{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.14","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"nvidiaTeslaT4","dataSources":[{"sourceId":81933,"databundleVersionId":9643020,"sourceType":"competition"},{"sourceId":9645646,"sourceType":"datasetVersion","datasetId":5890662}],"dockerImageVersionId":30787,"isInternetEnabled":false,"language":"python","sourceType":"notebook","isGpuEnabled":true}},"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","trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import pandas as pd\n!python /kaggle/input/py-file/child_mind/ca.py\n!python /kaggle/input/py-file/child_mind/g.py\n!python /kaggle/input/py-file/child_mind/l.py\n!python /kaggle/input/py-file/child_mind/r.py\n!python /kaggle/input/py-file/child_mind/x.py","metadata":{"execution":{"iopub.status.busy":"2024-10-17T01:53:08.152119Z","iopub.execute_input":"2024-10-17T01:53:08.152921Z","iopub.status.idle":"2024-10-17T02:02:18.150978Z","shell.execute_reply.started":"2024-10-17T01:53:08.152876Z","shell.execute_reply":"2024-10-17T02:02:18.149972Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sub1=pd.read_csv('cat.csv')\nsub2=pd.read_csv('gbm.csv')\nsub3=pd.read_csv('lgb.csv')\nsub4=pd.read_csv('random.csv')\nsub5=pd.read_csv('xgb_.csv')\nsample=pd.read_csv('/kaggle/input/child-mind-institute-problematic-internet-use/sample_submission.csv')","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sub1 = sub1.sort_values(by='id').reset_index(drop=True)\nsub2 = sub2.sort_values(by='id').reset_index(drop=True)\nsub3 = sub3.sort_values(by='id').reset_index(drop=True)\nsub4 = sub4.sort_values(by='id').reset_index(drop=True)\nsub5 = sub5.sort_values(by='id').reset_index(drop=True)","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sample['sii'] = np.round(sub2['sii'] *0.15 +  0.7* sub3['sii']+  0.15* sub5['sii'])\nsample['sii'] = sample['sii'].astype(int)\nsample.to_csv('submission.csv', index=False)","metadata":{},"execution_count":null,"outputs":[]}]}