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"author_email": "briford@supercowpowers.com",
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"License :: OSI Approved :: Apache Software License",
"Natural Language :: English",
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"description": "## Bro Analysis Tools (BAT) [](https://travis-ci.org/SuperCowPowers/bat) [](http://codecov.io/github/SuperCowPowers/bat?branch=master) [](https://pypi.python.org/pypi/bat) [](https://choosealicense.com/licenses/apache-2.0) \n\nThe BAT Python package supports the processing and analysis of Bro data\nwith Pandas, scikit-learn, and Spark\n\n### Recent Improvements (Fall 2019):\n- Better Docs ()\n- Faster/Smaller Pandas Dataframes for large log files: [Large Dataframes](https://supercowpowers.github.io/bat/large_dataframes.html)\n- Better Panda Dataframe to Matrix (ndarray) support: [Dataframe To Matrix](https://supercowpowers.github.io/bat/dataframe_to_matrix.html)\n- Vastly improved Spark Dataframe Class:\n - [Bro to Spark](https://nbviewer.jupyter.org/github/SuperCowPowers/bat/blob/master/notebooks/Bro_to_Spark.ipynb)\n - [Bro to Parquet](https://nbviewer.jupyter.org/github/SuperCowPowers/bat/blob/master/notebooks/Bro_to_Spark.ipynb)\n\n## BroCon 2017 Presentation\n\nData Analysis, Machine Learning, Bro, and You!\n([Video](https://www.youtube.com/watch?v=pG5lU9CLnIU))\n\n## Why BAT?\n\nBro already has a flexible, powerful scripting language why should I use\nBAT?\n\n**Offloading:** Running complex tasks like statistics, state machines,\nmachine learning, etc.. should be offloaded from Bro so that Bro can\nfocus on the efficient processing of high volume network traffic.\n\n**Data Analysis:** We have a large set of support classes that help\nbridge from raw Bro data to packages like Pandas, scikit-learn, and\nSpark. We also have example notebooks that show step-by-step how to get\nfrom here to there.\n\n\n### Getting Started\n- [Examples of Using BAT](https://supercowpowers.github.io/bat/examples.html)\n\n### How-To Analysis Notebooks\n\n- [Bro to Scikit-Learn](https://nbviewer.jupyter.org/github/SuperCowPowers/bat/blob/master/notebooks/Bro_to_Scikit_Learn.ipynb)\n- [Bro to Matplotlib](https://nbviewer.jupyter.org/github/SuperCowPowers/bat/blob/master/notebooks/Bro_to_Plot.ipynb)\n- [Bro to Spark](https://nbviewer.jupyter.org/github/SuperCowPowers/bat/blob/master/notebooks/Bro_to_Spark.ipynb)\n- [Bro to Parquet](https://nbviewer.jupyter.org/github/SuperCowPowers/bat/blob/master/notebooks/Bro_to_Spark.ipynb)\n- [Bro to Kafka to Spark](https://nbviewer.jupyter.org/github/SuperCowPowers/bat/blob/master/notebooks/Bro_to_Kafka_to_Spark.ipynb)\n- [Clustering: Picking K (or not)](https://nbviewer.jupyter.org/github/SuperCowPowers/bat/blob/master/notebooks/Clustering_Picking_K.ipynb)\n- [Anomaly Detection Exploration](https://nbviewer.jupyter.org/github/SuperCowPowers/bat/blob/master/notebooks/Anomaly_Detection.ipynb)\n- [Risky Domains Stats and Deployment](https://nbviewer.jupyter.org/github/SuperCowPowers/bat/blob/master/notebooks/Risky_Domains.ipynb)\n\nInstall\n-------\n\n $ pip install bat\n\nDocumentation\n-------------\n\n\n\nThanks\n------\n\n- The DummyEncoder is inspired by Tom Augspurger's great PyData Chicago\n 2016 [Talk](https://youtu.be/KLPtEBokqQ0)\n\n\n\n",
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