Types of Charts and Graphs: Uses, Examples, and How to Choose the Right One

Charts and graphs turn numbers into something people can understand quickly. A spreadsheet may contain hundreds or thousands of values, but the right chart can reveal the important pattern in seconds.

The best chart is not the most attractive or complicated one. It is the chart that makes the main message easiest to understand.

What Is a Chart? How Do I Use It?

A chart is a visual representation of data. Instead of presenting only numbers in rows and columns, a chart uses bars, lines, points, areas, shapes, or colors to make patterns easier to see.

Charts can help answer questions such as which category is largest, how a value changes over time, how a total is divided, whether two variables are related, or where values are concentrated.

What Are the Main Types of Charts and Graphs?

The most common chart families include bar and column charts, line charts, pie and donut charts, scatter plots, histograms, box plots, heatmaps, area charts, treemaps, Sankey diagrams, maps, and specialized business charts.

Each chart type has strengths and weaknesses, so the best choice depends on the data and the message.

The One Question That Will Help You Choose the Right Visualization

Before choosing a chart, ask: What do I want the reader to understand?

This is more useful than starting with the software and picking a design that looks interesting. Once you know whether you are showing comparison, change, distribution, relationship, composition, flow, or geography, the choices become much clearer.

1. Line Charts: Show Change Over Time

A line chart connects data points in order, usually across time. The horizontal axis normally represents time, while the vertical axis shows the measured value.

Line charts are especially useful for tracking trends, showing increases and decreases, comparing several time series, and spotting unusual spikes or drops.

Do not normally connect unrelated categories with a line. Also avoid placing too many series on one chart because the result becomes difficult to read.

2. Bar and Column Charts: Compare Categories

A bar chart compares values across categories using rectangular bars. The length of each bar represents its value. Horizontal bars work well when labels are long, while vertical columns are often convenient when there are only a few categories.

Because people compare bar lengths, the numeric axis should normally start at zero.

3. Pie and Donut Charts: Show Parts of a Whole

A pie chart divides a circle into slices. Each slice represents one part of a total. Pie and donut charts work best when a small number of categories genuinely make up one meaningful whole.

They become difficult to read when there are many slices or when the values are very similar. In those cases, a bar chart often makes comparison easier.

4. Scatter Plots: Reveal Relationships

A scatter plot shows the relationship between two numeric variables. Each point represents one observation.

Scatter plots can reveal positive or negative relationships, clusters, unusual points, and nonlinear patterns. Remember that a relationship does not prove that one variable causes the other.

5. Histograms: Show Distribution

A histogram shows how frequently numeric values fall into ranges. It is useful for seeing the typical range, skewness, multiple peaks, unusual values, and the overall shape of a distribution.

A histogram is different from a bar chart because the bars represent ranges of continuous values rather than separate categories.

6. Box Plots: Compare Distributions

A box plot summarizes a numeric distribution using the median, the middle half of the data, the overall spread, and possible unusual observations.

Box plots become especially useful when you want to compare distributions across several groups rather than compare only their averages.

7. Heatmaps: Highlight Patterns in Dense Data

A heatmap uses color to represent values in a grid. Rows and columns represent categories or ranges, while color intensity represents the value.

Heatmaps are useful when you want to find busy periods, repeated patterns, exceptions, or concentration in large tables.

8. Area Charts

An area chart is similar to a line chart, but the space between the line and the baseline is filled. This makes the size or total more visually prominent.

Stacked area charts can also show how several components contribute to a changing total over time.

9. Bubble Charts

A bubble chart extends a scatter plot by using bubble size to represent a third numeric variable.

Bubble charts can be useful, but area is harder to compare accurately than position or length, so avoid using bubble size when readers need exact comparisons.

10. Treemaps: Show Hierarchical Structure

A treemap uses nested rectangles to show hierarchy and part-to-whole relationships. Rectangle size represents a numeric value while nesting shows parent and child categories.

Treemaps are good for overview and hierarchy, but exact comparisons are usually easier in a bar chart.

11. Sankey Diagrams: Visualize Flows

A Sankey diagram shows movement between categories or stages. The width of each band represents the size of the flow.

It is useful for user journeys, energy flows, budgets, process paths, and other cases where quantities move or split between stages.

12. Network Graphs: Map Connections

A network graph shows connections between entities using nodes and links. It can reveal clusters, central nodes, and relationship structure.

Use a network graph when the connections themselves are the main subject, not simply when you need to compare values.

13. Stacked Bar Charts

A stacked bar chart divides each bar into sections. It can show both a total and how that total is divided among subgroups.

If precise subgroup comparison is more important than the total, grouped bars are often easier to read.

14. Grouped Bar Charts

A grouped bar chart places several bars side by side for each category. This makes it easier to compare individual series directly.

Use grouped bars when individual category comparisons matter more than the combined total.

15. Dot Plots

A dot plot uses points rather than full bars to show values across categories. It can be a clean alternative when the zero baseline is not central to the message.

Dot plots are also useful when many categories need to fit into limited space.

