Ever found yourself swimming in a sea of data, feeling like you’re drowning in numbers and text? Let’s throw you a lifeline—the right types of charts can turn that overwhelming data ocean into a navigable waterfront park.
Navigating through information visually allows for smoother sailing in understanding complex data, whether for business decisions, academic research, or personal curiosity.
Set sail with me as we chart the course of this article; consider it your compass to the art of visual data storytelling.
You’ll uncover the secrets to picking the perfect chart that makes your audience nod in enlightened agreement instead of scratching their heads in confusion. From the clear structure of bar graphs to the intuitive elegance of pie charts and beyond, you’re about to become a connoisseur of chart selection.
By this article’s end, you’ll not only recognize a scatter plot from a histogram but also know exactly when to use each to make your message stand out. Onwards, to a land where ‘Data Analysis’ and ‘Infographics’ are not just buzzwords but trusted allies in your quest for clarity.
Table of Contents
The Different Types of Charts
| Chart Type | Primary Use Case | Data Visualization Characteristics | Typical Data Used For | Limitations/Notes |
|---|---|---|---|---|
| Bar Chart | Comparing categories | Length of bars represent value | Categorical data | Not ideal for time series or many categories |
| Line Chart | Time series trends | Points connected by lines show change over time | Sequential data | Can be cluttered with too many variables |
| Pie Chart | Proportions/percentages | Circular chart divided into sectors | Part-to-whole relationships | Not for comparisons, bad with many slices |
| Scatter Plot | Relationship between variables | Dots represent value pairs | Bivariate quantitative data | Less effective for categorical data |
| Histogram | Distribution of numerical data | Bars represent frequency of data in intervals | Continuous data | Cannot show developments over time |
| Area Chart | Cumulative trends | Filled area between line and axis, stacked possible | Sequential data, part-to-whole | Can be hard to read if stacked |
| Box Plot | Statistical distribution | Visual summary of data quartiles and outliers | Quantitative data | Not for detailed distribution analysis |
| Bubble Chart | Multivariable relationships | Dots with size variation | Tri-variate data | Can get cluttered, hard to read |
| Stacked Bar Chart | Sub-category comparison | Bars divided into sub-bars stacked on top of each other | Part-to-whole for categories | Can be complex with too many stacks |
| Heat Map | Data density and patterns | Color-coded values | Matrix data, comparisons | Not precise for individual value reading |
| Radar Chart | Multivariate comparison | Axes emanating from center for each variable | Comparable quantitative variables | Confusing with too many variables/spikes |
| Treemap | Hierarchical data | Nested boxes of varying sizes and colors | Hierarchical, part-to-whole | Hard to track once segmentations grow |
| Gantt Chart | Project timelines | Horizontal bars against time axis | Schedules, milestones | Mainly for project management |
| Waterfall Chart | Sequential changes | Connected bars showing positive and negative changes | Financial statements, inventory | Mainly for financial or inventory analysis |
| Sankey Diagram | Flow quantity | Width of arrows proportional to flow quantity | Energy, material, cost flows | Requires good data structuring |
| Bullet Chart | Performance against target | Bar with performance marks and target | Performance metrics | Limited to simple performance tracking |
| Pyramid Graph | Hierarchical relationships, often demographics | Triangular chart with sections | Population structures, processes | Limited to processes with a clear hierarchy |
| Venn Diagram | Set relationships | Overlapping circles to show commonality | Statistical, probabilistic data | Overlapping only effective for a few sets |
| Pictograph | Representing data with icons | Icons to represent data values | Education, simple comparisons | Not for complex or precise data |
| Cartesian Graphs | Plotting mathematical functions, relationships | X and Y axes with points or lines | Mathematics, science data | Requires understanding of xy-coordinate system |
| Dot Plot | Comparing frequency or count | Dots represent quantities | Comparative discrete data | Less informative for continuous data |
| Organizational Chart | Displaying hierarchies | Diagram showing structure of an organization | Corporate or group structures | Not for data analysis, just structure |
| Dual Axis Chart | Comparing two variables with different scales | Two different Y axes for different data scales | Two distinct data types | Can mislead if scales are not labeled carefully |
| Flow Chart | Processes or workflows | Diagram with steps in a process | Decision paths, processes | Can become complex with many steps |
| Spline Chart | Smooth trends | Curved lines connecting data points | Sequential data with smooth trends | Can mislead as it implies smoothness between points |
| Mekko Chart | Market data proportions | Bar widths and heights represent different relationships | Market segmentation data | Complex and hard to read |
| Gauge Charts | Data within a predetermined range | Semi-circular or circular dial | Performance against a goal | Limited data representation per chart |
| Funnel Chart | Process stages and completion rates | Truncated cone, each segment a process stage | Sales pipeline, conversion rates | Difficult with too many stages |
Bar Chart
Chart created with wpDataTables
A bar chart is your visual shot of espresso for comparison between different groups or categories. Each bar’s height or length varies according to its value, straight up showcasing differences in a way that’s easy to grasp.
