How to work with Jupyter notebook
In this article, you will learn how to use Jupyter Notebook to analyse data persisted in the Quix platform
Although Quix is a realtime platform, to build realtime in-memory models and data processing pipelines, we need to understand data first. To do that, Quix offers a Data catalogue that makes data discovery and analysis so much easier.
You’ll need some data stored in the Quix platform. You can use any of our Data Sources available in the samples Library, or just follow the onboarding process when you sign-up to Quix.
You will also need Python 3 environment set up in your local environment.
python3 -m pip install jupyter python3 -m pip install requests python3 -m pip install pandas
The Quix web application has a python code generator to help you connect your Jupyter notebook with Quix.
Go to the platform
Go to the Data catalogue
Select data to visualize
Select parameters, events, aggregation and time range
Press Connect button
Select Python language
Copy Python code to your Jupyter notebook and execute.
|If you want to use this generated code for a long time, replace the temporary token with PAT token. See authenticate your requests how to do that.|
If you find that the query results in more data than can be handled by Jupyter Notebooks try using the aggregation feature to reduce the amount of data returned.
For more info on aggregation check out this short video.