semvec/pypi-packages huggingface dataset:
uiza 1.2.0
Uiza SDK tool

# Python Client for Uiza platform

## Introduction

The Uiza API is organized around RESTful standard. Our API has predictable, resource-oriented URLs, and uses HTTP response codes to indicate API errors. JSON is returned by all API responses, including errors, although our API libraries convert responses to appropriate language-specific objects.

## Documentation

See the [.Uiza API docs v4](https://docs.uiza.io/v4).

## Installation

### Supported Python Versions

- Python 2.7.x. Python 2.7 support will be removed on January 1, 2020.
- Python 3.x
- Tested with Python 2.7.11, 3.4, 3.6.8

### Install uiza package via pip

Suggestion install this library using pip with [virtualenv](https://virtualenv.pypa.io/en/latest/). Because with virtualenv, it is possible to install this library without:

- Needing system install permission.
- Clashing with the installed system dependencies.

On Mac/Linux

```bash
pip install virtualenv
virtualenv <your-env>
source <your-env>/bin/activate
<your-env>/bin/pip install uiza
```

On Windows

```bash
pip install virtualenv
virtualenv <your-env>
<your-env>\Scripts\activate
<your-env>\Scripts\pip.exe install uiza
```

## Usage

The first, needing create Uiza connection using `app_id` and `authorization`:

```python
import uiza

uiza.authorization = "your-authorization"
uiza.app_id = "your-app-id"

``` 

After connection created, this is example search Entity:

```python
import uiza
from uiza.api_resources.entity import Entity
from uiza.exceptions import ServerException

uiza.authorization = "your-authorization"
uiza.app_id = "your-app-id"

try:
    entity_data, _ = Entity().search(keyword='Sample')
except ServerException as e:
    raise e
except Exception as e:
    raise e

...

```

Next steps, reading the [Client Library Documentation]() to see other available methods on the client.

- [Entity](https://github.com/uizaio/api-wrapper-python/blob/master/docs/entity.md)
- [Category](https://github.com/uizaio/api-wrapper-python/blob/master/docs/category.md)
- [Storage](https://github.com/uizaio/api-wrapper-python/blob/master/docs/storage.md)
- [Live Streaming](https://github.com/uizaio/api-wrapper-python/blob/master/docs/live.md)
- [Callback](https://github.com/uizaio/api-wrapper-python/blob/master/docs/callback.md)
- [User](https://github.com/uizaio/api-wrapper-python/blob/master/docs/user.md)

## Unittest

The first, you need install dependencies:

```bash
pip install -r requirements.txt
```

Run unittest:

```bash
python -m unittest discover tests
```

Coverage code:

```bash
coverage run -m unittest discover tests
coverage report
``` 


## Contributing

Bug reports and pull requests are welcome on GitHub at [https://github.com/uizaio/api-wrapper-python](https://github.com/uizaio/api-wrapper-python).

## License

The package is available as open source under the terms of the [MIT License](https://choosealicense.com/licenses/mit/).
xl-formulas 0.0.1
Helper to save Excel formulas from Pandas dataframes

# xlFormulas
Helper class to write Excel-style formula strings to worksheets when saving from a Pandas dataframe.

Default initialization assumes the worksheet will be saved with an index and header row (the first real 'data' cell would be B2) but an index and header parameter are available to ensure alignment.

Pass in mathematical operators with strings, limited support currently for Excel built-in functions. If a value is not a column name in df.columns it is passed in as it is, whether that means it's an operator or builtin function.

The ```.formula()``` method returns a list of strings beginning with '=' and containing the row index for the Excel formula

Installation:

```pip install xl-formulas```

Basic usage:

```
import pandas as pd
from xlFormulas import ExcelFormulas

df = pd.read_excel('sample_data.xlsx')

# Pass in Pandas dataframe to intialize ExcelFormulas helper
ef = ExcelFormulas(df)

# Returns a column like "=B2+C2" in df['C']
df['C'] = ef.formula('A + B')

# Makes a "=(B2 + C2)/(C2 - D2)" column in df['D']
df['D'] = ef.formula(f'{ef.paren('A + B')} / {ef.paren('B - C')}'

# Use Excel built-in functions (Still pretty buggy)
# This would get a column of "=SUM(B2,C2,5)" in df['E']
df['E'] = ef.formula(ef.builtin('SUM', 'A', 'B', 'C'))
```
paracoord 0.5
Parallel Coordinates plotting

# paracoord: Plot 2-dimensional arrays in Parallel coordinates

## Purpose
This package is an attempt to implement the idea of 
[parallel coordinates](https://link.springer.com/article/10.1007/s11416-009-0127-3) 
from [Sébastien Tricaud](https://www.splunk.com/blog/author/stricaud.html) and [
Philippe Saadé](mailto:psaade@gmail.com) to general purposes.

## Example
```
from paracoord import get_paracoord_plot


# Create 10x5 random array
values = np.random.random_sample((10, 5))
print(values)

# Plot parallel coordinates of those values
get_paracoord_plot(values)

# Set arbitrary labels for those 10 5-dimensional vectors
labels = ['aaa', 'bbb', 'aaa', 'ccc', 'bbb', 'aaa', 'aaa', 'bbb', 'aaa', 'ccc']
# Plot them in parallel coordinates with automatically chosen colors
get_paracoord_plot(values, labels=labels)
# Plot them with self defined color dict and save the resulting plot
color_dict = {'aaa': 'b', 'bbb': 'r', 'ccc': 'g'}
get_paracoord_plot(values, labels=labels, color_dict=color_dict, save_path='random_example.jpg', set_legend=True)
```

## Options
* `values`: 2-dimensional numpy array
* `labels`: optional, array containing labels for each row of `values`
* `color_dict`: dict, optional, ignored if ` labels` not provided. {label -> color} dict.
If `labels` is provided but not `color_dict`, the color of each label will be automatically chosen
* `save_path`: path to the file where the resulting image will be stored.
If not provided, image will not be stored
* `set_legend`: boolean, optional, ignored if `labels`not provided. If to set a color legend for the labels or not
* `box`: boolean. If to set a frame (x-axis, y-axis etc.) for the resulting image
* `ylims`: (ymin, ymax). If not provided, will be set to the result to `get_y_min_nax(values)`


## Installation
```
pip install paracoord
```

## Final note
Enjoy, do whatever you want with it as long as you don't hold me responsible for the consequences :)
Suggestions, remarks, critics, pull requests appreciated