{"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 in \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 \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory\n\nimport os\nprint(os.listdir(\"../input\"))\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"import cv2\n\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nplt.style.use('seaborn')\nsns.set(font_scale=1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_train = pd.read_csv(\"../input/train.csv\")\nlabels = pd.read_csv(\"../input/labels.csv\")\nsample_sub = pd.read_csv(\"../input/sample_submission.csv\")","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_train.head()","execution_count":49,"outputs":[{"output_type":"execute_result","execution_count":49,"data":{"text/plain":" id attribute_ids\n0 1000483014d91860 147 616 813\n1 1000fe2e667721fe 51 616 734 813\n2 1001614cb89646ee 776\n3 10041eb49b297c08 51 671 698 813 1092\n4 100501c227f8beea 13 404 492 903 1093","text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
idattribute_ids
01000483014d91860147 616 813
11000fe2e667721fe51 616 734 813
21001614cb89646ee776
310041eb49b297c0851 671 698 813 1092
4100501c227f8beea13 404 492 903 1093
\n
"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"labels.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"sample_sub.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_train.shape, labels.shape, sample_sub.shape","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_train.groupby(\"attribute_ids\").size().sort_values()[::-1][:10]","execution_count":77,"outputs":[{"output_type":"execute_result","execution_count":77,"data":{"text/plain":"attribute_ids\n13 405 896 1092 1158\n813 896 586\n194 1034 489\n13 552 482\n121 1059 465\n121 433 425\n13 626 365\n79 1059 352\n13 813 896 339\n121 1039 332\ndtype: int64"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_train.groupby(\"attribute_ids\").size().sort_values()[::-1][:10].hist(bins=10)","execution_count":80,"outputs":[{"output_type":"execute_result","execution_count":80,"data":{"text/plain":""},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"print(\"train size is {}\".format(len(os.listdir(\"../input/train/\"))))\nprint(\"test size is {}\".format(len(os.listdir(\"../input/test/\"))))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"c = 1\nplt.figure(figsize=[16,16])\nfor img_name in os.listdir(\"../input/train/\")[:16]:\n img = cv2.imread(\"../input/train/{}\".format(img_name))[...,[2,1,0]]\n plt.subplot(4,4,c)\n plt.imshow(img)\n plt.title(\"train image {}\".format(c))\n c += 1\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"c = 1\nplt.figure(figsize=[16,16])\nfor img_name in os.listdir(\"../input/test/\")[:16]:\n img = cv2.imread(\"../input/test/{}\".format(img_name))[...,[2,1,0]]\n plt.subplot(4,4,c)\n plt.imshow(img)\n plt.title(\"test image {}\".format(c))\n c += 1\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"**Well, let's find out which score sample_submission has**"},{"metadata":{"trusted":true},"cell_type":"code","source":"sample_sub.to_csv(\"submission.csv\", index=False)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","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}