How can you use R to win data visualization contests?

1 Know your tools

R has a rich ecosystem of packages and libraries that can help you create various types of data visualizations. Some of the most popular ones are ggplot2, plotly, leaflet, shiny, and rmarkdown. You should familiarize yourself with these tools and learn how to use them effectively. For example, ggplot2 is based on the grammar of graphics, which allows you to build plots layer by layer using different aesthetics and geometries. Plotly can help you create interactive and web-based graphics that can be embedded in websites or dashboards. Leaflet can help you create dynamic maps with custom markers and layers. Shiny can help you create interactive web applications that can take user inputs and display outputs. Rmarkdown can help you create reports and documents that combine code, text, and graphics.

2 Know your data

Before you start visualizing your data, you should explore and understand it. You should know what variables and values are in your data, how they are distributed, how they are related, and what insights or patterns they reveal. You should also clean and transform your data if needed, such as dealing with missing values, outliers, errors, or inconsistencies. You can use various R functions and packages to help you with data exploration and manipulation, such as dplyr, tidyr, lubridate, stringr, and forcats. You should also use descriptive statistics and visual summaries, such as histograms, boxplots, scatterplots, and correlation matrices, to get a sense of your data.

3 Know your audience

When you create a data visualization, you should keep in mind who your audience is and what they want to know. You should tailor your visualization to suit their needs, interests, and expectations. You should also consider the context and purpose of your visualization, such as whether it is for education, persuasion, entertainment, or exploration. You should choose the appropriate type and style of visualization that can communicate your message clearly and effectively. You should also use colors, fonts, labels, legends, titles, and annotations that can enhance your visualization and make it easy to read and understand.

4 Know your story

A data visualization is not just a collection of shapes and colors, but a way of telling a story with data. You should have a clear and compelling story that you want to tell with your visualization, such as a problem, a solution, a trend, a comparison, or a discovery. You should use your data and visualization to support your story and highlight the main points and findings. You should also use narrative techniques, such as hooks, transitions, climax, and resolution, to engage your audience and guide them through your story. You should also use interactivity, animation, or annotation to add depth and detail to your story.

5 Know your feedback

One of the best ways to improve your data visualization skills and win contests is to get feedback from others. You should seek feedback from different sources, such as your peers, mentors, experts, judges, or users. You should ask for constructive and specific feedback, such as what works well, what can be improved, what is confusing, or what is missing. You should also be open and receptive to feedback, and use it to refine and polish your visualization. You should also give feedback to others, as this can help you learn from their strengths and weaknesses, and build your network and reputation.