{"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)\nimport matplotlib.pyplot as plt\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\n\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":"2023-03-22T08:56:25.586732Z","iopub.execute_input":"2023-03-22T08:56:25.587197Z","iopub.status.idle":"2023-03-22T08:56:25.612718Z","shell.execute_reply.started":"2023-03-22T08:56:25.587096Z","shell.execute_reply":"2023-03-22T08:56:25.611740Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"example1 = pd.read_csv('/kaggle/input/tlvmc-parkinsons-freezing-gait-prediction/train/tdcsfog/003f117e14.csv')\nexample1.describe()","metadata":{"execution":{"iopub.status.busy":"2023-03-22T09:12:28.038512Z","iopub.execute_input":"2023-03-22T09:12:28.039828Z","iopub.status.idle":"2023-03-22T09:12:28.079400Z","shell.execute_reply.started":"2023-03-22T09:12:28.039762Z","shell.execute_reply":"2023-03-22T09:12:28.078144Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"plt.figure(figsize=(15,4))\nplt.xlabel('Time')\n\nfor i in range(len(example1['Time'])):\n    plt.plot(example1.iloc[i:i+2, 0], example1.iloc[i:i+2,1], \n             lw = 0.5,\n             color = 'blue' if example1.iloc[i,5] == 0 else 'red')\n    plt.plot(example1.iloc[i:i+2, 0], example1.iloc[i:i+2,2], \n             lw = 0.5,\n             color = 'green' if example1.iloc[i,5] == 0 else 'red')\n    plt.plot(example1.iloc[i:i+2, 0], example1.iloc[i:i+2,3], \n             lw = 0.5,\n             color = 'orange' if example1.iloc[i,5] == 0 else 'red')\n\nplt.legend(['AccV', 'AccML', 'AccAP'])\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2023-03-22T09:29:25.457381Z","iopub.execute_input":"2023-03-22T09:29:25.457834Z","iopub.status.idle":"2023-03-22T09:29:51.033674Z","shell.execute_reply.started":"2023-03-22T09:29:25.457793Z","shell.execute_reply":"2023-03-22T09:29:51.032532Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}