Metadata-Version: 2.1
Name: ProcessEntropy
Version: 0.5.dev0
Summary: A toolkit for calculating process entropy quickly. With specific applications to tweets.
Home-page: https://github.com/tobinsouth/ProcessEntropy
Author: Tobin South
License: MIT license
Description: # ProcessEntropy
        
        A toolkit for calculating process entropy quickly. With specific applications to tweets.
        
        
        ## Example Usage
        
        ```
        # Load in tweets between 2018/11/16 to 2019/01/01
        import pandas as pd
        with open("example_data/BBCWorld_Tweets_small.csv", 'r') as f:
            BBC = pd.read_csv(f)
            
        with open("example_data/BuzzFeedNews_Tweets_small.csv", 'r') as f:
            BuzzFeed = pd.read_csv(f)
        
        
        # Find process entropy of BuzzFeed tweets
        from ProcessEntropy.CrossEntropy import tweet_self_entropy
        
        print(tweet_self_entropy(BuzzFeed['tweet']))
        
        
        # Find cross entropy between BuzzFeed and BBC World
        from ProcessEntropy.CrossEntropy import timeseries_cross_entropy
        
        target = list(zip(BuzzFeed['created_at'], BuzzFeed['tweet']))
        source = list(zip(BBC['created_at'], BBC['tweet']))
        
        print(timeseries_cross_entropy(target, source))
        
        
        
        ```
        
        ## Requirements
        
        - Python 3.x with packages:
        	- Numba
        	- NTLK
        	- Numpy
        
        
        ## Installation
        
        ```
        pip install ProcessEntropy
        ```
        
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