Metadata-Version: 2.1
Name: EZPlotly
Version: 0.0.8
Summary: An easy wrapper for making Plotly plots in Jupyter notebooks
Home-page: https://github.com/prateekt/EasyPlotly
Author: Prateek Tandon
Author-email: prateek1.tandon@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE.txt

# EZPlotly and EZPlotly_bio For Jupyter Notebooks
Introducing EZPlotly: An easy, intuitie wrapper for making Plotly plots in Jupyter notebooks

Plotly offers interactive plots, as opposed to the static plots that most other python visualization tools provide. However, Plotly syntax can be challenging to write, whereas the other libraries are a lot easier to plot with. EZPlotly helps bridge the gap. EZPlotly makes ploting with Plotly simpler and mot matplotlib or matlab-like for experienced users of those toolsets.

In addition, EZPlotly offers domain-specific extensions for making interactive domain-specific plots in Plotly.
-The YayROCS package enables common Deep Learning / Machine Learning plotting functions such as making interactive ROC curves, AUCs, and p-Value comparison charts.
-The EZPlotly_bio extension offers a rich toolset for bioinformaticians to make common bioinformatics plots such as qqplots, chromosome rolling medians, chromosome frequency histograms and barcharts. 

# Installation

pip install EZPlotly

# Example syntax:

```python
import EZPlotly as EP

exampleHist = EP.hist(data=a,min_bin=0.0,max_bin=1.0,bin_size=0.1,title='MyHistogram',xlabel='a')
exampleScatter = EP.scattergl(x=a,y=b,title='Test',xlabel='x',ylabel='y')
EP.plot_all([exampleHist,exampleScatter])
```

For more examples, checkout run the EZPlotlyExamples.ipynb in Jupyter!

# EasyPlotly_bio for Bioinformaticians:

In the bioinformatics domain? Currently in the works is a bioinformatics extension (EasyPlotly_bio) for making common bioinformatics plots such as qqplots, chromosome rolling medians, chromsome count bar charts, and chromosome histograms.


