{"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":"# 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\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 read-only \"../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# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2022-06-07T07:29:12.55955Z","iopub.execute_input":"2022-06-07T07:29:12.560802Z","iopub.status.idle":"2022-06-07T07:29:12.571497Z","shell.execute_reply.started":"2022-06-07T07:29:12.56072Z","shell.execute_reply":"2022-06-07T07:29:12.570674Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"data = pd.read_csv('/kaggle/input/challenge-datascience-wind-turbine-cs/training_set.csv')","metadata":{"execution":{"iopub.status.busy":"2022-06-07T07:29:13.072426Z","iopub.execute_input":"2022-06-07T07:29:13.073394Z","iopub.status.idle":"2022-06-07T07:29:19.735664Z","shell.execute_reply.started":"2022-06-07T07:29:13.073337Z","shell.execute_reply":"2022-06-07T07:29:19.734382Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"data['MAC_CODE'].value_counts()","metadata":{"execution":{"iopub.status.busy":"2022-06-07T07:29:19.737821Z","iopub.execute_input":"2022-06-07T07:29:19.73825Z","iopub.status.idle":"2022-06-07T07:29:19.776868Z","shell.execute_reply.started":"2022-06-07T07:29:19.738216Z","shell.execute_reply":"2022-06-07T07:29:19.77531Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"dummies = pd.get_dummies(data['MAC_CODE'], drop_first=True)\ndummies","metadata":{"execution":{"iopub.status.busy":"2022-06-07T07:30:58.727926Z","iopub.execute_input":"2022-06-07T07:30:58.728448Z","iopub.status.idle":"2022-06-07T07:30:58.778941Z","shell.execute_reply.started":"2022-06-07T07:30:58.728411Z","shell.execute_reply":"2022-06-07T07:30:58.777945Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"data = data.drop('MAC_CODE', axis=1)","metadata":{"execution":{"iopub.status.busy":"2022-06-07T07:31:11.842404Z","iopub.execute_input":"2022-06-07T07:31:11.842914Z","iopub.status.idle":"2022-06-07T07:31:12.025718Z","shell.execute_reply.started":"2022-06-07T07:31:11.842874Z","shell.execute_reply":"2022-06-07T07:31:12.024749Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"new_data = pd.concat([data, dummies], axis=1)","metadata":{"execution":{"iopub.status.busy":"2022-06-07T07:31:17.055966Z","iopub.execute_input":"2022-06-07T07:31:17.057019Z","iopub.status.idle":"2022-06-07T07:31:17.251414Z","shell.execute_reply.started":"2022-06-07T07:31:17.056959Z","shell.execute_reply":"2022-06-07T07:31:17.250442Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"new_data","metadata":{"execution":{"iopub.status.busy":"2022-06-07T07:31:17.635497Z","iopub.execute_input":"2022-06-07T07:31:17.636416Z","iopub.status.idle":"2022-06-07T07:31:17.741028Z","shell.execute_reply.started":"2022-06-07T07:31:17.636358Z","shell.execute_reply":"2022-06-07T07:31:17.739784Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}