What to use it for:
- Comparing product sales
- Showing survey results
- Tracking changes over time with different groups
Tips for creating one:
- Label your axes clearly
- Use contrasting colors for different categories
- Keep it simple; avoid cluttering with too much text
What we like about it: The simplicity – it’s the classic, clear-cut choice when you want immediate comparisons without the frills.
Line Chart
Chart created with wpDataTables
Imagine your data points holding hands across a page; that’s your line chart. It’s about watching trends and changes over time, with a line that flows across the data points, often revealing patterns you might miss in a table.
What to use it for:
- Monitoring stock market trends
- Tracking website traffic over months
- Comparing performance metrics over time
Tips for creating one:
- Keep your line paths smooth
- Highlight significant points or changes
- Limit the number of lines to avoid confusion
What we like about it: The versatility and clear visual of trends—line charts can tell a time story like no other.
Pie Chart
Chart created with wpDataTables
Fancy a visual slice of something whole? Enter the pie charts. It takes a full circle, the ‘pie,’ and divides it into color-coded ‘slices.’ Each slice size corresponds to its portion of the whole, making it a delicious choice for showing percentages.
What to use it for:
- Displaying market share among competitors
- Illustrating a budget breakdown
- Showing demographic segmentation
Tips for creating one:
- Limit the number of slices to keep things readable
- Use contrasting colors
- Put the largest slice at 12 o’clock and work around
What we like about it: The immediate visual impact—it’s a globally understood, quick way to digest part-to-whole relationships.
Scatter Plot
The scatter plot is the renegade artist of the data world, throwing dots across a grid to show us the relationship between two variables. Where the dots fall, a story is told, revealing correlations or intriguing clusters.
What to use it for:
- Spotting correlations between variables
- Identifying data outliers
- Analyzing research data sets
Tips for creating one:
- Keep your axes scaled proportionally
- Use dots that are easy to differentiate
- Include trend lines if applicable
What we like about it: The depth of analysis it permits—scatter plots give us a bird’s-eye view on complex variable relationships.
Histogram
Our trusty histogram is all about showing frequency—the number of results in sequential numeric data ranges. Think bars holding hands; there are no spaces between them because they’re displaying a continuous range.
What to use it for:
- Presenting age distribution
- Showing income ranges in a population
- Analyzing test scores’ spread
Tips for creating one:
- Ensure your bins (ranges) make sense for your data
- Start your first bin at zero
- Keep your bin width consistent
What we like about it: The clarity in showcasing data distribution—histograms make spotting the most common ranges straightforward and satisfying.
Area Chart
Chart created with wpDataTables
An area chart takes the stage with the flair of a line chart but throws in some color beneath the line. This chart is all about volume—the filled area helps viewers quickly see total value changes over time.
What to use it for:
- Highlighting volume change over time
- Understanding specific part-to-whole relationships within larger trends
- Stacking multiple data sets to compare changes
Tips for creating one:
- Use semi-transparent colors if layering multiple sets
- Keep your y-axis clear
- Highlight key data points on your line
What we like about it: The drama—area charts bring a dynamic visual punch, emphasizing the magnitude of changes over time.
