How to make sense of the data around?
People love to look at beautifully presented information. Ever so often we come across data and try to extract some meaningful information from that. With so much information available, we also constantly define new ideas and practices to interpret, share or convey the information as best as possible.
I’d like to share some common ways to visualise the data available to you. Let’s get started.
Spreadsheet Software
Almost all spreadsheets softwares and services, for example, Google Sheet, Microsoft Excel and Numbers provide in built support for charts, using which you can generate charts from your data with just a couple of clicks.
A vast amount of external data sources provide data in excel format, like the statistics published by governments. I’d use this method to find some trends and patterns in a preliminary study of the data. The problem with these charts is that you have limited customisation options and the chart follows design language of the spreadsheet software.
Programming Languages
D3.js (for JavaScript), seaborn (for Python), ggplot2 (for R) etc are some of the libraries you can use to generate effective graphs from your data. The amount of customisations we can do on charts with these libraries has no bounds. Personally, for super customised graphs, I’d go with D3.js, and use tools like Adobe Illustrator for final touches.
First and foremost, this requires a knowledge of programming. This is what makes it less approachable to people outside the computer science industry. People working in Data Science find this method more powerful and fit for their needs because of the great level of control and the freedom to invent their own visualisations.
For instance, At VIPERdev, we created ClimateGraph.io to visualise data on climate change. We used plotly.js (JavaScript) to churn out customised visualisation with our branding, in short span of time.
Visualisation Softwares & Tools
Tableau, DataWrapper, RawGraphs, Flourish and Microsoft Power BI provide intuitive interfaces to visualise and analyse data amongst other functionalities. They are used extensively in the corporate world and by data visualisation developers.
These tools have made it possible to create fancy, informative and creative charts without code. The drag and drop interfaces allow you to play with the data and generate graphs using GUI. These powerful tools let the users customisations to their graphs, from custom channels and marks to creating news kinds of visualisation.
Handmade Visualisations
Yes! There are some amazing reading materials (like http://www.dear-data.com/) to learn more and get started with handmade data visualisations. The best part about making such a visualisation is you get a chance to come closer to your data, and use water colours or crayons or literally anything to develop your channel to encode the information.
I find myself using this method all time. Before starting to code in D3.js, I try to sketch the whole visualisation. This method makes it really fast to try out different channels and different encoding strategies and to get feedback on them, before actually starting coding the visualisation.
