ztext 0.0.8

An easy to use NLP tool

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)

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/)

find a demo at

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)`