25 Top Chart Types for Data Visualization

October 27, 2023

Mile Zivkovic

The chart you use can make a difference between an amazing dashboard and one that no one understands. Here are the top chart types for data visualization.

What do you think makes a bigger impression: a table comparing GDP growth in a country over the years or a graph with the exact same data?

table vs chart

While both tell the same thing, the graph is much easier to understand - this is the power of data visualization. But how do you choose which visualization type to use? Sometimes, even the best data can be rendered useless if you use the wrong type of chart or visualization.

Today, we’re going to show you the different chart types: how they work and what you should (not) use them for. You don’t have to be an Excel pro to become an expert in showing your data in a more graphical way.

Line chart

When you want to track and trace the evolution of a specific quantitative value, this chart type is a good choice. It is often used to show trends and analyze data changes over time. The line graph can also be used for comparing data from multiple values by using multiple curved or straight lines.

line chart

In a line chart, the y-axis represents the quantitive value, while the x-axis shows the timescale or a sequence of intervals. The direction of the line on the chart tells you a story about where the data is going - an upward or a downward slope shows you the general direction of the values in the visualization.

Best for: trend analysis, time series data, comparing multiple data series.

Bar chart

One of the most commonly used chart types is the bar chart, and for a good reason. If you’re looking for an answer to the question of “how many” for several categories and a specific period of time, this is the chart to use.

bar chart

The classic bar graph setup uses horizontal bars for comparing numeric values across different categories. The longer the bar, the bigger the value displayed on the horizontal axis. You can also group data from one bar into multiple subdivisions to show even more data in one visualization.

Best for: comparing categories, ranking items, frequency distribution.

Scatter plot

If you have two or more variables and want to discover the relationship between them, a scatter plot can be a solid choice. When you have two different variables, they are located on the X and Y axis. The data point is horizontally and vertically located for each variable on the scatter chart. 

scatter plot
This graph is an example for education, showing the relation between the exam results of a student, and how often they attended their classes.

The closer the data points are together, the more related they are. Moreover, if they form a line or a curve, it signifies a strong relationship. The more spaced out the data points are, the weaker the relationship.

Best for: identifying relationships, correlation analysis, and detecting outliers.

Box plot

If you’re doing explanatory data analysis, a box plot (or boxplot chart) is an excellent choice. You can use it to summarize data measured on an interval scale. With a box plot chart, you show the distribution of data points, their central value and their variability.

box plot
This example compares profit margins per shop, also showing the outliers of certain sales transactions that had a higher or lower profit margin, making it easier to compare across stores

One major advantage of a box plot over other types of charts is that you can see a variable’s spread and outliers in one place. Also, this graph type does not take up much space in your dashboard.

Best for: comparing distributions, identifying central tendency, understanding data spread.

Column chart

This is one of the most common chart types that can be used for various sets of data. It’s great for answering the question of “how many” for a specific time period and across different categories. Time indication can be used as a category too so you can track a metric over time.

It uses vertical bars to compare numeric values across different categories or time frames. The longer the bar, the higher the value, which you can see on the vertical axis in the chart. 

Best for: comparing categories, ranking items, frequency distribution.

Dual axis chart

Dual axis chart (also called a multiple axis chart) lets you you compare metrics or different units of measure or scales on a single chart. This way, you can visualize trends that may not be obvious when viewing data points in isolation from each other.

For example, you can have a dual axis chart with products sold on one axis and revenue over time on another axis. This way, you can show the relationship between the two.

Best for: comparing different data types, showing relationships, highlighting trends

Area chart

Similar to the line chart, an area chart lets you track changes over time for one or more categories. You can just as easily compare data from multiple categories with multiple areas.

area chart

You can use it to show trends over time for related categories. The main difference between an area chart and a line chart is that the area below the line is filled with color to show volume.

If the differences between the values in the data are big enough for a clear representation, an area chart may be a better choice than a line chart.

