{"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":{"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","trusted":true},"cell_type":"code","source":"import pandas as pd\nimport pyarrow.parquet as pq\nimport os","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"fdf5ce5a61d782c04ce0556be06a8d047cb522c1"},"cell_type":"code","source":"import pandas as pd\nimport pyarrow.parquet as pq\nimport os","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"31eacc38a037498d7f17f2b0c5110b750fccd1a2"},"cell_type":"code","source":"os.listdir('../input')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"3d043200a35b9fc821b79dda95ccb144447c111a"},"cell_type":"code","source":"train = pq.read_pandas('../input/train.parquet').to_pandas()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"974d98b8d980c4afe93a6ddebb0b60179a142bd0"},"cell_type":"code","source":"train.info()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"611825012af59e9c335f9c1d55e46b16b0b77499"},"cell_type":"code","source":"train.columns[:5]","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"4714773aa83c08f8ce58ed99ec37b567278cae12"},"cell_type":"code","source":"subset_train = pq.read_pandas('../input/train.parquet', columns=[str(i) for i in range(5)]).to_pandas()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"1c5c63563e73d2690954374379b61e501c4d6f81"},"cell_type":"code","source":"subset_train.info()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"a84d7b3bf873711adb4416c82ffa43331134df30"},"cell_type":"code","source":"subset_train.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"d41c9fe1984530205f277588b7999b482720786e"},"cell_type":"code","source":"","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.6.6","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":1}