{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"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 in \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 \"../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# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"#Understanding marginal emission factor\n#Average emissions refers to the amount of emissions generated over a given time, divided by the amount of energy produced in that time.\n#So for specific source, according to different types of primary_fuel calculate emission_factor \n#total_emission_factor = amount of emission generation over a given time/ amount of energy produced in that time \n\n\ndf = pd.read_csv('/kaggle/input/ds4g-environmental-insights-explorer/eie_data/gppd/gppd_120_pr.csv')\ndf.column = ['capacity_mw', 'estimated_generation_gwh', 'source', 'primary_fuel']\ndf1 = df[df.column]\nprint(df1)\n\ndf1_source = df1.source.unique()\ndf1 = df1.values.tolist()\n\n\ndef avg_emission_factor(df1, a=0, b=0, c=0, d=0):\n    for i in range(len(df1_source)):\n        for j in range(len(df1)):\n            if df1[j][3] == df1_source[i]:\n                a += int(df1[j][0])        # emission_generated_per_source\n                b += int(df1[j][1])        # energy_produced_per_source\n        c += a                             # total_emission_generated\n        d += b                             # total_energy_produced\n    avg_emission_factor = c/d\n    return avg_emission_factor\n    \navg_marginal_emission = avg_emission_factor\nprint(avg_marginal_emission)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","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}