Box Plot (Box-and-Whisker Plot)
The box plot, the unsung data hero, captures a five-number summary in a glance—minimum, first quartile, median, third quartile, and maximum. It’s a statistical treasure chest, unlocking distribution insights at speed.
What to use it for:
- Statistical analyses across different groups
- Spotting outliers or anomalies in data sets
- Comparing distributions between multiple sets
Tips for creating one:
- Clearly mark the median and quartiles
- Use whiskers to show the range
- Highlight outliers for added insight
What we like about it: The sheer data depth—box plots reveal distribution details that other charts simply can’t touch.
Bubble Chart
Bubble charts are the free spirits—mixing the detail of scatter plots with the added oomph of bubble size to represent a third data dimension. They make patterns and relationships pop in multidimensional glory.
What to use it for:
- Multi-variable analysis
- Displaying social, economic, health, and scientific data sets
- Revealing complex data relationships
Tips for creating one:
- Keep a consistent scale for bubble sizes
- Select distinct colors for different data sets
- Ensure text labels are legible
What we like about it: The third dimension of context—the size aspect adds a layer of nuance that elevates data storytelling.
Stacked Bar Chart
Got segments within segments? Stacked bar charts have you covered, upgrading the traditional bar chart by stacking different data segments on top of one another. They’re your deep-dive into categorical subdivision at first sight.
What to use it for:
- Showcasing total sales while breaking down different product contributions
- Exploring parts of a whole over time or categories
- Comparing total values while seeing segment proportions
Tips for creating one:
- Stick to a clear color palette for different segments
- Keep segment order consistent across bars
- Label segments clearly for readability
What we like about it: The layered insights—it’s like getting the inside scoop on each category while still seeing the big picture.
Heat Map
Bring the warmth with a heat map, where colors aren’t just pretty—they’re telling you a story. This chart uses color shades to show value differences across a two-dimensional surface. It’s intuitive: the warmer the color, the higher the value.
What to use it for:
- Visualizing complex data matrices
- Revealing patterns or performance across different variables
- Observing geographic data distribution
Tips for creating one:
- Choose your color gradient wisely
- Avoid using too many color shades to maintain clarity
- Annotate for context where necessary
What we like about it: The instant ‘aha!’ moment—heat maps make spotting trends and outliers a walk in the park.
Radar Chart (Spider Chart)
Radar charts, also known as spider charts because of their web-like appearance, are about comparing multivariate data. Picture a super spy’s gadget screen, with each axis representing different attributes for comparison.
What to use it for:
- Comparing attributes of different products or services
- Assessing performance across multiple areas
- Skill evaluations for people or teams
Tips for creating one:
- Limit the number of variables to keep it legible
- Standardize your scales for accurate comparison
- Use contrasting colors for different datasets
What we like about it: Its 360-degree view—radar charts let you see all facets of your data in one unified visual circle.
Treemap
Imagine a visual organizer for your data, breaking it down into nested rectangles. Larger boxes catch the eye first, with each rectangle’s size reflecting its value proportion. It’s a sleek way to compare parts in a whole.
What to use it for:
- Displaying hierarchical data
- Illustrating proportions within a dataset
- Visualizing budget allocations or market segmentations
Tips for creating one:
- Use color coding meaningfully to represent different categories
- Keep your labels concise
- Order your rectangles to reflect data hierarchy
What we like about it: The neat breakdown—it’s like turning a complex spreadsheet into an easily digestible art piece.
Gantt Chart
Time and task master, the Gantt chart is your guide through the project management jungle. Horizontal bars map out timelines and deadlines, making it crystal clear who’s on what and when things are due.
What to use it for:
- Managing project schedules
- Coordinating task dependencies
- Tracking progress against time
Tips for creating one:
- Update regularly for accuracy
- Use different colors for various tasks or phases
- Keep the timeline consistent and clear
What we like about it: The control it gives—there’s no project too tangled for a well-executed Gantt chart to make sense of.
