I will make a dashboard to give an overview of the refills for the car using MEAN.JS and D3.js.

A simple description how to use R and Python to interact in a Jupyter notebook.

My first experience with MongoDB. I will install MongoDB and Pymongo, insert some data and query it. Next step will be to tryout monary, but for this notebook it is out of scope.

My first experiment using the NLTK library of Python

Inspired by this tutorial I tried to continue investigating Elasticsearch since I would like to use a fast indexing tool for the data I am gathering and the applications I am developing.

As a training for myself to get more familiar with image classification and OpenCV I followed the tutorial on http://www.pyimagesearch.com/2014/08/04/opencv-python-color-detection/. I modified it slightly to fit my environment.

In my previous post on testing in Python I explained how to test in a Jupyter Notebook. Now a few weeks later I need to get familiar with mocking in Python. Since this is a new concept for me I made a small notebook testing different functionalities of the mocking library.

Unittesting in a Jupyter notebook

To add some custom style to your dashboard, you can create a cascade stylesheet in your app folder and overrule the standard dashboard lay-out.

In this short tutorial I will create a Splunk app to monitor the webserver. We will create the bare-bone app and we add a few panels to the dashboard.