semvec/pypi-packages huggingface dataset:
Ficamacos 0.1.0
Option pricing with COS, Carr Madan and Filon's method
Requires Python: >=3.7

# Ficamacos

## Usage
Calculate option prices under Lévy market model using Filon's method, Carr-Madan'method and COS method.


## Requirement
Numpy


## Installation

```
pip install Ficamacos
```
ztext 0.0.8
An easy to use NLP tool
Requires Python: >=3.6

# 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`)`