Waterfall Chart
The waterfall chart is like a financial storybook, illustrating a starting value and the sequential impact of positive or negative values that lead to a final result. It’s transparency and insight in a unique visual flow.
What to use it for:
- Understanding income statements
- Displaying cumulative effect of sequentially introduced values
- Analyzing inventory or sales numbers
Tips for creating one:
- Start with a clear initial value column
- Use descending or ascending order for the flow of values
- Keep a distinct color for increases and decreases
What we like about it: Its sequential storytelling—waterfall charts drill down into the why’s and how’s behind final numbers.
Sankey Diagram
Sankey diagrams flaunt the flow of energy, materials, or costs between processes. With arrows widening and narrowing, they capture the magnitude of flow visually. It’s data transforming into a river system map, ebbing and flowing through channels.
What to use it for:
- Analyzing energy transfer
- Tracking supply chain logistics
- Visualizing traffic flow or user navigation paths
Tips for creating one:
- Make your flow directions easy to follow
- Use weight variations in arrows to represent different flow volumes
- Keep your colors consistent for similar flow types
What we like about it: The flow dynamics—it’s a power move to track where and how resources get channeled in complex systems.
Bullet Chart
Think of the bullet chart as the sharpshooter of data points. It’s about hitting targets, with clear markers for performance against goals. Sleek and compact, it’s a bar chart evolved—delivering performance evaluations without the fluff.
What to use it for:
- Measuring performance against set benchmarks
- Displaying progress towards a goal
- Comparing metrics across different categories
Tips for creating one:
- Lay out your target markers distinctly
- Use contrasting colors for the performance bar
- Keep your value scales accurate
What we like about it: Its crisp precision—bullet charts give you the low-down on hitting or missing targets at a glance.
Pyramid Graph
Visualize your hierarchy with a Pyramid Graph, where each section represents a different level or component within a larger system. It’s like a corporate ladder or a food chain, neatly packed into a triangle.
What to use it for:
- Displaying organizational structures
- Illustrating food chains or energy hierarchies
- Showing demographic distributions
Tips for creating one:
- Make the largest base section represent the largest segment
- Use gradients or colors to distinguish levels
- Add labels for each section for clarity
What we like about it: The crystal-clear hierarchy—it’s visual storytelling from the ground up, or should we say, from the base up.
Venn Diagram
Venn Diagrams are masters of intersecting worlds, cleverly showing commonalities and differences with overlapping circles. It’s a relationship exploration that says, “Let’s see where we meet and where we part ways.”
What to use it for:
- Examining correlations between groups
- Identifying shared characteristics
- Comparing product features or market segments
Tips for creating one:
- Keep overlaps clear and balanced
- Use contrasting colors for various groups
- Label each section for easy identification
What we like about it: The overlap magic—Venn Diagrams make understanding complex relationships seem like a walk in the park.
Pictograph
A picture is worth a thousand words, and Pictographs take that to heart. Using icons or images to represent data quantities, they bring a dose of visual fun to stats and facts.
What to use it for:
- Educating young audiences
- Presenting survey data engagingly
- Highlighting social media engagement
Tips for creating one:
- Choose universally recognizable icons
- Keep the icon size consistent for accurate representation
- Add a key to explain icon values
What we like about it: Its playful nature—Pictographs turn data into a visual party, inviting everyone to the celebration.
Cartesian Graphs
Cartesian Graphs are the granddads of the graphing world. With their x and y-axes, they’re about plotting points on a grid to see where values land.
What to use it for:
- Mapping out algebraic functions
- Plotting geographical coordinates
- Displaying changes in variable relationships
Tips for creating one:
- Clearly mark your axes with units
- Use a grid for easier point placement
- Highlight important data points
What we like about it: The foundation it provides—Cartesian Graphs are the base of many other graph types, a reliable classic in the world of data.
Dot Plot
Dot Plots are the minimalist’s dream, breaking down data to simple dots along a line. They tell a clear story about frequency and distribution without any superfluous details.
