{"cells":[{"metadata":{},"cell_type":"markdown","source":"Thanks, guys!\n\nhttps://www.kaggle.com/surajpm/steal-like-an-atom <br>\nhttps://www.kaggle.com/roydatascience/steal-like-an-electron <br>\nhttps://www.kaggle.com/lpachuong/statstack <br>\n\nUPDATE: new dataset from https://www.kaggle.com/marcelotamashiro/lgb-public-kernels-plus-more-features. Thnks, bro!\n"},{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"#loading packages\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\nimport statistics\nimport os\nprint(os.listdir(\"../input\"))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#reading all submission files\n#sub1 = pd.read_csv('../input/giba-r-data-table-simple-features-1-17-lb/submission-giba-1.csv')\n#sub2 = pd.read_csv('../input/keras-neural-net-for-champs/workingsubmission-test.csv')\n#sub3 = pd.read_csv('../input/no-memory-reduction-workflow-for-each-type-lb-1-28/LGB_2019-07-18_-1.2243.csv')\nsub4 = pd.read_csv('../input/from-sub-lgb/sub_lgb_model_individual.csv')\n#sub5 = pd.read_csv('../input/stacking-try/stack_median.csv')\nsub6 = pd.read_csv('../input/stealing/submission.csv')\nsub7 = pd.read_csv('../input/stealing/submission1.csv')\n\n#print( sub1['scalar_coupling_constant'].describe() )\n#print( sub2['scalar_coupling_constant'].describe() )\n#print( sub3['scalar_coupling_constant'].describe() )\nprint( sub4['scalar_coupling_constant'].describe() )\n#print( sub5['scalar_coupling_constant'].describe() )\nprint( sub6['scalar_coupling_constant'].describe() )\nprint( sub7['scalar_coupling_constant'].describe() )\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Random weights to each submission by trying and experimenting\nsub6['scalar_coupling_constant'] =  0.34*sub6['scalar_coupling_constant'] + 0.33*sub7['scalar_coupling_constant'] + 0.33*sub4['scalar_coupling_constant']\nsub6.to_csv('submission.csv', index=False )","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#plotting histogram\nsub6['scalar_coupling_constant'].plot('hist', bins=100)","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.6.4","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":1}