{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"\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","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"train = pd.read_csv('../input/osic-pulmonary-fibrosis-progression/train.csv')\n\nsub1 = pd.read_csv('../input/osic-temp-data/submission.csv')\nsub2 = pd.read_csv('../input/osic-temp-data/submission(1).csv')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"sub1[['Patient','Week']] = sub1.Patient_Week.str.split(\"_\",expand=True)\n\nsub2[['Patient','Week']] = sub1.Patient_Week.str.split(\"_\",expand=True) ","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"train_data_list = []\n\nfor person in train.Patient.unique():\n    person_data = train[train['Patient'] == person]\n    week_list = person_data['Weeks']\n    fvc_list = person_data['FVC']\n    train_data_list.append([week_list,fvc_list])","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"submission_data_list_1 = []\n\nfor person in sub1.Patient.unique():\n    person_data = sub1[sub1['Patient'] == person]\n    week_list = person_data['Week']\n    fvc_list = person_data['FVC']\n    submission_data_list_1.append([week_list,fvc_list])","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"submission_data_list_2 = []\n\nfor person in sub2.Patient.unique():\n    person_data = sub2[sub2['Patient'] == person]\n    week_list = person_data['Week']\n    fvc_list = person_data['FVC']\n    submission_data_list_2.append([week_list,fvc_list])","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Train data Graph Single","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"for week_list,data_list in train_data_list:\n    plt.plot(week_list.to_list(),data_list.to_list())\n    \nplt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Training Data Grouped","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"i = 1\nlines_in_graph = 10\nfor week_list,data_list in train_data_list:\n    i = i+1\n    plt.plot(week_list.to_list(),data_list.to_list())\n    if i%lines_in_graph==0:\n        plt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Submission 1 Data Seperate","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"for week_list,data_list in submission_data_list_1:\n    plt.plot(week_list.to_list(),data_list.to_list())\n    plt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Submission 1 Data Single","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"for week_list,data_list in submission_data_list_1:\n    plt.plot(week_list.to_list(),data_list.to_list())\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Submission 2 data Seperate","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"for week_list,data_list in submission_data_list_2:\n    plt.plot(week_list.to_list(),data_list.to_list())\n    plt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"for week_list,data_list in submission_data_list_2:\n    plt.plot(week_list.to_list(),data_list.to_list())\nplt.show()","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":4}