chart types and purposes

An introduction of chart types and purposes in IT 7113 Data Visualization at Kennesaw State University - updated in 2024.
About Jack Zheng

Faculty of IT at Kennesaw.edu
chart chart type chart purpose data chart data visualization Chart http Data http www visual type
An introduction of chart types and purposes in IT 7113 Data Visualization at Kennesaw State University - updated in 2024.
About Jack Zheng

Faculty of IT at Kennesaw.edu
chart chart type chart purpose data chart data visualization Chart http Data http www visual type
Data Chart Types
IT 7113 Data Visualization
J.G. Zheng
Spring 2024
http://idi.Kennesaw.edu/it7113/
https://www.edocr.com/v/lonn6pal/
Content Overview
Topics of this lecture:
• Categorization of charts particularly by 
functions/purposes
• Summary of the most common type charts
2
Charts are the basic kind of data visualization tool and used universally in 
all kinds of reports and analysis.
This lecture notes (the first one on charting) provides an introduction of 
charts and their categorizations, with a focus on commonly used charts.
The purpose of 
visualization is insight, 
not pictures
https://towardsdatascience.com/how-did-i-classify-50-chart-
types-by-purpose-a6b0aa5b812d
Chart
• A chart is a graphical representation of data
– Chart is a unique combination of symbols (visual 
elements) with visual properties which directly 
represents quantitative values
– http://en.wikipedia.org/wiki/Chart
• Chart vs. Diagram
– These two terms are very similar; they are often used 
together or interchangeably in daily life.
– Chart is more abstractly presented and focuses more on 
quantitative values.
– Diagrams also cover a lot of qualitative information like 
process, concepts, ideas, structures, etc.; they also 
intergrade more real-world contexts like maps.
– Diagram is sometimes considered to include chart.
3
Basic Chart Types
• Basic or general-use charts serve a wide range of analysis and 
visualization needs. 
– They are commonly applied in all kinds of reports and analysis, and not 
limited to a particular type of business or industry.
– The basis for other advanced charts, composite charts, or more specialized 
charts.
– Commonly named directly by its visual elements, bar, pie, line, etc.
• List of basic chart types
– bar/column chart
–
line/area chart
– pie chart
– scatter/bubble chart
– spider/radar chart
• Other common charts
– Histogram
– Tree map
– Heat map
4
Note:
Many of the chart variations 
mentioned in the following 
slides can be found in the chart 
catalogs listed in slide 5 and 6.
Chart Catalog and Selection Tool
5
• The following are detailed and interactive 
references for charts. They are good resources.
Ferdio*
http://datavizproject.com
An interactive resource with a lot of examples. Included 
diagrams and maps. Categorization by function and a 
unique category by data inputs. It provides details for 
each chart. I use it for reference a lot.
Data catalog*
http://www.datavizcatalogue.
com
An interactive catalog with very detailed description for 
each chart. Added many smaller and specific 
categories. I use it for reference a lot.
From Data to Viz
https://www.data-to-viz.com A classification of chart types based on input data 
format. It comes in the form of a decision tree. It also 
provide details for each chart.
Chart make 
directory
http://chartmaker.visualising
data.com
This is a community effort to catalog charts by function 
and show solutions for each major visualization tool 
(with links to external resources). 
* I use this resource for reference a lot.
Chart Categorization Quick Refs
6
• The following are some efforts that simply try to 
categorize charts by purpose or data type without much 
explanation. They are good as a quick reference.
Abela's version
• https://extremepresentation.com/desig
n/7-charts/
• https://www.qlik.com/blog/third-pillar-
of-mapping-data-to-visualizations-
usage
This is the most widely referred version with a simple visual itself. 
But it was criticized by Stephen Few with a lot of details 
https://www.perceptualedge.com/blog/?p=2080 - Categorized by four 
purposes: compositions, comparison, distribution, and relationship.
Camões’s version
https://excelcharts.com/classification-
chart-types/
Influenced by Abela’s version, added evolution (like trend) and 
profiling. The blog is very brief. He has an updated version with more 
details in his book “data at work” https://www.dataatworkbook.com.
Juice Analytics
https://www.juiceanalytics.com/chartchoo
ser
Provided as an interactive online chooser with templates for Excel 
and PowerPoint. Categorized similarly but added an “trend” 
category.
Schwabish’s
Graphic Continuum
• https://policyviz.com/2014/09/09/graphic-
continuum/
• https://www.informationisbeautifulawards.c
