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Site updated at 2016-07-24 17:14:05 UTC

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blog/categories/iot-data/atom.xml
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@ -4,7 +4,7 @@
<title><![CDATA[Category: IoT-Data | Home Assistant]]></title>
<link href="https://home-assistant.io/blog/categories/iot-data/atom.xml" rel="self"/>
<link href="https://home-assistant.io/"/>
<updated>2016-07-23T19:30:05+00:00</updated>
<updated>2016-07-24T17:13:16+00:00</updated>
<id>https://home-assistant.io/</id>
<author>
<name><![CDATA[Home Assistant]]></name>
@ -39,7 +39,7 @@ One of the graphs created with this tutorial.
<!--more-->
<h3><a class='title-link' name='dependencies' href='#dependencies'></a> Dependencies </h3>
<h3>{% linkable_title Dependencies %}</h3>
<p>In order to run the provided Jupyter notebook, please make sure you have the following applications/libraries installed on your computer:</p>
@ -53,11 +53,11 @@ One of the graphs created with this tutorial.
<p>As a Windows user myself, I find the easiest, quickest and most hassle-free way of installing all of these dependencies is to use <a href="https://winpython.github.io/">WinPython</a>. This free open-source portable distribution includes all of the dependencies required for this notebook, as well as a few other essential Python libraries you may require for data exploration in the future.</p>
<h4><a class='title-link' name='why-jupyter' href='#why-jupyter'></a> Why Jupyter? </h4>
<h4>{% linkable_title Why Jupyter? %}</h4>
<p>While all Home Assistant implementations can have varying setup, components and scripts, the underlying data structure is standardized and well-defined. This allows us to write Python code that is environmentally agnostic. Wrapping it in a Jupyter notebook ensures the code, visualizations and directions/explanations are kept digestible and neatly-packaged. One of the amazing features of Jupyter is the ability to change code as you go along, customizing all outputs and visualizations on the fly!</p>
<h4><a class='title-link' name='where-do-i-start' href='#where-do-i-start'></a> Where do I start? </h4>
<h4>{% linkable_title Where do I start? %}</h4>
<p>This tutorial is based around a heavily commented Jupyter Notebook that we created. So to get started, you will have to open that:</p>
@ -78,7 +78,7 @@ One of the graphs created with this tutorial.
One of the graphs created with this tutorial.
</p>
<h4><a class='title-link' name='whats-next' href='#whats-next'></a> What’s next? </h4>
<h4>{% linkable_title What’s next? %}</h4>
<p>Thanks to the magic of Jupyter, all of the code is customizable: want to selectively display your data, only covering a specific entity? Sure thing! Want to change the properties of the plots? No problem!</p>