More URL Updates (#23035)

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@ -19,9 +19,9 @@ This blog post will show you ways to export data for reporting, visualization, o
In this blog post I use the temperature of the [Aare](https://en.wikipedia.org/wiki/Aare) river close to where I live as a show case. The temperatures were recorded with the [Swiss Hydrological Data sensor](/integrations/swiss_hydrological_data) and the name of the sensor is `sensor.aare`.
The database is stored at `<path to config dir>/.homeassistant/home-assistant_v2.db` as [SQLite database](https://www.sqlite.org/). In all examples we are going to use the path: `/home/ha/.homeassistant/home-assistant_v2.db`
The database is stored at `<path to config dir>/.homeassistant/home-assistant_v2.db` as [SQLite database](https://www.sqlite.org/index.html). In all examples we are going to use the path: `/home/ha/.homeassistant/home-assistant_v2.db`
If you are just curious what's stored in your database then you can use the `sqlite3` command-line tool or a graphical one like [DB Browser for SQLite](http://sqlitebrowser.org/).
If you are just curious what's stored in your database then you can use the `sqlite3` command-line tool or a graphical one like [DB Browser for SQLite](https://sqlitebrowser.org/).
The table that is holding the states is called `states`. The `events` tables is responsible for storing the events which occurred. So, we will first check how many entries there are in the `states` table. `sqlite3` needs to know where the databases is located. To work with your database make sure that Home Assistant is not running or create a copy of the existing database. It's recommended to work with a copy.
@ -72,7 +72,7 @@ After the import a graph can be created over the existing data.
Graph in LibreOffice
</p>
You can also use [matplotlib](http://matplotlib.org/) to generate graphs as an alternative to a spreadsheet application. This is a powerful Python 2D plotting library. With the built-in support for SQLite in Python it will only take a couple lines of code to visualize your data.
You can also use [matplotlib](https://matplotlib.org/) to generate graphs as an alternative to a spreadsheet application. This is a powerful Python 2D plotting library. With the built-in support for SQLite in Python it will only take a couple lines of code to visualize your data.
```python
import sqlite3

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@ -26,11 +26,11 @@ One of the graphs created with this tutorial.
_TL; DR: Use [this Jupyter Notebook][nb-prev] to visualize of your data_
[blog post by Fabian]: /blog/2016/07/19/visualizing-your-iot-data/
[DB Browser for SQLite]: http://sqlitebrowser.org/
[Pandas]: http://pandas.pydata.org/
[matplotlib]: http://matplotlib.org/
[DB Browser for SQLite]: https://sqlitebrowser.org/
[Pandas]: https://pandas.pydata.org/
[matplotlib]: https://matplotlib.org/
[Jupyter notebook]: https://jupyter.org/
[nb-prev]: https://nbviewer.jupyter.org/github/home-assistant/home-assistant-notebooks/blob/master/other/DataExploration-1/DataExploration-1.ipynb
[nb-prev]: https://nbviewer.org/github/home-assistant/home-assistant-notebooks/blob/master/other/DataExploration-1/DataExploration-1.ipynb
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@ -19,4 +19,4 @@ Heatmap
[heatmap]: https://en.wikipedia.org/wiki/Heat_map
[Jupyter notebook]: https://jupyter.org/
[nb-prev]: https://nbviewer.jupyter.org/github/home-assistant/home-assistant-notebooks/blob/master/other/DataExploration-2/DataExploration-2.ipynb
[nb-prev]: https://nbviewer.org/github/home-assistant/home-assistant-notebooks/blob/master/other/DataExploration-2/DataExploration-2.ipynb

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@ -10,7 +10,7 @@ og_image: /images/blog/2017-11-hassio-virtual/social.png
---
The images for the Raspberry Pi family and the Intel NUC are an easy way to get started with [Hass.io](/hassio/). For a test or if you have a system which is already hosting virtual machines then the [**Hass.io installer**](/hassio/installation/#alternative-install-on-generic-linux-server) is an option to use Hass.io in a virtualized environment. In this guide the host is a Fedora 27 system with [libvirt](https://libvirt.org/) support and the guest will be running Debian 9. Hass.io will be installed on the guest.
The images for the Raspberry Pi family and the Intel NUC are an easy way to get started with [Hass.io](/getting-started). For a test or if you have a system which is already hosting virtual machines then the [**Hass.io installer**](/installation/) is an option to use Hass.io in a virtualized environment. In this guide the host is a Fedora 27 system with [libvirt](https://libvirt.org/) support and the guest will be running Debian 9. Hass.io will be installed on the guest.
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