Different types of graphs and when to use them.
Learn about the different types of graphs you can use and how they can help you visualise different data sets.
You’ve collected your data and it’s ready to go, but deciding how best to present it is equally important. How you visualise your gathered information will help you understand the relationships between data points and interpret their meaning. In turn, this makes data easier to understand for readers, bridging the gap between the information you’re presenting, and its practical value.
In this helpful guide, we’ll explore the different types of graphs and when to use them. Whether you’re torn between scatter graphs, line graphs or charts, read on to learn more about each type and what they’re best used for.
1. Bar charts.
A bar chart is a great choice if you want to compare different categories of data – for example, population by region or sales by product. It displays this data using colour-coded bars that reach either horizontally or vertically. Because of this side-by-side data visualisation, bar charts are ideal for comparing more discrete data across different groups.
When creating a bar chart, it’s a good idea to make sure spacing is consistent, and to keep the number of bars to a necessary minimum. This avoids cluttering the space with too much information, and makes data easier to compare.
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2. Line graphs.
A line graph helps you visualise how data changes over time, making it one of the most useful types of graphs to represent data across different dates and points. It’s best used when tracking data trends, such as revenue or temperature, for example. Although there are no strict rules as to when to use a line graph, they’re a great fit for representing continuous data and analysing time-based patterns.
To keep your line graph clear and easy to navigate, use distinct colours and try to avoid too many overlapping lines and data points.
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3. Pie charts.
A pie chart is best used to illustrate how a whole is divided into parts – for example, showing how a company’s budget is split across departments. With this in mind, it’s useful when you need to visualise proportions or percentages. However, when comparing the different types of graphs you can use, a pie chart works better when working with simpler datasets with fewer categories.
A pie chart is a great graph to use for part-to-whole comparisons. Just make sure to avoid cramming in too many slices to keep things clear and effective when creating one.
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4. Doughnut charts.
A doughnut chart is similar to a pie chart but with a blank centre, making it easier to compare multiple data series or to add more information, metrics and labels in the middle. It’s a good choice if you want to illustrate proportions within your data, like market share by brand or how time is divided across a project’s different tasks. Among the different types of graphs and charts, doughnut charts are great for part-to-whole comparisons with added visual clarity.
When creating your doughnut chart, limit the number of categories to around five to seven segments to keep things clear and easy to interpret.
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5. Tree maps.
A tree map displays hierarchical data using nested squares and rectangles to represent smaller parts of a greater whole, making it great for comparing proportions within categories. For example, you could use a tree graph to visualise business budget by department or website traffic by source.
The size and colour of each rectangle represent different data values, with the size often being proportional. With this in mind, keeping the colour key straightforward and easy to use is important when building out tree maps.
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6. Scatter plots.
A scatter plot shows the relationship between two variables using dots plotted on the X and Y axes. It’s great for spotting correlations or trends, such as the link between study time and test scores. Among the different types of graphs, scatter plots are ideal for showing patterns in data and detecting any outliers in your dataset.
A key tip is to add a clear trendline to highlight correlations and detect any major outliers.
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7. Histograms.
A histogram is similar to a bar chart, but groups data into ranges and focuses on displaying continuous information. This makes it perfect for showing the distribution and frequency of numerical data, like exam scores or ages. It essentially helps you understand how data spreads across intervals.
When creating your histogram and compiling the relevant data, make sure to choose your intervals carefully for more accurate insights.
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8. Heat maps.
A heat map uses colour gradients to represent data intensity across two dimensions, helping you quickly identify patterns or hotspots. It’s ideal for visualising data like website clicks, sales by region, or customer activity. When deciding what graph to use for showing density or concentration, heat maps provide a clear and intuitive view.
Because heat maps often use quite a high volume of data to visualise patterns, it’s a good idea to keep the colour coding clear and consistent.
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How to make the most out of these graph examples.
How can Adobe Express help you create your own graphs?
Whether you’re compiling graphs for work, school or even a personal project, you want to make sure they’re formatted clearly and consistently. With Adobe Express, you can explore hundreds of free templates and editing tools to ensure you’re creating an effective graph that’s perfect for your needs.
1. Make a graph from scratch.
You can create your graph from scratch using free Adobe Express templates. Build up your elements, add axes, bars, plots, lines, tags – anything you need to help visualise your information.
2. Edit free graph templates.
If you don’t know how to get started, browse a huge library of graph and chart templates. From Bar chart to pie charts and scatter plots, find the right fit for your data.
3. Customise a line graph with your own data.
Once you’ve found the template you’re happy with and you’ve got the foundations down, customise it with your own data. Tweak the display, design your lines, perfect your colour key, and get it ready to share.
4. Design your own pie chart.
If you’re looking for a simpler way to display your data, a pie chart is the way to go. Choose your template, add your data, and customise your colours in just a few clicks.
Present your own graphs, charts and more with the AI presentation maker.
Once you’ve built your chart, it’s time to share it. The best way to do that is in a presentation – especially if you’ve collected the data for a work or school project. With Adobe Express’ AI tool, you can create a stunning presentation in a few seconds. Simply create your prompt, provide some background information, and watch as the perfect presentation template is created. Edit until it’s ready to go, and save and share it however you like.
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