https://github.com/andersy005/beyond-matplotlib-tutorial-sea-2018
Tutorial on building interactive data visualizations with Holoviews, Geoviews, and Bokeh for 2018 NCAR SEA Conference
https://github.com/andersy005/beyond-matplotlib-tutorial-sea-2018
bokeh geoviews holoviews matplotlib
Last synced: 9 months ago
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Tutorial on building interactive data visualizations with Holoviews, Geoviews, and Bokeh for 2018 NCAR SEA Conference
- Host: GitHub
- URL: https://github.com/andersy005/beyond-matplotlib-tutorial-sea-2018
- Owner: andersy005
- License: mit
- Created: 2018-01-10T04:05:46.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2018-04-05T06:42:40.000Z (about 8 years ago)
- Last Synced: 2024-12-30T13:36:48.371Z (over 1 year ago)
- Topics: bokeh, geoviews, holoviews, matplotlib
- Language: Jupyter Notebook
- Homepage:
- Size: 38.1 MB
- Stars: 4
- Watchers: 3
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
[](https://mybinder.org/v2/gh/andersy005/beyond-matplotlib-tutorial-sea-2018/master)
# Beyond Matplotlib: Building Interactive Climate Data Visualizations with Bokeh and Friends, SEA 2018
This repository contains materials: examples, demos for the [Beyond Matplotlib: Building Interactive Climate Data Visualizations with Bokeh and Friends](https://sea.ucar.edu/event/beyond-matplotlib-building-interactive-climate-data-visualizations-bokeh-and-friends) tutorial that will be presented at the [2018 UCAR Software Engineering Assembly](https://sea.ucar.edu/conference/2018).
The Python visualization tools presented in this repo include: [Bokeh](http://bokeh.pydata.org),
[HoloViews](http://holoviews.org),
[GeoViews](http://geo.holoviews.org),
[Matplotlib](http://matplotlib.org),
, and [HoloExt](http://holoext.readthedocs.io/en/latest/).
## Installation
### Running in the cloud (binder)
To run notebooks in the cloud (no installation required) [](https://mybinder.org/v2/gh/andersy005/beyond-matplotlib-tutorial-sea-2018/master)
### Running Locally
#### Step 1: Install a [Miniconda](http://conda.pydata.org/miniconda.html) (or [Anaconda](https://www.continuum.io/downloads) environment)
-----------------------------------------------------------------
Any Linux, Mac OS X, or Windows computer with a web browser (preferably Google Chrome, or FireFox) should be suitable.
If you don't already have conda on your machine, you can get it from [Miniconda](http://conda.pydata.org/miniconda.html), by opening a terminal window and
##### Download Miniconda
# for linux
$ wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh
# for osx
$ wget https://repo.continuum.io/miniconda/Miniconda3-latest-MacOSX-x86_64.sh -O miniconda.sh
# for windows
# go to: https://conda.io/miniconda.html
##### Install Miniconda
$ bash miniconda.sh
# follow instructions
#### Step 2: Clone beyond-matplotlib-tutorial-sea-2018 git repo
git clone https://github.com/andersy005/beyond-matplotlib-tutorial-sea-2018.git
#### Step 3: Then `cd` to the beyond-matplotlib-tutorial-sea-2018 folder and create a separate Conda environment to work in for this tutorial
cd beyond-matplotlib-tutorial-sea-2018
conda env update
This downloads all of the dependencies and then all you have to is:
source activate pyviz
(omitting "source" if you are on Windows).
#### Step 4: Launch Jupyter Notebook
You can then launch the notebook server and client
jupyter notebook
A browser window with a Jupyter Notebook instance should now open, letting you select and execute each notebook.
If you don't see the notebook appear (e.g. on some OS X versions), you may need to cut and paste the URL from the console output manually.
#### Step 5: Test that everything is working
You can see if everything has installed correctly by selecting the `00-welcome.ipynb` notebook and doing "Cell/Run All" in the menus. There may be warnings on some platforms, but you'll know it is working if you see the HoloViews logo after it runs `hv.extension()`