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README.md

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+
+# HoloViews <img src="http://assets.holoviews.org/logo/holoviews_color_icon_500x500.png" alt="HoloViews logo" height="40px" align="right" />
+
+**Stop plotting your data - annotate your data and let it visualize
+itself.**
+
+<div class="container">
+<div class="common"><img src="http://assets.holoviews.org/collage/iris.png" width='20%'>
+                    <img src="http://assets.holoviews.org/collage/cells.png" width='22%'>
+                    <img src="http://assets.holoviews.org/collage/scatter_example.png" width='43%'></div>
+<div class="common"><img src="http://assets.holoviews.org/collage/square_limit.png" width='20%'>
+                    <img src="http://assets.holoviews.org/collage/bars_example.png" width='20%'>
+                    <img src="http://assets.holoviews.org/collage/texas.png" width='20%'>
+                    <img src="http://assets.holoviews.org/collage/mandelbrot.png" width='20%'></div>
+<div class="common"><img src="http://assets.holoviews.org/collage/dropdown.gif" width='31%'>
+                    <img src="http://assets.holoviews.org/collage/dragon_fractal.gif" width='26%'>
+                    <img src="http://assets.holoviews.org/collage/ny_datashader.gif" width='31%'></div>
+</div>
+
+HoloViews requires [Param](http://ioam.github.com/param/) and
+[Numpy](http://www.numpy.org/) and is designed to work together with
+[Matplotlib](http://matplotlib.org/) or
+[Bokeh](http://bokeh.pydata.org), making use of the [Jupyter/IPython
+Notebook](http://jupyter.org).
+
+You can get the latest version of HoloViews from the ioam conda channel:
+
+> conda install -c ioam holoviews
+
+Or clone holoviews directly from GitHub with:
+
+    git clone git://github.com/ioam/holoviews.git
+
+Please visit [our website](http://holoviews.org) for official releases,
+installation instructions, documentation, and many detailed [example
+notebooks and tutorials](http://holoviews.org/Tutorials). Additional
+user contributed notebooks may be found in the
+[holoviews-contrib](https://github.com/ioam/holoviews-contrib)
+repository including examples that may be run live on
+[mybinder.org](http://mybinder.org/repo/ioam/holoviews-contrib).
+
+For general discussion, we have a [gitter
+channel](https://gitter.im/ioam/holoviews). In addition we have [a
+user-contributed wiki](https://github.com/ioam/holoviews-contrib/wiki)
+describing current work-in-progress and experimental features. If you
+find any bugs or have any feature suggestions please file a GitHub Issue
+or submit a pull request.
+
+Usage
+-----
+
+Once you've installed HoloViews, you can get started by launching
+Jupyter Notebook:
+
+    jupyter notebook
+
+Now you can download the [tutorial
+notebooks](http://assets.holoviews.org/notebooks-1.7.zip). unzip them
+somewhere Jupyter Notebook can find them, and then open the
+Homepage.ipynb tutorial or any of the others in the Notebook. Enjoy
+exploring your data!
+
+Note: When running HoloViews in Jupyter Notebook 5.0 a data rate limit
+was introduced which severely limits the output that HoloViews can
+display. This limit will be removed again in the upcoming 5.1 release,
+in the meantime you can raise the limit manually by overriding the
+default `iopub_data_rate_limit`:
+
+    jupyter notebook --NotebookApp.iopub_data_rate_limit=100000000
+
+Alternatively you can set a higher default in the user configuration
+file in `~/.jupyter/jupyter_notebook_config.py`, by adding:
+
+    c.NotebookApp.iopub_data_rate_limit=100000000
+
+If the configuration file does not exist generate one first using:
+
+    jupyter notebook --generate-config
+
+Features
+--------
+
+**Overview**
+
+-   Lets you build data structures that both contain and visualize
+    your data.
+-   Includes a rich [library of composable
+    elements](http://www.holoviews.org/Tutorials/Elements.html) that can
+    be overlaid, nested and positioned with ease.
