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Building Python Data Applications with Blaze and Bokeh Tutorial, SciPy 2015

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Blaze and Bokeh tutorial, SciPy 2015

Building Python Data Applications with Blaze and Bokeh Tutorial, SciPy 2015

Setup

git clone https://github.com/chdoig/scipy2015-blaze-bokeh.git
cd scipy2015-blaze-bokeh
  • Option A: Anaconda

If you don't have Anaconda installed, you can install it from here. After following the instructions, you should be ready to go. Check it with:

python check_env.py

If you already have Anaconda installed, make sure to update both conda and the dependencies to the latest versions, by running:

conda update conda
conda install bokeh=0.9
conda install blaze=0.8
conda install ipython=3.2
conda install netcdf4
  • Option B: Miniconda or Conda Environments

If you want one the following:

  • a lightweight alternative to Anaconda, you can install Miniconda from here.

or

  • isolate this scipy tutorial dependencies from your default Anaconda by using conda environments.

Follow this commands after cloning this repository:

cd scipy2015-blaze-bokeh
conda env create

If you are running Linux or OS X run:

source activate scipy-tutorial

If you are running Windows, run:

activate scipy-tutorial

Testing

Make sure you have the right environment setup by running the following script:

python check_env.py

Also, try to run the testing notebook (0 - Test Notebook.ipynb):

ipython notebook

and run all the cells.

Data

This tutorial will be using datasets from the following projects:

For your convenience I have uploaded the datasets we are going to use directly to s3. Download the datasets before attending the tutorial from:

Move those datasets to the folder ~/scipy2015-blaze-bokeh/data

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