semvec/pypi-packages huggingface dataset:
tdam-api 0.1.0
A Python client for the TDAmeritrade Trading API
License: MIT
Keywords: tdam_api tdameritrade api trading stocks options

========
Overview
========

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    :target: https://travis-ci.org/jbasu/tdam_api

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    :target: https://coveralls.io/r/jbasu/tdam_api

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A Python Client for the TDAmeritrade API

* Free software: MIT license

Installation
============

::

    pip install tdam_api

Documentation
=============


https://tdam_api.readthedocs.io/


Development
===========

To run the all tests run::

    tox

Note, to combine the coverage data from all the tox environments run:

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    - - Windows
      - ::

            set PYTEST_ADDOPTS=--cov-append
            tox

    - - Other
      - ::

            PYTEST_ADDOPTS=--cov-append tox



Documentation
-------------

The full documentation is at http://tdam_api.rtfd.org.
pctl-scale 0.1.1
Scale a variable into an open interval (0,1) whereas values within a given lower and upper percentile maintain a linear relation, and outlier saturate towards the interval limits.
License: MIT
Requires Python: >=3.6

[![Build Status](https://travis-ci.org/kmedian/pctl_scale.svg?branch=master)](https://travis-ci.org/kmedian/pctl_scale)
[![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/kmedian/pctl_scale/master?urlpath=lab)

# pctl_scale
Scale a variable into an open interval (0,1) whereas values within a given lower and upper percentile maintain a linear relation, and outlier saturate towards the interval limits.

This scaling functions was developed with **ratio-scale** data in mind 
(i.e. it has a natural zero value).


## Table of Contents
* [Installation](#installation)
* [Usage](#usage)
* [Commands](#commands)
* [Support](#support)
* [Contributing](#contributing)


## Installation
The `pctl_scale` [git repo](http://github.com/kmedian/pctl_scale) is available as [PyPi package](https://pypi.org/project/pctl_scale)

```
pip install pctl_scale
```


## Usage
Check the [examples](examples) folder for notebooks.


## Commands
* Check syntax: `flake8 --ignore=F401`
* Run Unit Tests: `python -W ignore -m unittest discover`
* Remove `.pyc` files: `find . -type f -name "*.pyc" | xargs rm`
* Remove `__pycache__` folders: `find . -type d -name "__pycache__" | xargs rm -rf`
* Upload to PyPi with twine: `python setup.py sdist && twine upload -r pypi dist/*`


## Debugging
* Notebooks to profile python code are in the [profile](profile) folder


## Support
Please [open an issue](https://github.com/kmedian/pctl_scale/issues/new) for support.


## Contributing
Please contribute using [Github Flow](https://guides.github.com/introduction/flow/). Create a branch, add commits, and [open a pull request](https://github.com/kmedian/pctl_scale/compare/).
sf_tools 2.0.4
Tools for image analysis, signal processing and statistics.
License: MIT

sf_tools 

 Author: Samuel Farrens 
 Year: 2018 
 Email: samuel.farrens@cea.fr 
 Website: https://sfarrens.github.io 

 sf_tools is a series of Python modules with applications to image analysis signal processing and statistics.. 

 Full documentation available here: https://sfarrens.github.io/sf_tools/