In this tutorial, you will learn how to build an interactive data visualization using geospatial data. We will cover a wide range of technologies: Pandas for cleaning the data, Flask for building the server, Javascript libraries d3.js, dc.js and crossfilter.js for building the charts and Leaflet.js for building the map.
In this blog post, I will introduce the building blocks for creating a simple IoT application. To do this, I will use an Arduino microcontroller with a photocell (light intensity sensor), a node.js server for capturing and transferring the data, and a cloud service called plotly to visualise the data. By the end of this tutorial, we will have a functioning IoT application that you can customise to other use-cases.
Step by step tutorial for building an interactive data visualization dashboard using a dataset from DonorsChoose.org. This tutorial introduces a range of technologies: MongoDB for storing and querying the data, Python for building a web server that interacts with MongoDB and serving html pages, Javascript libraries d3.js, dc.js and crossfilter.js for building interactive charts.