TL;DR: Poor chart design can distort insights and confuse users. This guide shares 12 actionable tips and best practices to make your charts clear, accurate, and user-friendly. Learn how to choose the right axis type, optimize labels, manage legends, reduce clutter, and enhance interactivity, especially for .NET MAUI charts. Apply these techniques to create dashboards and apps that effectively communicate data.
Welcome to the Chart of the Week blog series!
Great charts don’t just display data; they tell a story. The difference between confusion and clarity often comes down to small design choices, such as selecting the right chart type, making axis labels readable, and ensuring that interactive elements actually assist users. These details collectively have a significant impact.
This guide highlights some of the most common charting mistakes, each illustrated with clear before-and-after visuals. You won’t need any code to follow along: just practical examples and quick fixes you can recognize and apply right away.
With these actionable tips, you’ll be able to create charts that communicate your insights more effectively and give users a much better experience.
Let’s see how it’s done!
Visual challenges in chart UI design and how to overcome them
1 Plot numbers on a numeric axis
Scenario and impact:
Imagine you plot values like 2, 5, 20, and 21. If you use a category axis, each value gets the same spacing on the axis. The big jump from 5 to 20 appears to be the same distance as the tiny step from 20 to 21, creating a false sense of uniform progression. This can mislead readers about how quickly values change and by how much.
Solution:
Use a numeric axis so spacing reflects real values. For example, gaps between 5 and 20 will appear wider than 20 and 21, showing true trends. Add clear tick marks (0, 5, 10, 15, 20, 25) and choose line or scatter charts for continuous numeric data. Reserve category axes for names or labels like products or regions.
2 Use bars to compare categories
Scenario and impact:
Suppose you visualize customer ratings for three products: Alpha, Beta, and Gamma. If you draw a line between these categories, it looks like there is a smooth path from Alpha to Beta to Gamma. That suggests a continuous trend, as if moving along time or a number scale. But these are separate items, not a sequence. The line can trick readers into thinking there is momentum or change over “steps” that don’t exist.
Solution:
Use Columns or bars so each category stands on its own with a shared baseline. This makes comparisons clear and honest. For compact views, consider a dot plot. Reserve line charts for continuous data such as time or numeric sequences.
3 Keep axis labels clear and readable
Scenario and impact:
Picture a chart displaying daily data for an entire month, with all 31 dates crammed onto the x-axis, labels overlap and blur into an unreadable mess.
Solution:
Display fewer labels (e.g., every 5th date), rotate text slightly, or use short formats like “Jan 15.” For dense data, enable zoom and pan or switch to a horizontal bar chart for long names.
Reference: For more details on handling overlapping axis labels in .NET MAUI Cartesian Chart, refer to the KB article.
4 Use a datetime axis for time intervals
Scenario and impact:
Consider a chart showing website visits on Jan 1, Jan 2, Jan 15, and Feb 1. If the axis treats dates as labels, the large gap between Jan 2 and Jan 15 appears identical to the one-day gap between Jan 1 and Jan 2. This makes patterns over time hard to interpret, and zooming or panning jumps from label to label instead of moving smoothly through days and weeks.
Solution:
Use a DateTime axis so spacing reflects actual time intervals. Choose the right granularity (days, weeks, or months) and let the chart handle missing dates as empty space. Labels format consistently (like Jan 1, Jan 8, Jan 15), and navigation feels natural when you zoom or pan. Pick the right time grain (days, weeks, or months), and let the chart handle missing dates as empty space rather than squeezing them together.
5 Show bars from zero to avoid misleading differences
Scenario and impact:
Imagine a bar chart comparing two months of sales: 500 and 520 units. If the y-axis starts at 480 instead of zero, the 20-unit difference looks huge because the bars fill most of the axis range. Readers may think sales jumped dramatically when they barely changed. This distorted baseline can lead to wrong decisions and loss of trust.
Solution:
Always start the value axis at zero for bar and column charts so bar length matches the true size of each value.
6 Reduce label noise; keep the trend visible
Scenario and impact:
Picture a line chart tracking daily temperatures for 90 days. If every point is labeled, the text overlaps and hides the line, burying the trend under a wall of numbers. On mobile, it becomes almost impossible to read. Viewers struggle to see patterns or find the latest value.
