{"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 pandas as pd\nsubs = ['../input/dtabp-1st-place-solution/submission.csv','../input/2nd-place-solution/submission_lgbm_13.6469.csv','../input/bid-price-predicition-4th-place-submission/submission.csv']\nssub = pd.read_csv('../input/digital-turbine-auction-bid-price-prediction/sample_submission.csv')\ndel ssub['winBid']\ndid = 'deviceId'\nfor i in range(len(subs)):\n    ssub = ssub.merge(pd.read_csv(subs[i],names = [did,f'winBid{i}']), on = did)\n    \nssub['winBid'] = ssub.filter(like ='winBid', axis = 1).median(axis = 1)\nssub[[did,'winBid']].to_csv('submission.csv', index = False)\nssub.head(30)","metadata":{"execution":{"iopub.status.busy":"2022-10-09T18:04:20.954786Z","iopub.execute_input":"2022-10-09T18:04:20.955220Z","iopub.status.idle":"2022-10-09T18:04:21.442388Z","shell.execute_reply.started":"2022-10-09T18:04:20.955181Z","shell.execute_reply":"2022-10-09T18:04:21.440156Z"},"trusted":true},"execution_count":null,"outputs":[]}]}