Metadata-Version: 2.1
Name: pyDataVis
Version: 1.4.0
Summary: A GUI application for fast visualization and analysis of numerical data
Home-page: https://github.com/PierreAlphonse/pyDataVis.git
Author: Pierre Alphonse
Author-email: palphonse@wanadoo.fr
License: MIT
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Visualization
Description-Content-Type: text/markdown
Requires-Dist: pandas
Requires-Dist: scipy
Requires-Dist: matplotlib
Requires-Dist: PyQt5
Requires-Dist: odfpy
Requires-Dist: dans-diffraction

# pyDataVis

**pyDataVis** is an open source application for interactive visualization, analysis and manipulation of scientific data. There are many [free plotting software](https://en.wikipedia.org/wiki/Category:Free_plotting_software) most of them far more powerful than *pyDataVis*. However, in terms of simplicity, it is hard to beat. Indeed it is designed to be very easy to use, just drag and drop your data file in *pyDataVis* window and immediately you are seeing the curves. For now, *pyDataVis* is limited to 2D plotting.

*pyDataVis* is written in [Python](https://en.wikipedia.org/wiki/Python_(programming_language)) and use [PyQt](https://riverbankcomputing.com/software/pyqt/) as graphic user interface (GUI) and [Matplotlib](https://matplotlib.org/) for plotting.


## Installation

### Installation from Debian package
This package can be found on the [website](https://pyDataVis.github.io) of pyDataVis, in [Downloads page](https://pydatavis.github.io/Downloads.html).
Assuming that the .deb file is in Downloads folder, to install, open a Terminal and type:
```
cd Downloads
sudo dpkg -i pyDataVis.deb
```

### Installation with Windows installer
This installer can be found on the [website](https://pyDataVis.github.io) of pyDataVis, in [Downloads page](https://pydatavis.github.io/Downloads.html).


### Installation from the Python Package Index
Open a Terminal and run:
```
pip install pyDataVis
```
Then to launch the application:
```
pyDataVis
```

### Installation from source archives
pyDataVis requires Python 3, PyQt5, Numpy, Pandas, Scipy and Matplotlib. The easiest way to install everything is to use Open Source [Anaconda](https://www.anaconda.com/products/individual) that will "just work" out of the box for Windows, macOS and common Linux platforms.

The source archives can be found on the [website](https://pyDataVis.github.io) of pyDataVis, in [Downloads page](https://pydatavis.github.io/Downloads.html). Extract the archive to the place where you want to store the program.

You can instead clone the repository if you have [git](https://git-scm.com/) installed.
Open a Terminal and change the current working directory to the location where you want to clone pyDataVis, for example ~/myprog:
```
cd ~/myprog
```
Then type:
```
git clone https://github.com/pyDataVis/pyDataVis.git
```

To launch the application, change the current working directory to the pyDataVis folder, for example ~/myprog/pyDataVis:
```
cd ~/myprog/pyDataVis
```
and execute the pyDataVis.py script:
```
python pyDataVis.py
```


## Support
To display the manual, open the page https://pydatavis.github.io/ in your browser or use the *Help* option in the *Help* menu.

The folder *examples*, in the source archives, contains files for testing almost all the function. For those who have not installed from source archives, they can be found on the [website](https://pyDataVis.github.io) of pyDataVis, in [Downloads page](https://pydatavis.github.io/Downloads.html).

If you need more information, feel free to contact me at: palphonse@wanadoo.fr


## Testing
To see almost every script commands in action you can run the self tests with the 'Run tests' option in Help menu.


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


## Author
Pierre Alphonse
palphonse@wanadoo.fr


## Contributing
This is a one-man project made by a non-professional. There must be many thing to improve.
Any help is welcome.


## Roadmap
This sofware was developed on Linux (Ubuntu 20.04), tested on Windows 10 but not yet tested on macOS.



