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    "info": {
        "author": "Agustin Rodriguez",
        "author_email": "agustin.dev@protonmail.com",
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            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3"
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        "description": "## From WhatsApp chats to pandas dataframe made easy\n\nWhatsParser is a tool for parsing `.txt` chat files rendered by the WhatsApp messaging App. Is intended to make the shift from WhatsApp data to pandas dataframe as rapid as possible. Reading and parsing the `.txt` file is done like this:\n\n```python\nfrom whatsparser import WhatsParser\n\nmessages = WhatsParser('./chat.txt')\n```\n\nOnce the file has been parsed, all messages are stored as dictionaries with three keys: _datetime_, _author_ and _content_. Using indexing you can access individual data point:\n\n```Python\nlen(messages) # Get how many messages there are\n>> 3590\n\nmessages[35] # Get a message\n>> {'datetime': datetime.datetime(2017, 9, 15, 19, 10, 2),\n    'author': 'Agustin Rodriguez',\n    'content': 'Hi! this is a Whatsapp message'}\n```\n\nThe datetime key stores a datetime object, all the others have string as values.\n\n### Pandas dataframe\n\nConvert all messages into a pandas DataFrame so you can use your favorite tools for data analysis:\n\n```Python\ndf = messages.to_dataframe() # Returns a pandas dataframe\n```\n\n## Looping\n\nWhatsParser also offer the possibility of iterate through the object using various functions. When iterating over `messages` a copy is made of all messages stored and iteration and changes occurs over this copy. It is possible to change the data store inside `messages` by assigning the results of the iteration to `messages.data`.\n\n### Filter messages\n\n```Python\ndef find_long_messages(message):\n  if len(message['content']) > 100:\n    return True\n  return False\n\nmessages.data = list(filter(find_long_messages, messages))\n# Now, messages contains only those messages with a length greater than 100 characters.\n```\n\n### List comprehension\n\n```Python\nfrom emoji import get_emoji_regexp\n\ndef remove_emojis(message):\n  message['content'] = get_emoji_regexp().sub(r'', message['content'])\n  return message\n\nmessages.data = [remove_emojis(message) for message in messages]\n# All messages got their emojis remove from the text\n```\n\n### Map function\n\n```Python\ndef remove_emojis(message):\n  message['content'] = get_emoji_regexp().sub(r'', message['content'])\n  return message\n\nmessages.data = list(map(remove_emojis, messages))\n```\n\n### For loop\n\nIterate over `messages.data` to make changes on the fly, if no just use `messages`.\n\n```Python\n# For changing data\nfor message in messages.data:\n  message['content'] = 'NEW CONTENT'\n\n# Without changing the data\nfor message in messages:\n  print(message['author'])\n\n```\n\n## License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n\n",
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        "keywords": "whatsapp,parser,text,dataframe",
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        "name": "WhatsParser",
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        "summary": "A parser for whatsapp .txt files",
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