Metadata-Version: 2.1
Name: ztext
Version: 0.0.8
Summary: An easy to use NLP tool
Home-page: https://github.com/ZackAnalysis/ztext
Author: Zack Dai
Author-email: zdai@brocku.ca
License: UNKNOWN
Description: # ztext
        
        This project is designed for NLP analysis eaily, event you don't have any background of NLP you still can use it for text insights.
        Functions:
          1. Text clean.
          2. Topic analysis
          3. SVO (Subject Verb and Object extraction)
          4. NER (Entity extraction)
          5. Topic and SVO visualization (for now Visualization only support run in Jupyter notebook and Colab)
        
        ![ztext](https://raw.githubusercontent.com/ZackAnalysis/ztext/master/ztextdemo.png)
        
        ## install
        
        In python3.6 or later environment
        
        `pip install ztext`
        
        In IPython, Jupyter notebook or Colab
        `!pip install ztext`
        
        from source:
        `pip3 install git+https://github.com/ZackAnalysis/ztext.git`
        
        ## Quick Start
        
        Start a Jupyter notebook locally or a Colab notebook ([https://colab.research.google.com/](https://colab.research.google.com/))
        
        ### find a demo at
        [https://colab.research.google.com/drive/1W2mD6QHOGdVEfGShOR_tBnYHxz_D5ore?usp=sharing](https://colab.research.google.com/drive/1W2mD6QHOGdVEfGShOR_tBnYHxz_D5ore?usp=sharing)
        
        install package:
        `!pip install ztext`
        `import ztext`
        
        load sampledata
        from sampledata:
        `df = ztext.sampledata()`
        `zt = ztext.Ztext(df=df, textCol='content',nTopics=5, custom_stopwrods=['sell','home'], samplesize=200)`
        
        from file 
        `!wget https://github.com/ZackAnalysis/ztext/blob/master/ztext/sampleData.xlsx?raw=true`
        `filename = "sampleData.xlsx"`
        `zt = ztext.Ztext()`
        `zt.loadfile(filename, textCol='content')`
        `zt.nTopics = 6`
        `zt.custom_stopwords = ['text','not','emotion']`
        
        from pandas dataframe
        `zt.loaddf(df)`
        
        ### Functions
        
        #### Sentiment analysis:
        `zt.sentiment()`
        
        #### Topic analysis:
        `zt.get_topics()`
        
        #### SVO and NER
        `zt.getSVO('topic2')`
        
        #### Visulzation
        `zt.getldaVis()`
        
        `zt.getSVOvis('topic2',options="any")`
        
        #### save output
        
        `zt.df.to_excel('filename.xlsx`)`
        
        
        
        
        
        
        
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