+-   Supports [rapid data
+    exploration](http://www.holoviews.org/Tutorials/Exploring_Data.html)
+    that naturally develops into a [fully reproducible
+    workflow](http://www.holoviews.org/Tutorials/Exporting.html).
+-   Create interactive visualizations that can be controlled via widgets
+    or via custom events in Python using the 'streams' system. When
+    using the bokeh backend, you can use streams to directly interact
+    with your plots.
+-   Rich semantics for [indexing and slicing of data in arbitrarily
+    high-dimensional
+    spaces](http://www.holoviews.org/Tutorials/Sampling_Data.html).
+-   Plotting output using the
+    [Matplotlib](http://www.holoviews.org/Tutorials/Elements.html),
+    [Bokeh](http://www.holoviews.org/Tutorials/Bokeh_Elements.html), and
+    [plotly](http://plot.ly/) backends.
+-   A variety of data interfaces to work with tabular and N-dimensional
+    array data using [NumPy](http://www.numpy.org/),
+    [pandas](http://pandas.pydata.org/),
+    [dask](http://dask.pydata.org/en/latest/),
+    [iris](http://scitools.org.uk/iris/) and
+    [xarray](http://xarray.pydata.org/en/stable/).
+-   Every parameter of every object includes
+    easy-to-access documentation.
+-   All features [available in vanilla Python 2 or
+    3](http://www.holoviews.org/Tutorials/Options.html), with
+    minimal dependencies.
+
+**Support for maintainable, reproducible research**
+
+-   Supports a truly reproducible workflow by minimizing the code needed
+    for analysis and visualization.
+-   Already used in a variety of research projects, from conception to
+    final publication.
+-   All HoloViews objects can be pickled and unpickled.
+-   Provides comparison utilities for testing, so you know when your
+    results have changed and why.
+-   Core data structures only depend on the numpy and param libraries.
+-   Provides [export and archival
+    facilities](http://www.holoviews.org/Tutorials/Exporting.html) for
+    keeping track of your work throughout the lifetime of a project.
+
+**Analysis and data access features**
+
+-   Allows you to annotate your data with dimensions, units, labels and
+    data ranges.
+-   Easily [slice and
+    access](http://www.holoviews.org/Tutorials/Sampling_Data.html)
+    regions of your data, no matter how high the dimensionality.
+-   Apply any suitable function to collapse your data or
+    reduce dimensionality.
+-   Helpful textual representation to inform you how every level of your
+    data may be accessed.
+-   Includes small library of common operations for any scientific or
+    engineering data.
+-   Highly extensible: add new operations to easily apply the data
+    transformations you need.
+
+**Visualization features**
+
+-   Useful default settings make it easy to inspect data, with
+    minimal code.
+-   Powerful normalization system to make understanding your data across
+    plots easy.
+-   Build [complex animations or interactive visualizations in
+    seconds](http://www.holoviews.org/Tutorials/Exploring_Data.html)
+    instead of hours or days.
+-   Refine the visualization of your data interactively
+    and incrementally.
+-   Separation of concerns: all visualization settings are kept separate
+    from your data objects.
+-   Support for fully interactive plots using the [Bokeh
+    backend](http://www.holoviews.org/Tutorials/Bokeh_Backend.html).
+
+**Jupyter Notebook support**
+
+-   Support for all recent releases of IPython and Jupyter Notebooks.
+-   Automatic tab-completion everywhere.
+-   Exportable sliders and scrubber widgets.
+-   Custom interactivity using streams and notebook comms to dynamically
+    updating plots.
+-   Automatic display of animated formats in the notebook or for export,
+    including gif, webm, and mp4.
+-   Useful IPython magics for configuring global display options and for
+    customizing objects.
+-   [Automatic archival and export of
+    notebooks](http://www.holoviews.org/Tutorials/Exporting.html),
+    including extracting figures as SVG, generating a static HTML copy
+    of your results for reference, and storing your optional metadata
+    like version control information.
+