# Bokeh Tutorial ## Setup ### Clone or download the repo First get local copies of the tutorial notebooks: ``` $ git clone https://github.com/bokeh/bokeh-notebooks.git ``` Or download from: https://github.com/bokeh/bokeh-notebooks/archive/master.zip ### Install the dependencies This tutorial has been tested on: * bokeh=0.12.0 * pandas=0.18 * ipython-notebook=4.0.4 * ipywidgets=4.1.1 Other combinations may work also. Packages are available via PyPI and anaconda.org. #### Installing with anaconda Install [anaconda](http://continuum.io/downloads) Anaconda should come with all the dependencies included, but you may need to update your versions. #### Install with miniconda Install [miniconda](http://conda.pydata.org/miniconda.html). Use the command line to create an environment and install the packages: ``` $ conda env create $ source activate bokeh-notebooks ``` Run this from the tutorial directory where environment.yml lives. ### Get the sample data Bokeh has a sample data download that gives us some data to build demo visualizations. To get it run: ``` $ bokeh sampledata ``` ### Install datashader and holoviews (optional) Optional tutorials 11 and 12 require the datashader and holoviews packages, respectively, which can be installed with: ```bash $ conda install -c bokeh datashader $ conda install -c holoviews/label/dev holoviews ``` ### Run Jupyter/IPython notebook From this folder run jupyter notebook, and open the `00-intro.ipynb` notebook. ``` $ jupyter notebook ```