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

Use the appropriate tools to bring your chosen visualization to life. For creating simple visualizations, spreadsheet software like Google Sheets or Microsoft Excel might be sufficient. For more advanced visualization techniques, you might need either coding-intensive tools, such as Python (Matplotlib, Seaborn, Plotly.py) or R (ggplot, Plotly.R), or little-to-no coding tools, like Tableau, Looker Studio, and Datawrapper.

Don't forget to check for accuracy and clarity of your visualization. Make sure the data is correctly represented, and the visualization effectively communicates the intended message. Seek feedback from peers or stakeholders if necessary. If you use colors, make sure they are inclusive, especially for colorblind individuals. You can use tools like Color Oracle or Color Brewer to help you refine your visualization's color scheme.

Present and Share

To effectively present visualizations to your audience, it is helpful 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 effectively convey your message but also connect with your audience and support their decision-making.