Solution:
Show only the labels that matter such as the latest value, highs and lows, or notable peaks and dips, so the line stays visible. Provide full details on demand with tooltips or a trackball when users hover or tap. Keep simple markers for unlabeled points, so the chart remains clean while the details are still easy to access.
For more details, see our guide on showing data labels for selected points in a MAUI Cartesian Chart.
7 Use a trackball to compare multiple series instantly
Scenario and impact:
Think of a chart with three lines plotted across months. If you hover normally, the tooltip jumps to whichever point is closest. You have to move the mouse between lines to read each value, tooltips flicker, and it’s even harder on touch screens. Comparing the values for the same month becomes slow and frustrating.
Scenario and impact:
Think of a chart with three lines plotted across months. If you hover normally, the tooltip jumps to whichever point is closest. You have to move the mouse between lines to read each value, tooltips flicker, and it’s even harder on touch screens. Comparing the values for the same month becomes slow and frustrating.
8 Use separate axes for different units
Scenario and impact:
A weather chart showing monthly rainfall (mm) and average temperature (°C) on the same y-axis distorts one series. For example, rainfall values like 120 mm, 60 mm, and 10 mm overshadow temperature values of 12°C, 18°C, and 25°C, making the temperature line look flat or rainfall bars overwhelming. This misleads viewers and hides real patterns.
Solution:
Use a secondary axis, with rainfall on the left and temperature on the right, each clearly labeled with its unit. Combine bars for rainfall and a line for temperature for quick visual distinction.
Reference: For more details, see our guide on simplifying data visualization with multi-axis charts in .NET MAUI.
9 Keep axis labels consistent in format and units
Scenario and impact:
A weather chart with y-axis values like -5, 0, 10, 20, but no units leaves readers guessing—Celsius or Fahrenheit? On a cold day, -5 might look extreme or mild depending on what the viewer assumes. Misinterpretation erodes trust and accuracy.
Solution:
Show the unit clearly as Celsius. Add an axis title like Temperature (°C) and format every label consistently, so readers know at a glance that all values are degrees Celsius.
Reference: For more details, see our guide on customizing axis labels using the LabelStyle property in .NET MAUI Charts.
10 Managing overloaded legends
Scenario and impact:
A multi-series line chart with a stacked legend on the right shrinks the chart area and forces readers to match colors by constant eye movement, especially hard on small screens. Readers keep glancing back and forth to find which color belongs to which line and lose the main story.
Solution:
Move the legend to the bottom for better space usage. Allow toggling series on/off and hide less important series by default for a cleaner first view. Keep colors distinct and labels clear.
Reference: For more details, see our guide on aligning chart legend items in .NET MAUI Circular Charts.
11 Limit pie slices for clear comparison
Scenario and impact:
A pie chart with 20 categories creates tiny slices, overlapping labels, and repeated colors. It’s hard to identify major contributors, and selecting small slices is frustrating. The chart looks busy but fails to answer the key question: which items contribute the most?
Solution:
Show only the key slices in the pie, keep the top contributors visible, and group the rest into “Other”. Alternatively, add a sorted column chart underneath to show the full ranking clearly. The pie series provides a quick sense of composition, while the column chart makes precise comparisons easy. Use distinct colors for the main slices and let tooltips provide exact values when needed.
Reference: For more details, see our guide on grouping small data segments in .NET MAUI Circular Charts.
12 Keep pyramid flow and totals consistent
Scenario and impact:
A funnel chart showing Visitors 34%, Signups 20%, Trials 22%, Qualified 14%, Purchases 10% breaks the expected flow because Trials exceed Signups, confusing viewers.
Solution: Keep one clear flow from top to bottom and size each slice to match its value. For example, “Visitors 45%, Signups 27%, Trials 14%, Qualified 9%, Purchases 5%” makes it obvious these are percentages of the total.
Note: For the non-linear flow data, we can change the mode of pyramid to Surface. In the Surface mode, the area of the segment is based on the value.
Conclusion
Thanks for reading! This blog explored the most impactful chart design pitfalls and the simple fixes that lead to clearer, more trustworthy visualizations. Whether you’re building dashboards, reports, or data‑driven apps, these practices help you present information that’s easy to read and act on.
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This article was originally published at Syncfusion.com.
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