{"cells":[{"metadata":{},"cell_type":"markdown","source":"# A late night ensemble of the best public kernels\n\n* from here: https://www.kaggle.com/hmendonca/4-ashrae-blended , & various public submissions (without leaks). Thnks!\n"},{"metadata":{"trusted":true},"cell_type":"code","source":"import os\nos.listdir('../input/')","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"import numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\nimport os\nimport matplotlib\nimport matplotlib.pyplot as plt\nfrom pandas.plotting import register_matplotlib_converters\nregister_matplotlib_converters()\n\nsub = None\nfor dirname, _, filenames in os.walk('/kaggle/input/ultimaincercare/'):\n    for filename in filenames:\n        filename = os.path.join(dirname, filename)\n        print(filename)\n        if sub is None:\n            sub = pd.read_csv(filename)\n        else:\n            sub.meter_reading += pd.read_csv(filename, usecols=['meter_reading']).meter_reading\n    sub.meter_reading = sub.meter_reading.clip(lower=0.0) / len(filenames)\n\nsub.describe()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"sub.to_csv(f'submission-final-1.csv', index=False, float_format='%g')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from IPython.display import FileLink\nFileLink('submission-final-1.csv')","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}