What to use it for:
- Showing small data set frequencies
- Comparing group sizes
- Spotting trends and clusters
Tips for creating one:
- Use a single axis for simplicity
- Keep dot sizes consistent
- Allow sufficient space between dots for differentiation
What we like about it: The simplicity—Dot Plots deliver clean, straightforward insight into your data’s building blocks.
Organizational Chart
Mapping out the corporate jungle, Organizational Graphs are the who’s who of who reports to whom. They visualize the company tree with all its branches right down to the last leaf.
What to use it for:
- Detailing company hierarchies
- Clarifying roles and responsibilities
- Onboarding new employees
Tips for creating one:
- Update regularly with personnel changes
- Use color coding for different departments
- Keep the design clean for easy navigation
What we like about it: The clarity it brings—the Organizational Graph turns complex structures into a navigable map.
Dual Axis Chart
When two datasets want to share the spotlight on a single stage, the Dual Axis Chart lets them. You’ve got two Y-axes, playing side by side but each dancing to their rhythm.
What to use it for:
- Comparing variables with different units or scales
- Showcasing relationships between two distinct data sets
- Identifying correlations and disparities
Tips for creating one:
- Clearly distinguish the two Y-axes and scale them adequately
- Use different chart styles for each data set
- Add labels and legends for clarity
What we like about it: The duality—the Dual Axis Chart is like having two charts in one, doubling your insights.
Flow Chart
Flow charts are the GPS in the world of processes and decision-making. They use symbols and arrows to guide you step-by-step, anticipating every turn in the road.
What to use it for:
- Outlining processes or workflows
- Demonstrating decision-making paths
- Clarifying complex methodologies
Tips for creating one:
- Keep the flow direction consistent
- Use standard symbols for actions and decisions
- Make sure the chart is easy to read
What we like about it: The roadmap it creates—Flow Charts avoid process-related pile-ups, ensuring smooth navigation through tasks.
Spline Chart
Imagine a Line Chart got a makeover to smooth things out. That’s your Spline Chart, with lines curving gracefully between data points, offering a polished view on trends.
What to use it for:
- Smoothing out fluctuations in data
- Displaying refined trend lines
- Enhancing visual appeal for presentations
Tips for creating one:
- Use control points to adjust curves
- Keep the curve changes intuitive
- Highlight significant data trends
What we like about it: The aesthetic finesse—Spline Charts take the edge off sharp turns, delivering a delightful visual flow.
Mekko Chart
Mekko Charts, also called Marimekko or Market Maps, are the bar charts that wanted to show a bit more. These beefed-up visuals highlight not only categories but also their composition and comparative size.
What to use it for:
- Displaying market segmentation
- Analyzing resource allocations
- Presenting revenue streams
Tips for creating one:
- Color-code to show category compositions
- Keep label text clear and legible
- Focus on widths and heights for accuracy
What we like about it: Its layered insight—Mekko Charts deliver a rich visual of your data’s complexities, making comparisons a breeze.
Gauge Charts
Gauge Charts mimic the dials and readings on a dashboard, providing real-time status checks. They show where a value sits within predefined ranges—like your data’s personal speedometer.
What to use it for:
- Monitoring key performance indicators
- Tracking progress towards goals
- Displaying status evaluations
Tips for creating one:
- Define clear ranges or zones
- Use contrasting colors for instant comprehension
- Limit the data to a manageable single metric
What we like about it: Its immediate readability—Gauge Charts offer quick, dashboard-style assessments that drive decisions.
Funnel Chart
Represent your process stages with a Funnel Chart—a visual trip from the broad beginning to the narrowed-down end. It shows progression, drop-offs, and bottlenecks, keeping things moving and improving.
What to use it for:
- Mapping sales processes
- Analyzing website conversions
- Tracking lead generation
Tips for creating one:
- Clearly show each stage of the process
- Use gradient colors to represent progression
- Highlight areas where changes occur
What we like about it: The process insight—Funnel Charts elegantly pinpoint where things flow smoothly and where to troubleshoot.
