Choosing the Right Chart: A Practical Guide to Accurate Data Visualization

01 Bar Chart

Bar charts are reliable for data that evolve over time or are grouped by multiple categories (e.g., industries or products). To keep them readable, arrange bars in chronological order, avoid sorting purely by value, and consider stacked or grouped layouts when multiple categories share the same time label.

When data are grouped by category without a time dimension, sorting from high to low can help draw quick conclusions, but for aggregated totals (e.g., overall revenue) a bar chart may be less effective, and a pie chart might be preferable.

Example: a Bluetooth interaction report uses stacked bars to compare yearly data across categories.

02 Line Chart

Line charts excel at showing trends over time or grouped categories, allowing fine‑grained detail. They are ideal for long time spans or data with many incremental changes because the line can bend smoothly to reflect subtle variations.

Be cautious when the dataset contains only a few time points; interpolating between them may mislead if the actual growth is non‑linear. Use complete data to avoid distortion.

Allen Downey’s study on birth timing illustrates a well‑constructed line chart based on over 30,000 data points, capturing the full distribution of probabilities.

03 Pie and Donut Chart

Pie (solid) and donut (hollow) charts are among the most common visualizations but are also frequently misused. Use them only when the parts sum to a whole (e.g., "75% of caterpillars prefer apples").

They cannot convey growth or decline trends; for example, a 99% increase in YouTube video views should be shown with side‑by‑side bars rather than a single 99% pie slice.

04 Pictogram (Quantity Chart)

Pictograms use repeated icons to represent quantities, making them effective for small numbers (e.g., "12 new restaurants on the street"). For larger figures, scale the icon (e.g., one bag = 1,000 items) or switch to typographic presentation, as displaying thousands of icons is impractical.

05 Typography

When data are large (over 100), not percentages, and independent, typographic design can be the best solution. Large numbers or isolated statistics often convey more impact as plain text than as a crowded visual.

Enhance typographic displays by pairing them with a single icon or illustration to provide contextual cues without overwhelming the viewer.

Overall, choose the visualization form that matches the data’s nature and audience expectations; a beautiful but confusing chart is merely abstract art.