{"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\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","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"import pandas as pd \nimport matplotlib.pyplot as plt \nimport seaborn as sns \n\nimport tifffile as tiff\nimport os\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## CSV file exploration\n`train.csv `contains the unique IDs for each image, as well as an RLE-encoded representation of the mask for the objects in the image. See the evaluation tab for details of the RLE encoding scheme."},{"metadata":{"trusted":true},"cell_type":"code","source":"train = pd.read_csv('/kaggle/input/hubmap-kidney-segmentation/train.csv')\ntrain.head()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"`HuBMAP-20-dataset_information.csv` this csv file contains all the information about the images and dataset, Let us see some here  "},{"metadata":{"trusted":true},"cell_type":"code","source":"data_info = pd.read_csv('/kaggle/input/hubmap-kidney-segmentation/HuBMAP-20-dataset_information.csv')\ndata_info.head()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## EDA "},{"metadata":{"trusted":true},"cell_type":"code","source":"sns.countplot(data_info['race'])\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"sns.countplot(data_info['laterality'])\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"sns.countplot(data_info['ethnicity'])\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"sns.distplot(data_info['age'])\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"sns.distplot(data_info['weight_kilograms'])\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"sns.distplot(data_info['height_centimeters'])\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"sns.distplot(data_info['bmi_kg/m^2'])\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":""},{"metadata":{},"cell_type":"markdown","source":"## correlation matrix"},{"metadata":{"trusted":true},"cell_type":"code","source":"data_info.corr()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"img = tiff.imread('../input/hubmap-kidney-segmentation/train/aaa6a05cc.tiff')\nimg_array = np.array(img)\nplt.imshow(img) ","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# To be cont... "},{"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}