{"cells":[{"metadata":{"trusted":true},"cell_type":"code","source":"import os\nimport pandas as pd\nos.listdir('../input')","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"one = pd.read_csv('../input/champs-blending-tutorial/1.csv')  ## distance\ntwo = pd.read_csv('../input/champs-blending-tutorial/2.csv')  ## LGB + features\nthree = pd.read_csv('../input/champs-blending-tutorial/3.csv') ## MPNN\nfour = pd.read_csv('../input/otherkernelsadded/submission-2.csv')  ## GIBA\nfive = pd.read_csv('../input/otherkernelsadded/submission-giba-1.csv')  ## GIBA+\nsix = pd.read_csv('../input/otherkernelsadded/workingsubmission-test.csv')   ##\nseven = pd.read_csv('../input/otherkernelsadded/LGB_2019-07-18_-1.2243.csv') ## LGB\n\nsubmission = pd.DataFrame()\nsubmission['id'] = one.id\nsubmission['scalar_coupling_constant'] = (0.40*one.scalar_coupling_constant) + \\\n                                        (0.29*two.scalar_coupling_constant) + \\\n                                        (0.19*three.scalar_coupling_constant) + \\\n                                        (0.04*five.scalar_coupling_constant) + \\\n                                        (0.04*six.scalar_coupling_constant) + \\\n                                        (0.04*seven.scalar_coupling_constant)\n\nsubmission.to_csv('my_blend_1.csv', index=False)","execution_count":null,"outputs":[]}],"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":4,"nbformat_minor":1}