Types of charts and when to use them

Choosing a chart is not mainly a design decision. It is a question about what relationship the reader needs to see. A polished chart can still be confusing when its structure does not match the data. A simple chart can be powerful when it makes the intended comparison obvious.

This guide covers 11 useful chart types available in Chart Maker. For each one, you will find its purpose, suitable data, common use cases, limits, and a direct link to the tool.

Chart type selection at a glance

1. Bar chart

A bar chart compares values across separate categories. Each bar represents one category, and its length represents the value. Bars may be vertical or horizontal. Horizontal bars are often easier to read when category names are long.

Best for:

• Comparing products, departments, regions, survey answers, or other named groups.
• Ranking values from highest to lowest.
• Showing a small number of separate time periods.
• Making precise comparisons from a shared zero baseline.

Avoid it when: the horizontal axis is a dense, continuous sequence and the change between adjacent points matters. A line chart usually communicates that pattern more naturally.

Data format: place category labels in the first column and one or more numeric series in the columns to the right.

Practical tip: sort the bars when rank matters, but keep a natural order when categories have one, such as age ranges or stages in a process.

Create a bar chart

2. Line chart

A line chart connects ordered data points. The path makes direction, slope, turning points, and repeated patterns easy to see. Time is the most common horizontal axis, but another continuous sequence such as distance can also work.

Best for:

• Tracking a value by day, month, quarter, or year.
• Comparing trends for several groups across the same periods.
• Showing acceleration, decline, seasonality, or recovery.
• Highlighting the path between measurements rather than isolated totals.

Avoid it when: the labels are unrelated categories. Connecting departments, brands, or survey options suggests a continuity that does not exist.

Data format: put ordered labels or dates in the first column. Add one numeric column for each line.

Practical tip: use consistent intervals. When dates are irregular, explain that clearly because equal visual spacing can otherwise imply equal time gaps.

Create a line chart

3. Area chart

An area chart is based on a line chart, but the space below the line is filled. The fill gives more visual weight to the magnitude of the values. This makes area charts useful when the amount represented by the trend is part of the message.

Best for:

• Showing the volume of a measure across time.
• Emphasizing sustained periods of high or low activity.
• Communicating cumulative change when the underlying calculation supports it.
• Presenting one dominant time series with a strong overall shape.

Avoid it when: several series overlap and hide each other. Multiple lines are usually easier to compare than several opaque areas.

Data format: use the same ordered table structure as a line chart.

Practical tip: check what the baseline means. The filled region attracts attention, so an arbitrary or truncated baseline can exaggerate the visual impression.

Create an area chart

4. Pie chart

A pie chart divides one circle into slices. Each slice represents a category’s share of the total. The full circle has a clear meaning only when all categories belong to the same whole and do not overlap.

Best for:

• Showing a simple budget split.
• Communicating a dominant majority.
• Presenting a small set of vote, traffic, or market shares.
• Giving a quick part-to-whole overview to a general audience.

Avoid it when: there are many slices, negative values, overlapping categories, or several values that are almost the same size. A sorted bar chart handles those situations better.

Data format: put category names in the first column and positive values in the second. Raw values are fine because the chart calculates the shares.

Practical tip: keep the number of slices modest, label them clearly, and avoid 3D effects that distort their apparent size.

Create a pie chart

5. Donut chart

A donut chart uses the same part-to-whole structure as a pie chart but removes the center. The open space can make the chart feel lighter and leave room for a total or short label in designs that support center text.

Best for:

• The same simple composition questions as a pie chart.
• Dashboard cards that pair a breakdown with one headline number.
• Layouts where a ring fits better than a full circle.

Avoid it when: precise comparison is more important than the overall composition. Readers still have to compare angles and arc lengths.

Data format: use one label column and one positive value column.

Practical tip: do not choose a donut only because it looks modern. First confirm that the categories form one meaningful total.

Create a donut chart

6. Stacked bar chart

A stacked bar chart divides each bar into components. The full length represents a category total, while each segment shows how one series contributes to that total.

Best for:

• Comparing totals while keeping their composition visible.
• Showing channel mix across regions or periods.
• Displaying survey response distributions.
• Comparing departmental or project spending categories.

Avoid it when: readers must compare every segment precisely. Only the first segment shares a common baseline, so middle segments are harder to judge. Grouped bars or separate charts may be clearer.

Data format: place the main category in the first column and give every component its own numeric column.

Practical tip: keep the segment order and colors consistent across every bar. Changing them forces the reader to decode the stack repeatedly.

Create a stacked bar chart

7. Scatter plot

A scatter plot places each observation according to two numeric measurements. The horizontal position represents one variable and the vertical position represents the other. The pattern of dots can reveal association, clusters, gaps, and unusual observations.

Best for:

• Exploring whether two continuous variables move together.
• Identifying outliers.
• Finding clusters or separate groups.
• Checking whether a relationship appears linear or curved.

