09-07, 11:55–12:30 (Europe/Lisbon), Auditorium
Data science projects are often characterized by visualizations which
enhances the creative storytelling process and allow us to derive actionable
insights from data. This is enabled through the use of good visualization tools/libraries which enable us to present data in a manner that is interactive and is easily understandable. Often, the action in itself tends to be more significantly remembered by the audience in comparison to static insights. This inturn
calls for the need for using interactive dashboards as a way to present the data.
Currently, the plethora of tools available for this purpose often makes it a tedious task to decide which is the best fit. Often the choice oscillates between learning to use explicit dashboarding tools or using existing python libraries which may allow visualizations but not necessarily dashboarding.
Apart from the cost associated with some of these explicit dashboarding tools, there might also be a learning curve associated with it.
Therefore, in this talk, I would like to take you through a simple pythonic approach of building dainty dashboards using Plotly Dash in python to ease the process of data exploration and allow for interactive visualizations that enable creative storytelling.
In this talk, we would be looking at Plotly Dash as an interactive dashboarding tool for data exploration through creative and informative visualizations. Familiarity with python would be a pre-requisite. The format of the talk is informative and hands-on. We would be creating a dashboard along the way following the learning by doing approach. We would be using an open source healthcare dataset available online for the purpose of creating these visualizations. Further we'll cover the following topics:
1. Introduction: A bit about Plotly Dash and why you should use it.
2. Taking First steps: Exploring functions for loading data.
3. Boilerplate code for our Dash app.
4. A bit about Dash Core Components.
5. Diving into visualizations - Adding various figures, charts, graphs to our dashboard.
6. Experimenting with dashboard layouts.
7. Interaction between app components: Looking at callback functions.
8. Finally, hosting the app for the world to see!
I am currently working as a Data Engineering Professional at Novo Nordisk. I am inspired by the advancing developments in making computers imitate and understand human language, vision, and intelligence and passionate about building tech that adds value to society.