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        "description": "# ProcessEntropy\n\nA toolkit for calculating process entropy quickly. With specific applications to tweets.\n\n\n## Example Usage\n\n```\n# Load in tweets between 2018/11/16 to 2019/01/01\nimport pandas as pd\nwith open(\"example_data/BBCWorld_Tweets_small.csv\", 'r') as f:\n    BBC = pd.read_csv(f)\n\nwith open(\"example_data/BuzzFeedNews_Tweets_small.csv\", 'r') as f:\n    BuzzFeed = pd.read_csv(f)\n\n\n# Find process entropy of BuzzFeed tweets\nfrom ProcessEntropy.CrossEntropy import tweet_self_entropy\n\nprint(tweet_self_entropy(BuzzFeed['tweet']))\n\n\n# Find cross entropy between BuzzFeed and BBC World\nfrom ProcessEntropy.CrossEntropy import timeseries_cross_entropy\n\ntarget = list(zip(BuzzFeed['created_at'], BuzzFeed['tweet']))\nsource = list(zip(BBC['created_at'], BBC['tweet']))\n\nprint(timeseries_cross_entropy(target, source))\n\n\n\n```\n\n## Requirements\n\n- Python 3.x with packages:\n\t- Numba\n\t- NTLK\n\t- Numpy\n\n\n## Installation\n\n```\npip install ProcessEntropy\n```\n\n\n",
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