semvec/pypi-packages huggingface dataset:
Rajsaro 1.1
Python package for extracting information from various documents like Aadhar card, Covid certificate, GST certificate, PAN card, Passport, PDF to Image, and Voter ID card.
License: MIT
Requires Python: >=3.8

# RajsaroITSolutions

Rajsaro is a Python package designed to simplify the process of extracting information from a variety of identity documents including Aadhar cards, Covid certificates, GST Certificates, PAN cards, Passports, converting PDF to Images, and processing Voter ID cards.

## Installation

To install Rajsaro, simply use pip:

```bash
pip install rajsaro
```

## Usage

After installation, import the package into your project:

```python
from rajsaro import Aadhar, Pan, Gst, Passport, Voter

# Example: Extracting information from an Aadhar card
aadhar_info = Aadhar.extract_info('path_to_aadhar_card_image')
print(aadhar_info)
```

Replace `'path_to_aadhar_card_image'` with the actual path to the image file of the Aadhar card.

## Features

- Extract personal information from various identity documents.
- Convert PDF documents to images for further processing.
- Robust and flexible to handle different document formats.

## Development

To contribute to Rajsaro, clone the repository and make sure to follow the best practices for coding and documentation.

```bash
git clone https://github.com/your_username/Rajsaro.git
```

## Contributing

Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make are **greatly appreciated**.

Please ensure you provide tests for your code and update the documentation accordingly.

## License

Distributed under the MIT License. See `LICENSE` for more information.

## Contact

RajsaroITSolutions - rajsaroitsolutions@gmail.com

Project Link: [https://github.com/Gokul-RS16/RS_LIB/tree/master/Rajsaro](https://github.com/Gokul-RS16/RS_LIB/tree/master/Rajsaro)
```
chroptiks 0.1.7
A set of helper functions for quickly making matplotlib plots with a high number of built-in options.
License: MIT
Keywords: matplotlib plotting utilities

chroptiks
=========

Description
-----------

chroptiks is a Python package that offers advanced plotting utilities,
making it easier to create complex and informative visualizations. It
extends the functionality of libraries like matplotlib and scipy,
providing a user-friendly interface for a variety of plotting needs.

Requirements
------------

Python libraries: matplotlib, numpy, scipy

Installation
------------

To install chroptiks, run:

.. code:: bash

   pip install chroptiks

or if you want to install from source:

.. code:: bash

   git clone https://github.com/cagostino/chroptiks.git
   cd chroptiks
   python setup.py install

Features
--------

—2D Histograms (hist2d): Easily create 2D histograms for data analysis.

—1D Histograms (hist1d): Simplify the process of creating and
customizing 1D histograms.

—Scatter Plots (scatter): Enhanced functionality for scatter plot
creation.

—3D Plots (plot3d): Intuitive tools for 3D data visualization.

—Bar Charts (plotbar): Quick and customizable bar chart creation.

Example usage
-------------

hist2d, hist1d, scatter, plot3d, plotbar are now ready to be used as per
their defined functionalities and plots are generated through each of
their plot methods. For example:

.. code:: python


   import numpy as np
   from chroptiks.plotting_utils import hist2d

   x = np.linspace(-1,1, 100000)+np.random.normal(0,.1, size=100000)
   y = x**(3)+np.random.normal(0, 0.3, size=100000)
   z =  np.random.normal(size=100000)

   hist2d.plot(x,y,nx=200,ny=200)

   hist2d.plot(x,y,nx=40, ny=40, ccode = z, ccodename='Z', xlabel='X', ylabel='Y')

   hist2d.plot(x,y,nx=200,ny=200,bin_y=True, size_y_bin=0.1, xlabel='X', ylabel='Y', percentiles=False)

   from chroptiks.plotting_utils import hist1d

   hist1d.plot(z, range=(-2,2), bins=100, xlabel='Z', ylabel='Counts')

   hist1d.plot(z, range=(-2,2), bins=100, xlabel='Z', ylabel='Counts', normed=True)

   hist1d.plot(z, range=(-4,4), bins=100, xlabel='Z', ylabel='Cumulative Count', cumulative=True)



   from chroptiks.plotting_utils import scat

   #scat
   scat.plot(x,z)

   #scat with color-code
   scat.plot(x,y, ccode=z, color=None, edgecolor=None, vmin=-0.5, vmax=0.5)
   #note if you use ccode to color the points, you must set color to None, and I would advise you to set edgecolor to None as well or else each will have outlines.

   #scat with y-binning
   scat.plot(x, y, bin_y=True, size_y_bin=0.1, percentiles=True, xlabel='X', ylabel='Z', aspect='auto')