{"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\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\n\nimport os\n","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"trainfile = '../input/digit-recognizer/train.csv'\ntraindata = pd.read_csv(trainfile).to_numpy()\ntraindata","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"import matplotlib.pyplot as plt\nfrom sklearn.tree import DecisionTreeClassifier","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"X = traindata[:,1:]\ny = traindata[:,0]\nclassifier = DecisionTreeClassifier()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"classifier.fit(X,y)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"testfile = '../input/digit-recognizer/test.csv'\ntestdata = pd.read_csv(testfile).to_numpy()\ntestdata","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#printing any random data\n\nptd = testdata[0,:]\nptd.shape = (28,28)\nplt.imshow(255-ptd,cmap ='gray')\nprint(classifier.predict([testdata[0]]))\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#preparation for the submission\nres = classifier.predict(testdata)\ndf =pd.DataFrame(res)\ndf = df.rename(columns={0:'#label'})\ndf['ImageId'] = [i+1 for i in range(len(df)) ]\ndf.set_index('ImageId',inplace=True)\ndf\ndf.to_csv('submission.csv')","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}