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    "info": {
        "author": "Martin Marenz",
        "author_email": "martin.marenz@gmail.com",
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        "description": "# DataFrameLabeler\nA small ipywidget tool for labeling data frames inside jupyter.\n\n# Installation\n\nCurrently, the only way to use the DataFrameLabeler is to clone this repositroy.\n\n# Why?\n\nThis small tool was inspired by the fast.ai image cleaner widget https://docs.fast.ai/widgets.image_cleaner.html .\nHowever, I needed a tool for tabular data.\n\n# How to use?\n\n```\n# imports\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nfrom DataFrameLabeler import DataFrameLabeler\n\n# If you have a pandas data frame where you want to assign each row eihter 'SUCCESS' or 'FAILURE'.\n# like the following one.\nlength = 100\ncols = ['A', 'B', 'C', 'D', 'E']\ndf = pd.DataFrame(np.random.rand(length, len(cols)), columns=cols)\n\n# First you need a function responsible to print a single row.\ndef plotter(idx, row):\n    fig = plt.figure()\n    plt.plot([i for i in row[cols]])\n    # plot should not be shown when called.\n    plt.close(fig)\n    return fig\n\n# Afterwards, just construct a DataFrameLabeler object.\n# If `target_col` exists in the data frame, its content will be used as preselection.\nlbl = DataFrameLabeler(df,\n                       labels=['FAILURE', 'SUCCESS'], # choices for the labels\n                       plotter=plotter,               # function which plots each row\n                       target_col='class_name',       # column name where the labels will be stored\n                       width=3,                       # number of figures in each row\n                       height=2                       # number of rows shown at once\n                       )\n```\n![DataFrameLabeler](images/screenshot_lbl.png)\n```\n# To obtain the newly labeled data frame call lbl.get_labeled_data()\n```\n![Result](images/screenshot_res.png)\n\n## TODO:\n* rework how user defined plotter works, atm its horrifying, especially when\n  using matplotlib\n* proper styling of buttons\n* allow groupby argument\n* allow multi selection\n* add automatic saving of intermediate result to csv or pickle file\n* rethink interface\n* add more unit tests\n* Documentation\n\n\n",
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        "license": "MIT",
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        "name": "DataFrameLabeler",
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        "summary": "An ipywidget helper class to manually label rows in pandas data frames.",
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