Data Visualization Tips to have a long-lasting Impact on Your Audience

Let’s start with the Bar Chart

Anmol Tomar

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Why is Data Visualization a critical skill?

Data visualization is an art; mastering it involves more than just creating plots. Today, we’re diving into the hidden gems of data visualization — the tips that often lurk in the shadows, unknown to many professionals but are very critical for creating impactful visualizations.

In this series of blogs, we will start with the Bar chart which is one of the most used — simple yet effective visualizations out there and yet used in the wrong setup many times.

Fundamentals: What is a Bar chart and when to use it?

A bar chart is used to compare & show the difference between different categories where one axis is categorical and the other is continuous (numeric).

A bar chart can be used to compare and find the largest and smallest category. For example — comparing the Medical Spending across different age groups (Millennials, GenZ, Young, etc.)

Bar chart (Image by Author)

1. The Power of Width

Tip: Optimal Bar Width for Impact

Bar charts are a staple in data visualization, but the width of those bars can make a significant difference. The key is finding the sweet spot — not too thin that bars get lost in the background, and not too wide that they clutter the visual space.

The image below illustrates the ideal/perfect width of the bar and highlights what too thin and too wide looks like.

Width of Bar graphs(Image by Author)

2. Multiseries chart

Multiseries bar charts, also known as grouped bar charts, are a powerful way to compare multiple categories across different groups. When dealing with complex datasets involving multiple series, these charts offer clarity and depth to your visual narrative.

Let’s explore some best practices to ensure you wield the multi series bar chart with finesse and create visual brilliance.

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Anmol Tomar

Top AI writer | Data Science Manager | Mentor. Want to kick off your career in Data Science? Get in touch with me: https://www.analyticsshiksha.com/