{"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 all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### Description\n\nThis notebooks runs the public [utility script](https://www.kaggle.com/xhlulu/tf-qa-jsonl-to-dataframe) to convert original dataset to DataFrame and saves it as an output. The output was used to create a new [simplified verision of the dataset](https://www.kaggle.com/feanorpk/tf-20-qa-simplified-dataframe)."},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"# Load data and convert to DataFrame\n\nfrom tf_qa_jsonl_to_dataframe import jsonl_to_df\n\ntf_qa_input_folder = '/kaggle/input/tensorflow2-question-answering/'\ntrain = jsonl_to_df(tf_qa_input_folder + 'simplified-nq-train.jsonl', truncate=True)\ntest = jsonl_to_df(tf_qa_input_folder + 'simplified-nq-test.jsonl', truncate=True, load_annotations=False)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### Save as output\nThis output was also saved as a [dataset](https://www.kaggle.com/feanorpk/tf-20-qa-simplified-dataframe)"},{"metadata":{"trusted":true},"cell_type":"code","source":"train.to_csv('train.csv')\ntest.to_csv('test.csv')","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":1}