semvec/pypi-packages huggingface dataset:
mxnet-neuron 1.5.1.1.0.1325.0
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MXNet Python Package
====================
MXNet is a deep learning framework designed for both *efficiency* and *flexibility*.
It allows you to mix the flavours of deep learning programs together to maximize the efficiency and your productivity.


Installation
------------
To install, check [Build Instruction](http://mxnet.io/get_started/setup.html)
Home-page: https://github.com/dmlc/mxnet
Author: UNKNOWN
Author-email: UNKNOWN
License: UNKNOWN
Description: UNKNOWN
Platform: UNKNOWN
pyclo 0.1.0
Immutable manipulation of Python data structures, Clojure style

# pyclo

Pyclo is a collection of functions for Python named after the Clojure standard library to perform the equivalent operation of the respective Clojure function.

Install with
```
pip install pyclo
```


## Rationale

While immutability is neither idiomatic nor common in Python, it is still beneficial to implement the concept through engineering discipline. However, soon one will find oneself writing the same constructs over and over again, and even though these expressions are fairly succinct, it is much nicer to refer to them by name. The goal of this library is to provide a collection of functions that promote immutable manipulation of standard Python data structures as a concept without strictly enforcing it.

They say that there are only two hard problems in software engineering, one of them being naming. Clojure is chosen as a source of inspiration for these functions because the author of this library considers Clojure's naming the gold standard.


## Reference

```
from pyclo import *
```

 - `dissoc(dict, *keys)` - return a copy of `dict` without specified `keys`.
 - `select_keys(dict, *keys)` - return a copy of `dict` only containing `keys`.
 - `get_in(dict, keys, default=None)` - look up a sequence of keys in a nested dict.


## Development

```
make test
make lint
make upload  # upload to Pypi
```
riskybusiness 0.0.3
A Python Library containing various functions to analyse the risk of a business.
Requires Python: >=3.6

# Analyse the risk of a business using Risky Business

## Functions :
1. Sharpe Ratio
2. Returns & Volatility
3. Risk by Return Ratio
4. Compounded Percentage
5. Annual Drawdown
6. Skewness & Kurtosis
7. Value Added Risk (VaR - Historic, Gaussian, Cornish-Fisher)
8. CVaR - Historic
9. VaR Comparison Plot

**Important** : Please read the [DOCUMENTATION](https://github.com/rajathkotyal/RiskyBusiness/blob/master/DOCUMENTATION.md) file before implementing any of the functions.

## Installation  

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install riskybusiness

```bash
pip install riskybusiness
```

## Usage

```python
import riskybusiness as rb
rb.FunctionName(dataset = Your_Dataset)
```
> Make sure the dataset is loaded using pandas with the necessary columns.

A sample program using all the functions is displayed in risky.ipynb
 - Open using Jupyter NB or Google Colab
 - This file contains the output samples of all the functions present in the library.

[github link](https://github.com/rajathkotyal/RiskyBusiness)

## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

## License
[MIT](https://choosealicense.com/licenses/mit/)