tweets-preprocess 0.2.4

Library for tweets preprocessing

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Tweets Preprocessor

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Preprocessor is a preprocessing library for tweet data written in Python. When building Machine Learning systems based on tweets and text data like twitter sentiment analysis, topic modelling, etc., preprocessing is required. This is required because of quality of the data as well as dimensionality reduction purposes.

This library makes it easy to clean the tweets so you don't have to write the same helper functions over and over again ever time.

Features

Currently supports cleaning :

• URLs
• Hashtags
• Mentions
• Emojis
• Smileys
• Length constraint
• remove tweets containing few specific keywords like birthday,congratulations,etc.
• .csv and .xlsx file support

Python 3.9+ on Windows.

Usage

Basic cleaning:

.. code:: python

>>># Import Preprocess from your library
>>>from tweets_preprocess import Preprocess
>>>import pandas as pd
>>>import numpy as np

>>># Instantiate a Preprocess object
>>>data = pd.read_excel(r"D:\Ipac_new\My_Python_Lib\tweet_preprocess\sample.xlsx")
>>>data['pre_text'] = ""

>>>rem = ["happy birthday","birthday","congratulations","rip","thank you","congrats","thanks"]  ## sample keywords
>>>length = 35 
>>>p = Preprocess(data,'Text',rem,length)
>>>d = p.process()

>>>data['pre_text'] = pd.Series(d)

>>>d1 = data.loc[data['pre_text']!='']
>>>#save cleaned tweets to csv file
d1.to_csv('pre-data.csv')

Example:
Raw Tweet: 'Tweet Preprocessor is #awesome 👍 https://github.com/anusha-ipac/tweets_preprocess'
Cleaned Tweet: 'Preprocessor is'

Removed hashtags, emojis, URLs from the raw tweet and returned clean tweet.
Removes tweets containing specific keywords.

Processing files:

Preprocessor currently supports processing .csv and .xlsx formats.

Installation

Using pip:

.. code:: bash

$ pip install tweets-preprocess

Using manual installation:

.. code:: bash

$ python setup.py build
$ python setup.py install