semvec/pypi-packages huggingface dataset:
statsfig 0.2.4
Stats Figures package
Requires Python: >=3.6

# Statsfig

Statsfig allow you to create following figures easily:

- Bernoulli distribution

- Binomial distribution
- Box-and-Whisker plot
- Chi square figures
- Exponential distribution
- Gamma distribution

- Normal distribution

- Poisson distribution
- Uniform distribution


## Installation

```
pip install statsfig
```

```
import statsfig as sf
```

## Available functions

| Functions                                                    | Description                                            |
| ------------------------------------------------------------ | ------------------------------------------------------ |
| [bernofig()](https://github.com/shinokada/statsfig/blob/master/doc/bernofig.md) | Bernoulli Distribution                                 |
| [binofig()](https://github.com/shinokada/statsfig/blob/master/doc/binomial.md) | Binomial Distribution                                  |
| [boxplot()](https://github.com/shinokada/statsfig/blob/master/doc/boxplot.md) | Box and whisker plot                                   |
| [chifig()](https://github.com/shinokada/statsfig/blob/master/doc/chifig.md) | Chi-Square Distribution                                |
| [expofig()](https://github.com/shinokada/statsfig/blob/master/doc/expofig.md) | Exponential Distribution                               |
| [gammafig()](https://github.com/shinokada/statsfig/blob/master/doc/gammafig.md) | Gamma Distribution                                     |
| [normcdf()](https://github.com/shinokada/statsfig/blob/master/doc/normal.md#normcdf) | Normal Distribution                                    |
| [normpdf_std](https://github.com/shinokada/statsfig/blob/master/doc/normal.md#normpdf_std) | Normal Distribution with different standard deviations |
| [normpdf_mean](https://github.com/shinokada/statsfig/blob/master/doc/normal.md#normpdf_mean) | Normal Distribution with different means               |
| [poisfix()](https://github.com/shinokada/statsfig/blob/master/doc/poisfig.md) | Poisson Distribution                                   |
| [uniformfig()](https://github.com/shinokada/statsfig/blob/master/doc/uniformfig.md) | Uniform Distribution                                   |
faytheclient 0.0.3
Faythe API Client Library
Requires Python: >=3.6

# Faythe Python Client

[![license](https://img.shields.io/badge/license-Apache%20v2.0-blue.svg)](LICENSE) [![PyPI version](https://badge.fury.io/py/faytheclient.svg)](https://badge.fury.io/py/faytheclient)

This is a client library for [Faythe](https://github.com/vCloud-DFTBA/faythe) built on the its API. It provides a Python API (the faytheclient module).

- **Python 3 only.**
- **This client is compatible with Faythe version >= v0.4.4.**

## Installation

Install the client:

```bash
python setup.py install
```

This package can be found on [PyPI](https://pypi.python.org/pypi/faytheclient).

```bash
pip install faytheclient
```

## Examples

The example can be found [here](./examples/).

- Create a copy of the environment variables example. Then adjust it:

```bash
cp .env.example .env
```

- Source the .env file:

```bash
source .env
```

- Run the example:

```bash
python example.py
```
discoin 4.0
Official Discoin Package
Requires Python: >=3.6

# Discoin for Python

This is the official discoin library for python. Here is discoin's [Gitbook](https://discoin.gitbook.io/docs/)

## Requirements
* Python 3.6 or up
* aiohttp

## Installation
```bash
$ pip install discoin
```

Documentation can be found [here](https://discoinpy.readthedocs.io)

## Credits
* [Dr_Ari_Gami](https://github.com/Dr-Ari-Gami/) (Main Developer)
* [DeveloperAnonymous](https://github.com/DeveloperAnonymous) (Collaborator)
* [Theelgirl](https://github.com/Theelgirl) (Collaborator)
* [PizzaFox](https://github.com/pizzafox) (Main developer of discoin)
* [Austin Huang](https://github.com/austinhuang0131) (Owner of discoin)