Automate sentiment analysis tool

Author : Sazin Reshed Samin

• Email : sazinsamin50@gmail.com

autosentiment is an open source library that generates sentiment type(positive,negetive,neutral) pie char,percentage,number and ternary value for pandas dataframe text portion.

- Usage

For analysis the seintiment type in positive,negetive or neutral

- Setup in normal environment and command window:

pip install autosentiment

- Setup in jupyter notebook:

!pip install autosentiment

- Import library :

import autosentiment as at

- The library is pandas dataframe dependent.

Have to get dataframe('text columns') and give to command.
Like df['text]

Features

- sentiment type pie chart :

at.pie()

- sentiment type amount :

Get the sentiment type(postive,negetive,neutral numbers)

at.number()

- sentiment percentage :

Get the percentage of sentiment type

at.percentage() 

at.ternary_analysis

Get the type of all text, here -1:negetive, 0:neutral, 1:positive

at.ternary_analysis()

- An example usages

>>import autosentiment as at

>>import pandas as pd

>>df=pd.read_csv("/home/samin/anaconda3/dataset_2.csv")

>>percent=at.percentage(df['text'])

>>print(percent)
>>Positve : 33.31 %, Negetive 20.96 %, Neutral : 45.72 %

>>number=at.number(df['text'])

>>print(number)
>>{'positive  ': 1087, 'negetive': 684, 'neutral': 1492}

>>ana=at.analysis_ternary(df['text'])

>>print(ana)
>>[-1, 1, 0.0, 0.0, 0.0, 0.0,.......,1]

>>at.pie(df['text'])

• For any bug, please notify in my email : sazinsamin50@gmail.com