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        "author": "Ajay Maity",
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        "description": "# EDA and Visualization Library\n[![Build Status](https://travis-ci.com/ajaymaity/eda-viz.svg?branch=master)](https://travis-ci.com/ajaymaity/eda-viz)\n[![license](https://img.shields.io/github/license/mashape/apistatus.svg?maxAge=2592000)](https://github.com/ajaymaity/eda-viz/blob/master/LICENSE)\n\nLight-weight Python EDA and Visualization Library for Data Scientists.\n\nThe `eda_viz` module is a light-weight library that will make your data \nexploration and visualization tasks lot simpler.\n\n## Installation\n\nYou can install `eda-viz` from PyPI:\n\n```buildoutcfg\npip install eda-viz\n```\n\nThe library is only tested in Python 3.6.5, and on Mac OS v10.13.6.\n\n## How to use\n\nLet's create a sample dataframe:\n\n```buildoutcfg\nimport pandas as pd\ndf = pd.DataFrame({\n    'categories': ['A', 'B', 'A', 'C', 'D', 'B', 'A'],\n    'numbers': [1, 2, 1, 3, 4, 2, 1]\n})\n```\n\n### Column Distribution\n\n```buildoutcfg\nfrom eda_viz.viz import column_distribution\ncolumn_distribution(df['categories'])\n```\n\n![Column Distribution](https://raw.githubusercontent.com/ajaymaity/eda-viz/master/images/example-column-distribution.png)\n\n### Histogram\n\n```buildoutcfg\nfrom eda_viz.viz import histogram\nhistogram(df['numbers'])\n```\n\n![Histogram](https://raw.githubusercontent.com/ajaymaity/eda-viz/master/images/example-histogram.png)\n\n### Bar Plot\n\n```buildoutcfg\nfrom eda_viz.viz import bar_plot\nbar_plot(df['categories'], df['numbers'])\n```\n\n![Bar Plot](https://raw.githubusercontent.com/ajaymaity/eda-viz/master/images/example-bar-plot.png)\n\nOther charts are a WIP.",
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