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<title>Training, Tutorials and Templates</title>
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<a class="menuItem" href="training-tutorials-and-templates.html">Training, Tutorials and Templates</a>
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<h1 class="title toc-ignore">Training, Tutorials and Templates</h1>
</div>
<p><strong>OxShef: Tools</strong> cannot be a complete overview of all visualisation tools available, nor can we maintain a complete overview of training and templates available for the dataviz tools that meet our <a href="https://oxshef-tools.netlify.com/reproducible-dataviz-workflow.html">reproducible dataviz workflow criteria</a>. However, you might find these resources generally useful:</p>
<ul>
<li><p><a href="https://github.com/sindresorhus/awesome">Awesome Lists (Data Viz)</a>: This is a crowd sourced collection of resources about data visualisation tools, tutorials and other resources. It’s maintained via GitHub, so anyone can contribute.</p></li>
<li><p><a href="https://Lynda.com">Lynda.com</a>: Subscription learning service with courses on a wide variety of dataviz tools, many Universities provide access to Lynda.com for free. Contact your local research support teams for support.</p></li>
<li><p><a href="https://datacamp.com">Datacamp.com</a>: Subscription learning service with courses on a variety of dataviz tools.</p></li>
</ul>
<p>Materials specific to dataviz tools that meet our <a href="https://oxshef-tools.netlify.com/reproducible-dataviz-workflow.html">reproducible dataviz workflow criteria</a>.</p>
<div id="section" class="section level2 tabset">
<h2></h2>
<div id="dash" class="section level3">
<h3>Dash</h3>
<p><a href="https://plot.ly/products/dash/">Dash</a> is a technology developed by <a href="http://plot.ly">plot.ly</a> that allows Python users to create rich, interactive data visualisations and interfaces - commonly abbreviated to “data dashboards”. This is a fairly new technology (first released June 2017) that does not have much coverage outside of the first-party resources on the plot.ly website.</p>
<p><strong>OxShef: dataviz</strong> are currently drafting a dedicated site with training, tutorials and templates for Dash dashboards. In the meantime, we recommend you check out the <a href="https://medium.com/@plotlygraphs/introducing-dash-5ecf7191b503">blog annoucement</a> and Chris’ <a href="https://youtu.be/sea2K4AuPOk">conference presentation at SciPy 2017</a>.</p>
</div>
<div id="jupyter" class="section level3">
<h3>Jupyter</h3>
<p><a href="jupyter.org">Jupyter</a> notebooks are the successor to iPython notebooks, a <em>literate programming</em> technology that allows text, code, charts and interactive content to be combined together into a single document. Jupyter allows code from multiple languages to be combined in the same document, the easiest to use languaes are <strong>Julia</strong>, <strong>Python</strong> and <strong>R</strong>. Using a combination of these technologies it is possible to build rich, interactive data visualisations. With some additional effort it is possible to host Jupyter notebooks in such a fashion that enables a <a href="https://tools.oxshef.io/reproducible-dataviz-workflow.html">reproducible dataviz workflow</a>.</p>
<p><strong>OxShef: dataviz</strong> are currently drafting a dedicated site with training, tutorials and templates for using Jupyter in a reproducible dataviz workfow. In the meantime, you might find this <a href="https://www.datacamp.com/community/tutorials/tutorial-jupyter-notebook">Datacamp.com free tutorial</a> useful and there is also a Lynda.com course that introduces the basics of Jupyter notebooks</p>
<iframe width="560" height="315" src="https://www.lynda.com/player/embed/543336?fs=3&w=560&h=315&ps=paused&utm_medium=referral&utm_source=embed+video&utm_campaign=ldc-website&utm_content=vid-543336" mozallowfullscreen="true" webkitallowfullscreen="true" allowfullscreen="true" frameborder="0">
</iframe>
<div style="margin-bottom:10px">
<strong><a href="https://www.lynda.com/NumPy-tutorials/NumPy-Data-Science-Essential-Training/508873-2.html" title="Learn how to use NumPy, Python, and Jupyter Notebook for numerical, scientific, and statistical programming as you build your analytics, machine learning, and data science skills.">NumPy Data Science Essential Training</a></strong> by <a href="https://www.lynda.com/author/1705401">Charles Kelly</a>
</div>
</div>
<div id="shiny" class="section level3">
<h3>Shiny</h3>
<p><a href="shiny.rstudio.com">Shiny</a> is an <code>R</code> library developed by RStudio that allows R users to create interactive web applications without having to learn HTML, CSS or JavaScript. <a href="https://oxshef-shiny.netlify.com"><strong>OxShef: Shiny</strong></a> provides a host of training, tutorials and templates for creating Shiny apps within the context of a fully <a href="https://oxshef-tools.netlify.com/reproducible-dataviz-workflow.html">reproducible dataviz workflow</a>.</p>
<p>There are many excellent resources for learning more (and keeping up to date with) Shiny:</p>
<ul>
<li><a href="https://github.com/grabear/awesome-rshiny">Awesome Shiny Resources</a>: This is a crowd sourced collection of resources for Shiny users.</li>
<li><a href="https://www.datacamp.com/courses/building-web-applications-in-r-with-shiny">Datacamp.com Shiny Course</a>: This is a free entirely-in-browser introduction to Shiny that is highly recommended to complete beginners to Shiny.</li>
<li><a href="shiny.rstudio.com/gallery/">RStudio’s Shiny Gallery</a>: This is an excellent showcase of examples and template Shiny apps, along with in-depth technical documentation on how the internals of Shiny works.</li>
</ul>
<p>There is also a Lynda.com course dedicated to creating Shiny apps and interactive presentations with RMarkdown.</p>
<iframe width="560" height="315" src="https://www.lynda.com/player/embed/490016?fs=3&w=560&h=315&ps=paused&utm_medium=referral&utm_source=embed+video&utm_campaign=ldc-website&utm_content=vid-490016" mozallowfullscreen="true" webkitallowfullscreen="true" allowfullscreen="true" frameborder="0">
</iframe>
<div style="margin-bottom:10px">
<strong><a href="https://www.lynda.com/RStudio-tutorials/Creating-Interactive-Presentations-Shiny-R/452087-2.html" title="Make the results of big data analysis more compelling and clear. Learn how to create interactive presentations and dashboards with RStudio and Shiny.">Creating Interactive Presentations with Shiny and R</a></strong> by <a href="https://www.lynda.com/author/4174500">Martin Hadley</a>
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