{"cells":[{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"9181c8df-7678-6110-eb9f-7b3b6a61b16b"},"outputs":[],"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\nfrom subprocess import check_output\nprint(check_output([\"ls\", \"../input\"]).decode(\"utf8\"))\n\n# Any results you write to the current directory are saved as output."},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"f92eb48f-200f-2f87-af22-325dde6aefa2"},"outputs":[],"source":"train = pd.read_csv('../input/train.csv')\ntrain.shape"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"a014067e-500c-219c-3cc5-19beca0c30b9"},"outputs":[],"source":"train.head()"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"07a18b4d-38d6-b1cf-8686-7d45a71164d6"},"outputs":[],"source":"labels = train['label']\nlen(labels)"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"0f033d5c-30fb-a713-0f25-c6d51e631a63"},"outputs":[],"source":"pixels = train.iloc[:, 1:785]\npixels.shape"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"147fb0d7-822e-c04c-05a7-4e817bf21bd9"},"outputs":[],"source":""}],"metadata":{"_change_revision":0,"_is_fork":false,"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.6.0"}},"nbformat":4,"nbformat_minor":0}