Data Visualization Guide

Define Your Goals

The first step in data visualization is understanding the purpose of your visualization. Determine what message you want to convey, who your audience is, and what decisions or actions they will take from the information presented.

Also, consider where the visualization will be published. Printed media can only accommodate static visualizations, while videos, websites, and social media can include either dynamic or interactive visualizations in addition to the static ones.

Explore, Analyze, and Understand Your Data

An exploratory analysis is helpful in understanding the characteristics of your data. Look for patterns, trends, correlations, and any outliers.

Descriptive statistics and hypothesis testing can also provide valuable insights into your data.

Choose and Design Your Visualization

The most appropriate visualization depends on your goal and data type.

Refer to this link to help you choose which visualization is most appropriate for your project.

Create and Refine Your Visualization

Once you decide on a visualization, use the right tools to bring it to life. Spreadsheet software like Google Sheets or Microsoft Excel might be sufficient for generating basic visualizations. For more advanced techniques, you might need other tools that require coding skills, such as Python (Matplotlib, Seaborn, Plotly.py) or R (ggplot, Plotly.R), or those that require little to no coding skills, like Tableau, Looker Studio, and Datawrapper.

Don't forget to evaluate your visualization for accuracy and clarity. Ensure the data is correctly represented, and the visualization effectively communicates the intended message. Seek feedback from peers or stakeholders. If you use colors, ensure they are inclusive, especially for colorblind individuals. Tools like Color Oracle or Color Brewer can help you refine your visualization's color scheme.

Present and Share

To effectively present visualizations to your audience, it is beneficial to provide background information and annotations, highlight key insights, and guide your audience through the data narrative for better comprehension. 

By following these guidelines, you can create, present, and share impactful data visualizations that not only convey your message effectively but also resonate with your audience and help them make informed decisions.