] == q2][\"correct\"]) \n            result_dict[f\"{q1}_and_{q2}\"] =  cohen_kappa_score(A, B)\n    ","metadata":{"execution":{"iopub.status.busy":"2023-03-19T07:14:47.791956Z","iopub.execute_input":"2023-03-19T07:14:47.792961Z","iopub.status.idle":"2023-03-19T07:14:54.245511Z","shell.execute_reply.started":"2023-03-19T07:14:47.792916Z","shell.execute_reply":"2023-03-19T07:14:54.244490Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sorted(result_dict.items(),key = lambda x:-abs(x[1]))","metadata":{"execution":{"iopub.status.busy":"2023-03-19T07:16:31.703484Z","iopub.execute_input":"2023-03-19T07:16:31.703874Z","iopub.status.idle":"2023-03-19T07:16:31.719358Z","shell.execute_reply.started":"2023-03-19T07:16:31.703839Z","shell.execute_reply":"2023-03-19T07:16:31.718373Z"},"trusted":true},"execution_count":null,"outputs":[]}]}