16. Waterfall Charts

A waterfall chart shows how positive and negative changes build from one value to another.

It is useful for profit analysis, budgets, cash flow, financial bridges, and explaining why an ending value differs from a starting value.

17. Funnel Charts

A funnel chart shows values at different stages of a process, such as visitors, leads, proposals, and customers.

Funnel charts are popular in sales and marketing, although a bar chart may be clearer when precise comparison between stages matters.

18. Radar Charts

A radar chart plots several measures around a circular shape. It can give a quick profile of a product, team, or category across several dimensions.

Radar charts become difficult to interpret when there are many dimensions or overlapping series, so grouped bars are often better for precise comparison.

19. Bullet Graphs

A bullet graph compares actual performance with a target. It may also show performance ranges such as poor, acceptable, and strong.

Bullet graphs are useful in dashboards because they communicate goal progress in little space.

20. Gantt Charts

A Gantt chart shows tasks along a time scale. Each task appears as a horizontal bar from its start date to its end date.

Gantt charts are commonly used for projects, construction schedules, software development, product launches, and event planning.

21. Maps and Geographic Charts

Maps are useful when geographic position is part of the question. Common forms include choropleth maps, symbol maps, bubble maps, and point maps.

Do not use a map simply because location is available. Use one when geography helps explain the pattern.

22. Candlestick Charts

A candlestick chart is mainly used in financial markets. Each candlestick can show opening price, closing price, high, and low for a specific period.

For general business reporting, a standard line chart is often simpler.

Showing Shares

When the main goal is to show percentages or shares of a total, use a chart that makes the part-to-whole relationship clear.

Pie and donut charts can work for a small number of categories. Stacked bar charts are usually better when you need to compare shares across several groups.

Showing Absolute Numbers

When the main question is simply how much, a bar chart is one of the safest choices. Bar length is easy to compare accurately.

Examples include sales by product, population by country, orders by store, or employees by department.

Showing Correlations

When you want to understand whether two numeric variables move together, use a scatter plot. Examples include price versus demand, ad spend versus conversions, or study time versus test score.

For very dense datasets, a heatmap or two-dimensional histogram can make concentration patterns easier to see.

Distribution

Sometimes the main question is how individual values are spread rather than which category is highest.

Histograms, box plots, violin plots, and density charts are useful for understanding center, spread, skewness, unusual values, and multiple peaks.

Flows and Relationships

Flow-based charts answer questions about movement or connection. Use Sankey diagrams for flows between stages and network graphs when links between entities are the main subject.

How Do You Choose the Right Charts for Data Visualization?

Choosing a chart becomes easier when you follow the question rather than the software. Start with what you want to show, then match the chart to the structure of the data.

A simple, familiar chart is usually better than a complex design when both communicate the same message.

Choosing Your Chart or Visualization Type

Your chart should also match the variable types and the audience. One categorical variable plus a numeric measure often suggests a bar chart. Time plus a numeric measure often suggests a line chart. Two numeric variables often suggest a scatter plot.

Data structure should guide the design.

Chart vs. Graph: Is There a Difference?

The words chart and graph are often used interchangeably. Some people use graph for visuals built around axes and mathematical relationships, while chart is used more broadly.

In everyday business and data analysis, the terms overlap, so using both naturally is reasonable.

Common Mistakes When Creating Charts

Common problems include using too many colors, adding unnecessary 3D effects, cutting off bar-chart axes, placing too many labels on a chart, and choosing an unusual chart only because it looks impressive.

The chart should help the reader understand the data, not make the reader work harder.

Best Practices for Clear Charts and Graphs

Use a title that explains the message. Label axes clearly. Include units where needed. Keep decoration and grid lines under control. Sort categories when ranking matters. Use consistent colors across related charts.

Most importantly, make sure the chart answers a clear question.

Tables vs. Charts

Use a table when readers need exact values or need to look up individual numbers. Use a chart when the main message lies in a pattern, direction, comparison, or relationship.

Not every dataset needs a graph.

Animated Chart Chooser

The animation below cycles through common questions and the chart type that is usually the best starting point.

Animated WebP: choose the chart based on what you want to show.

Visual Gallery of Common Chart Types

Frequently Asked Questions

Final Thoughts

There are dozens of types of charts and graphs, but most everyday data questions can be answered with a small set of reliable choices.

Use a bar chart to compare categories, a line chart to show change over time, a histogram or box plot to understand distribution, and a scatter plot to explore relationships.

The most important rule is simple: choose the chart that makes the answer easiest to see.

Sources

• • Flourish: Different types of charts
  • Tableau: Charts
  • Atlassian: Essential chart types
  • UNLV Data Visualization Guide
  • ThoughtSpot: Types of charts and graphs
  • Reddit Business Intelligence discussion
  • Datylon: Types of charts and graphs
  • Flourish: Choosing the right visualisation
  • Tableau: Which chart or graph is right for you?
  • eazyBI: Data visualization and chart types
  • Datawrapper: Chart types guide
  • UC Berkeley Data Visualization Guide