{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"import numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\nimport os\nprint(os.listdir(\"../input\"))\n\nimport matplotlib.pyplot as plt\nimport seaborn as sns\n\nimport cv2\nimport glob\nfrom zipfile import ZipFile","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_train = pd.read_csv(\"../input/train.csv\")\nprint(\"No of Observation : {}\".format(df_train.shape[0]))\nplt.rcParams[\"figure.figsize\"] = [16,5]\nsns.countplot(df_train[\"diagnosis\"])\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"folders = glob.glob(\"../input/train_images/*\")\nread_images = []        \n#, cv2.IMREAD_GRAYSCALE\nfor image in folders[0:20]:\n    read_images.append(cv2.imread(image,cv2.COLOR_BGR2RGB))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"plt.figure(figsize=(24,24))\nfor index in range(len(read_images[0:16])):\n    diag = folders[index].split('/')[-1].split('.')[0]\n    tp = df_train[df_train['id_code']== diag]['diagnosis']\n    ax = plt.subplot(4,4,index+1)\n    plt.xticks([])\n    plt.yticks([])\n    plt.grid(False)\n    plt.imshow(read_images[index])\n    ax.title.set_text('diagnosis = {}'.format(tp.to_string(index=False)))\nplt.show()","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.6.4","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":1}