FAQ about the types of charts
What’s the best chart to use for showing trends over time?
Line graphs, knock it out of the park here. They’re the classic go-to for a reason. You plot your data points along two axes and join the dots. The resulting ups and downs show trends as clear as day. Whether it’s market research numbers or tracking fitness goals, line graphs are your friend.
Can you explain when to use a pie chart?
Ah, the pie chart: ideal for displaying quantitative information that adds up to a whole. Picture your classic pizza pie. When you’re showing how big a slice each category takes, say in budget allocation or survey results, that’s when you roll out the pie chart.
Why would someone use a bar graph instead of a line graph?
Think about categories. Bar graphs are brilliant when you’re comparing different groups, like sales across different regions or quarterly performance reviews. When you’ve gotta showcase differences side-by-side, bar graphs are like visual candy bars – each category gets its own and there’s zero confusion.
What scenarios are best for using a scatter plot?
Alright, scatter plots are like matchmaking apps for data points—they show relationships. Are two variables playing nice together or not? You’re in data analysis heaven if you’re looking for correlations or trends amidst a field of seemingly random data. Like how study time relates to exam scores.
When is it more appropriate to use a histogram instead of a bar graph?
Feeling statistical? Histograms are your move. They’re about distribution—clumping data into ranges rather than isolated categories. Imagine you’ve got survey results with ages. Pop them into age groups, and a histogram will show how those groups stack up. It’s all about the range game.
What’s the main difference between a histogram and a bar graph?
Space—or the lack of it. Histograms have bars smushed together, showing continuous data—like age or weight. Bar graphs leave a little breathing room between the bars because they deal with discrete categories, like your favorite ice cream flavors or different brands of shoes.
Why use a Gantt chart?
Oh, you’re all about that project life? Gantt charts keep your tasks, deadlines, and who’s doing what straight. It’s a project manager’s dream—able to see the whole timeline at a glance. Miss a beat, and it’ll stick out like a sore thumb on a Gantt chart.
Can you use a flow chart for data representation?
No doubt. Flow charts tap into your inner guide. They’re ace for showing processes, like how a user navigates an app or the steps in a recipe. Start to end, decision points, different pathways—it’s all there in a roadmap format that’s as simple as following, well, a flow.
How do you choose which chart to implement when presenting data?
It’s about your message. What’s your data saying? What do you want to highlight? Each chart has its superpower—some for comparison, some for trends, some for distribution. Tailor your chart choice like you’d pick an outfit for the right occasion—in sync with the message and the audience.
What role does data visualization software play in chart selection?
Picture having a Swiss Army knife for data visualization. That’s your software right there. Tools like Microsoft Excel, Tableau, and Google Charts give you options galore and make the creation process smoother than a jazz record. They help you pick, customize, and perfect the chart for your data’s story.
Ending thoughts
We’ve seen the many types of charts, discovering each one’s quirks and features. Like the vibrant colors in a painting, these visual tools add clarity and impact to the story your data’s dying to tell.
- If it’s a snapshot of parts to a whole you need, pie charts offer up a visual feast.
- When trends call for tracking, line graphs step up like tireless time travelers.
- Got categories? Bar graphs raise the bar, making comparisons a piece of cake.
Mix in a dash of creativity when you select your chart. It’s not just about the data – it’s about telling a tale, making those numbers stick.
Working with visualization tools? They’re like a chef’s best knives, waiving magic over rough ingredients to churn out a Michelin-star dish. But remember, the chef’s touch—your knowledge—makes that tool sing.
Choose wisely, and watch your audience nod along, the clarity of your data as illuminating as the first light of dawn.
Are you interested in creating awesome charts in WordPress? Then check out wpDataTables, the #1 tables and charts plugin for WordPress.
If you liked this article about types of charts, you should check out this article about embedding a chart.
There are also similar articles discussing survey graph makers, survey chart types, survey tables, and creating a Google forms results graph.
And let’s not forget about articles on Chart.js examples, chart designs, Highcharts alternatives, and WordPress charts.
