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https://github.com/megbedell/astro-dataviz

demos of interactive data viz packages with astronomical data
https://github.com/megbedell/astro-dataviz

altair astronomy bokeh data-visualization matplotlib-animation

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demos of interactive data viz packages with astronomical data

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README 

        
This repository contains some IPython worksheets designed to demonstrate the relative capabilities of a few interactive plotting modules in python. These worksheets were made by Megan Bedell.



Slides for a companion talk can be found [here](https://docs.google.com/presentation/d/1sGvM4S9nQByNv3_1aj4nH5ynvp_pQt5MI1hk7djMcwk/edit?usp=sharing).



## Contents



The `animated_cepheids.ipynb` notebook shows how to make animated gifs or movies with matplotlib. As an example, we make a (somewhat cartoony) illustration of how Cepheid variable stars change in brightness over time using Gaia DR1 measurements.



The `interactive_exoplanets.ipynb` notebook demonstrates interactive plotting (tooltips, scroll and zoom, cross-linking plots, etc) with bokeh and altair. In this example, we use properties of confirmed exoplanets to make a mass-radius diagram.



The `interactive_gaia.ipynb` notebook ~~scales this up to large datasets with vaex and holoviews~~ is an unfinished look at using vaex and holoviews to view Gaia data. Although it's not extremely usable at the moment, it does contain links to other tutorials that may be helpful.



## Required software



These notebooks run with Python 3 and [Jupyter notebooks](http://jupyter.org/).



To run `animated_cepheids.ipynb` you'll just need a basic scientific stack (numpy, matplotlib, pandas) and astroquery. All of these are easy to install with pip.



To run `interactive_exoplanets.ipynb` you'll additionally need bokeh and altair, also available with pip:



```

pip install bokeh altair

```



If you're going to run from a notebook, you're good to go. If you want to run in Jupyter Labs you'll need an extension to make the bokeh plots render:



```

jupyter labextension install jupyterlab_bokeh

```



Note that altair is recommended for use with Jupyter Labs, but it still works in a notebook (with one extra line of setup code).



For `interactive_gaia.ipynb`, you'll need holoviews and vaex. The installation for these is more complex and has the potential to interfere with your normal python environment. One good way of installing is using [Anaconda distribution](http://continuum.io/downloads) and creating a virtual environment in which to install these packages. Here's a snippet of code to do this:



```

conda create -n dataviz_env python=3.6

source activate dataviz_env

pip install jupyterlab pandas astropy 

conda install -c conda-forge vaex

conda install -c conda-forge holoviews

```



(Some of the conda installs can be done in pip too, but I ran into install issues there that didn't come up with conda. Your mileage may vary.)



Then get the JupyterLab extension for holoviews:



```

jupyter labextension install @pyviz/jupyterlab_holoviews

```



## Using these notebooks



Download this repository by running:



```

git clone https://github.com/megbedell/astro-dataviz

```



Then go into the `astro-dataviz` directory and start a Jupyter notebook server:



```

jupyter notebook

```



Click on a notebook file to run it.