Avoid it when: one axis contains names or unrelated categories. A scatter plot requires meaningful numeric position on both axes.

Data format: each observation needs a pair of numeric values. Keep the units clear in the column names or surrounding explanation.

Practical tip: correlation does not prove that one variable causes the other. Use the chart to identify a pattern worth investigating, not to make an unsupported causal claim.

Create a scatter plot

8. Radar chart

A radar chart places several metrics on axes that extend from one center. Connecting the values creates a profile. Plotting two or three profiles can show broad strengths, weaknesses, and trade-offs across the same criteria.

Best for:

• Comparing products across the same feature scores.
• Reviewing skills or performance dimensions.
• Showing a small number of high-level profiles.
• Communicating an overall shape rather than exact values.

Avoid it when: the audience needs precise metric-by-metric comparison, the axes use incompatible scales, or too many profiles overlap. Grouped bars are often better for exact reading.

Data format: place metric names in the first column and one numeric column for each subject.

Practical tip: keep every metric pointing in the same direction. If a high value means good on one axis and bad on another, transform or explain the scale before comparing shapes.

Create a radar chart

9. Funnel chart

A funnel chart shows a quantity moving through sequential stages, usually from a large starting group to a smaller final group. The narrowing shape draws attention to retention and drop-off.

Best for:

• Sales pipelines.
• Signup and onboarding flows.
• Recruiting stages.
• Checkout or order completion.

Avoid it when: categories are not sequential, people can enter midway, stage definitions use different time windows, or values do not represent the same population moving through a process.

Data format: list stages in process order and enter the count remaining at each stage.

Practical tip: pair the chart with stage-to-stage and overall conversion rates. Width alone does not tell the reader whether a drop is acceptable or where action is needed.

Create a funnel chart

10. Gauge chart

A gauge chart places one current value within a defined range. It resembles a dial, making it familiar in dashboards and status reports. The chart becomes meaningful only when the range, target, and thresholds have clear definitions.

Best for:

• One headline KPI.
• Progress toward a target.
• A current reading with known acceptable limits.
• A compact status display for a nontechnical audience.

Avoid it when: several values need comparison. Multiple gauges use a lot of space and make relative differences difficult to judge. A bar chart or scorecard is usually more efficient.

Data format: use one value and a title that states the metric and unit.

Practical tip: do not add red, yellow, and green zones unless their boundaries come from real business rules.

Create a gauge chart

11. Gantt chart

A Gantt chart places project tasks on a calendar. Each horizontal bar spans a start and end date. The layout shows timing, overlap, ownership, and schedule gaps.

Best for:

• Project planning.
• Campaign and event schedules.
• Product launches.
• Research, construction, and software timelines.
• Coordinating work across people or phases.

Avoid it when: the main question is task priority, workload balance, or detailed dependencies that the chart does not display. A task board, capacity table, or dedicated project system may be more suitable.

Data format: every task needs a name, start date, and end date. Optional parent tasks and assignees add useful structure.

Practical tip: break long phases into specific outcomes, leave room for uncertainty, and review the dates with the people responsible for the work.

Create a Gantt chart

How to choose between similar chart types

Bar chart vs. line chart

Use a bar chart when the labels are separate categories. Use a line chart when the horizontal axis has a meaningful continuous order and the change between neighboring points matters. Read the full bar chart vs. line chart comparison.

Pie chart vs. bar chart

Use a pie chart to emphasize that a few values form one whole. Use a bar chart for accurate ranking, close values, negative numbers, or many categories. Read the full pie chart vs. bar chart comparison.

Line chart vs. area chart

Both show an ordered trend. Choose a line when direction and precise comparison are most important. Choose an area chart when the magnitude beneath the trend deserves stronger emphasis.

Bar chart vs. stacked bar chart

Use a regular bar chart to compare standalone values. Use a stacked bar chart when readers need to see both each category total and the components inside it.

Six rules that improve almost every chart

1. Write the question first. A chart should answer one clear question rather than display every available field.
2. Name the subject, measure, and time period. A title such as “Monthly revenue by channel, 2026” is more useful than “Sales chart.”
3. Include units. Readers should not have to guess whether values represent dollars, percentages, people, seconds, or thousands.
4. Use color to encode meaning. Repeated colors should represent repeated concepts. Decorative color changes can imply categories that do not exist.
5. Keep text readable after export. Review the PNG or SVG at the size where it will appear in a slide, document, or webpage.
6. Choose a table when lookup is the real task. Charts reveal patterns. Tables are often better when readers need exact values for many items.

What if your data needs a different chart?

Some datasets call for chart types that Chart Maker does not currently provide. A histogram is useful for a numeric distribution, a box plot summarizes quartiles and outliers, a map emphasizes geography, and a Sankey diagram shows flows between sources and destinations. Do not force that data into an unrelated chart just because the tool is available. Choose the structure that communicates the relationship honestly.

If one of the supported types fits your question, open the free chart maker, import CSV or Excel data, customize the result, and export it as PNG or SVG.