{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.14","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":10338,"databundleVersionId":862042,"sourceType":"competition"}],"dockerImageVersionId":30786,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"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\n# for 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":"2024-10-27T10:24:21.883005Z","iopub.execute_input":"2024-10-27T10:24:21.883452Z","iopub.status.idle":"2024-10-27T10:24:21.890047Z","shell.execute_reply.started":"2024-10-27T10:24:21.883412Z","shell.execute_reply":"2024-10-27T10:24:21.888441Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Маша","metadata":{}},{"cell_type":"code","source":"# EDA","metadata":{"execution":{"iopub.status.busy":"2024-10-27T10:09:27.955437Z","iopub.execute_input":"2024-10-27T10:09:27.955903Z","iopub.status.idle":"2024-10-27T10:09:27.961028Z","shell.execute_reply.started":"2024-10-27T10:09:27.955864Z","shell.execute_reply":"2024-10-27T10:09:27.959833Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Настя","metadata":{}},{"cell_type":"code","source":"# EDA","metadata":{"execution":{"iopub.status.busy":"2024-10-27T10:09:07.187869Z","iopub.execute_input":"2024-10-27T10:09:07.188300Z","iopub.status.idle":"2024-10-27T10:09:07.212598Z","shell.execute_reply.started":"2024-10-27T10:09:07.188252Z","shell.execute_reply":"2024-10-27T10:09:07.211455Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Ваня","metadata":{}},{"cell_type":"code","source":"# EDA\n\n\nlabels = pd.read_csv(\"/kaggle/input/rsna-pneumonia-detection-challenge/stage_2_train_labels.csv\")\nlabels.tail()","metadata":{"execution":{"iopub.status.busy":"2024-10-27T10:11:39.898497Z","iopub.execute_input":"2024-10-27T10:11:39.898951Z","iopub.status.idle":"2024-10-27T10:11:39.963267Z","shell.execute_reply.started":"2024-10-27T10:11:39.898915Z","shell.execute_reply":"2024-10-27T10:11:39.962157Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"class_info = pd.read_csv(\"/kaggle/input/rsna-pneumonia-detection-challenge/stage_2_detailed_class_info.csv\")\nclass_info.tail()","metadata":{"execution":{"iopub.status.busy":"2024-10-27T10:12:29.431585Z","iopub.execute_input":"2024-10-27T10:12:29.432031Z","iopub.status.idle":"2024-10-27T10:12:29.502128Z","shell.execute_reply.started":"2024-10-27T10:12:29.431983Z","shell.execute_reply":"2024-10-27T10:12:29.500828Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}