Best for: showing trends over time, parts-to-whole relationships, stacked data comparison

Stacked area chart

A stacked area chart shows you how a measure changes over time, as seen through multiple category values. Opposed to the regular area chart, it stacks all of the lines on top of each other. In other words, these charts visualize the cumulated sum with numbers or percentages over a certain time period, so you can show the contribution of each category. 

stacked area chart

Similarly, the stacked column chart measures contributions from different individual values with their total value.

column chart

While they have their pros, they are also not ideal for some use cases. For example, when you want to give an accurate representation of fluctuations per category.

Best for: part-to-whole contribution, changes to contribution over time, trend analysis.

Pie chart

It does not get more classic than a pie chart, which was invented in the 18th century. This chart type is ideal for showing different parts of a whole and getting a proportional distribution of your data. The circle (pie) is divided into pieces to show how much space a certain value takes up in proportion to the whole.

pie chart

The problem with pie charts is that as humans, we are naturally not very good at interpreting the sizes of the different slices. To combat this issue, make sure you don’t have more than five different slices in a pie. Or simply use a donut chart.

Best for: showing relative proportions, highlighting the relationship of a part to a whole, simple data sets. 

Donut chart

Pies vs. donuts debate in terms of taste is a tricky one. However, when it comes to chart types, donut charts are a better option than pie charts. There is just one difference: the doughnut chart has a hole in the middle of the slices, hence, making it a donut.

donut chart
Example of a donut chart in the construction industry: open tasks/tickets per construction stage (for better project management of a construction project)

The downside is the same: our brain can't interpret the sizes easily, so keep it under five slices for this chart type as well. However, since there is no center (that we focus on by default), we judge the pieces by their length. This makes them easier to read than pies. If you do have more than five data points, use a bar chart as a good alternative.

Best for: showing relative proportions, highlighting the relationship of a part to a whole, simple data sets. 

Bubble chart

A bubble chart is a fun way to show how many values you have per each category. The higher the value, the bigger the bubble, which gives you a super easy overview of your top categories. To get even more value from this chart type, you can group similar categories by using the same or similar colors.

bubble chart

You can adjust and customize bubble charts to show the type of data you need. For example, you can limit the number of bubbles or choose to display the absolute value of percentages.

Best for: showing multivariate data, comparing more than two variables, visualizing trends and patterns


A histogram shows you the frequency of numerical data by using rectangles. The vertical axis represents the frequency of a variable. The horizontal axis shows the variable value, e.g. months, weeks, days.

Example of average reply time per tickets in a customer support context. Horizontal access has reply time as variable value; vertical has the amount of tickets (frequency)

A histogram is the ideal chart type for comparing the distribution of numerical data in different time intervals or ranges.

Best for: data distribution analysis, identifying outliers, data preprocessing.

Funnel chart

This chart type is ideal for showing the stages of a process in parts stacked on top of each other and visually enhancing them with colors. The more items you have in a certain stage, the wider that part of the chart is.

funnel chart

This makes funnel charts ideal for taking a look at processes and identifying bottlenecks. In Luzmo, there are three different layout types for this chart: dynamic width, dynamic height, and equal and linar.

Best for: lead generation and conversion charts, website conversion analysis, sales and marketing funnel visualization.


A heatmap or a heat map is a type of chart that shows values for a main variable across two axis variables as a grid with squares in different colors. The variables are split into ranges similar to a histogram or a bar chart.


The typical heatmap chart has darker colors corresponding to the larger values in variables. This makes it easy to see patterns and make conclusions with a quick glance at a heatmap.

PS. another name for a heatmap is a density map, which is coincidentally, something entirely different from a chart.

Best for: data exploration and pattern recognition, correlation analysis, risk assessment and portfolio analysis.

Gantt chart

A Gantt chart is a subtype of a bar chart that shows different categories over a time period. You can use it to visualize the start and finish of a project in time period blocks. Besides data visualization, Gantt charts are also commonly used for project management to ensure that projects stay on track and within deadlines.

gantt chart

Best for: project planning, dependency management, task scheduling.

Radar chart

When you want to compare two or more categories based on different variables, a radar chart is the ideal choice for multivariable comparison. If you have a lot of data and a high number of variables and want to show them in one chart without it looking like a mess, you want to use a radar chart.

To make the radar chart more suitable for your needs, you can change the opacity of the color to make it more or less intense. A radar chart is often used for mapping out skillsets, e.g. for HR or training purposes.

radar chart

Best for: multi-dimensional data comparison, performance evaluation, feature comparison

Waterfall chart

You can use a waterfall chart to show a running total where the values are added or subtracted. This is a good type of chart to show how an initial value gets impacted over time with positive and negative values.

waterfall chart

The values can be based on the time or category. Other names for this chart are a flying bricks chart or a Mario chart.

Best for: financial statement analysis, project budget analysis, sales and revenue analysis.

Treemap chart

If you want to show a hierarchical structure in a fun way, this type of graph is a great choice. Alternatively, if you want to show proportions between different values within a single category, you can use a treemap.

treemap chart

Even though it’s called a treemap, this visualization type uses squares for visualizing categories. Every category has a colored rectangle area and subcategories are within these rectangles. The bigger the rectangles, the bigger bigger the part-to-whole ratio.

Best for: hierarchical data visualization, nested categories, quantitative data display.

Bullet chart

When you need to visualize data in terms of performance, bullet charts are one of the most logical choices. They allow you to show the progress of multiple categories in one place.

bullet chart

These chart types are most commonly used to compare a performance forecast with the actual numbers. If you want to track if your business or a certain department is meeting certain goals, this is a great chart type to use.

Best for: goal and target tracking, performance assessment, tracking efficiency and productivity.

Candlestick chart

Also known as the Japanese candlestick chart or a K-line, this is the ideal choice for visualizing and tracking financial data. It consists of two parts:

  • The body (the open and close price)
  • The wick (high and low price)
candlestick chart

When creating this type of chart, the body is filled by default when the open price is higher than the close price. This means you’re in a bear market. If the body is empty, this is a bull market

Best for: financial use cases - market sentiment, price reversals, support and resistance levels.

Sankey diagram

Dating back to the 19th century, the Sankey diagram is one of the oldest ways to show data values in visual form. This type of diagram is ideal for showing flows and amounts of traffic. The higher the quantity of the flow, the wider the streams in the diagram. 

sankey diagram
Example of how energy flows from different sources to different destinations

The flow can break out into multiple branches or subcategories, indicating the size connection between them.

Best for: energy flow analysis, material flow analysis, environmental data.

Choropleth map

This is a statistical thematic map that uses colors that match a number range. It’s most commonly used to summarize a geographic characteristic in a geographic area. You’ll see these maps when viewing information such as income per capita or population density.

choropleth map

Best for: geographic insights, data distribution, special patterns

Symbol map

A symbol map overlays quantitative values over geographical locations through the use of symbols. These maps are easy to read and they have been around for centuries. When preparing presentations of data studies or something happening to a geographical area, go with this chart type.

Best for: geospatial data, location analysis, spatial trends

symbol map

Pyramid chart

This chart type is ideal when comparing the distribution of two categories against each other on a few levels such as age groups, years and others. It’s commonly used for showing demographic data represented by two categories (male and female), grouped into different categories such as age groups.

pyramid chart

Best for: population demographics, market segmentation, economic data

Circle pack diagram

If you want to visualize hierarchies without using traditional chart types, this is an interesting choice. Instead of using bars, circles can be used to show hierarchy. The larger the circle, the larger the category, packing up smaller categories within it.

circle pack diagram
circle pack diagram 2

Best for: hierarchical data, proportional data, data exploration

Wrapping up

As you can see, there are a lot of chart types to choose from. The right chart for your application will be the one that shows the most relevant data in a way that is clear and easy to understand. However, finding that chart can be very challenging.

To help you out, you can use dashboard templates in Luzmo to find the most commonly used charts, along with their use cases. If you’re looking for inspiration, these templates will show you how to go from your data points to a useful visualization.

And if you’re ready to build an embedded analytics dashboard of your own, we can help you do that in a matter of hours - not weeks. Sign up for Luzmo today and go from raw data to interactive insights, rapidly fast!

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