om/showcase/611-the-graphic-continuum
A poster style visual presentation covering nearly 90 charts.
Financial Times 
Visual Vocabulary
https://www.ft.com/vocabulary
Financial Times Visual Vocabulary is based on the Graphic 
Continuum.
Fraconeri’s version
http://experception.net
A quick reference in PDF that considers data types and inputs, 
rather than purposes.
Choose a Chart
7
Andrew Abela’s thought starter
–
Figure from http://extremepresentation.com/design/7-charts/
–
Details from https://www.qlik.com/blog/third-pillar-of-mapping-data-to-visualizations-usage
–
Some critics from Stephen Few https://www.perceptualedge.com/blog/?p=2080
This is like trend or 
evolution
Apply your critical 
thinking to assess this 
categorization method
Jorge Camoes Version
8
Image from http://www.excelcharts.com/blog/classification-chart-types/
Details in https://www.dataatworkbook.com/data-work-07-how-choose-chart-graph/
A new category 
is added
Trend can be thought of 
comparison along timelines
Purposes in Categorizing Charts
Purpose/function Description
Basic Charts
Comparison
Comparing and sorting data points; can 
also compare to benchmarks or norms.
Column/bar
Trend/evolution
Variation of comparison involving 
temporal data.
Line/area chart
Composition
A hierarchy relationship. Also, it may 
imply part-to-whole comparisons.
Pie chart
Stacked column/bar chart
Tree map
Distribution
Aggregated value (usually count) of data 
points placed in categories; the category 
can be value ranges or time (trend).
Histogram
Scatter plot
Relationship
How things (data items) are related or 
positioned in a bigger context.
Scatter plot
Bubble chart
Profiling
To comprehend things through visual 
shapes and patterns.
Spider/radar chart
9
Charts are commonly categorized by the following purposes and functions. Please refer to the 
following for details
– https://www.qlik.com/blog/third-pillar-of-mapping-data-to-visualizations-usage (the basic four)
– http://www.excelcharts.com/blog/classification-chart-types/ (added evolution and profiling)
1. Comparison
• Comparison is the most common purpose of using charts.
– “Comparisons are found everywhere in data visualization, so much so that Edward Tufte 
says that “compared with what?” is “the deep, fundamental question in statistical analysis.” 
In a more or less explicit way, you’ll find comparisons at the heart of every category in our 
chart classification.” – From “Data at Work” Chapter 8 
https://www.dataatworkbook.com/data-work-08-sense-order-data-comparison-charts/
•
In this particular type of “comparison”, we usually compare discrete data items 
(entities, categories, etc.)
• Other purposes are more or less specific ways of comparisons
– Part-whole comparison  “composition”
– Relative positioning comparison  “relationship”
– Time-based comparison  “trend”
– Pattern comparison  “distribution” or “profile”
• Basic charts for comparison among data items
– Column/bar chart
• Alternatives
– Line/area chart
– Dot plot
10
Bar/Column Charts
•
Features and usage
– Use rectangular bars with length/area proportional to the values they represent.
– Often used to display and compare discrete data in different categories
– Convention: column chart has vertical columns and bar chart has horizontal bars
– Choose column or bar based on the size and shape of charting space
– Use horizontal bar charts if data items are more than 10 to 15, depending on situations 
•
Style variations
– Stacked bar/column
– Stacked percentage
–
Lollipop or pin chart https://www.tableau.com/about/blog/2017/1/viz-whiz-when-use-lollipop-chart-and-how-build-one-64267
– Butterfly diverging/bi-direction/mirror bar chart https://datavizproject.com/data-type/butterfly-chart/
– Pyramid chart
– Dot plot https://www.investopedia.com/dot-plot-4581755
– Radial bar chart
•
A basis for these more specialized chart types
–
Tornado chart
– Bullet chart
– Waterfall chart
– Histogram
– Candle stick chart
– Gantt chart
– Box plot
11
References:
•
https://datavizproject.com/data-type/bar-chart/
•
https://datavizcatalogue.com/methods/bar_chart.html
•
https://chartio.com/learn/charts/bar-chart-complete-guide/
Some Basic Bar Chart Variations
12
Horizontal bar chart
Stacked column chart
Stacked percentage chart
Vertical column chart 
(clustered)
2. Trend
• This category can be seen as a more specific 
comparison along the time dimension.
• Changes along the time can be viewed as continuous, 
rather than discrete – very often but still not always
• Major chart types to use
– Line chart
– Area chart
• Other alternatives
– Circular line chart (emphasizing cycles like year or hour)
– Bar chart (sometimes if too few time points)
– Connected dots
– https://www.dataatworkbook.com/data-work-11-change-over-
time/
13
Line Chart
• Features and usage
– Connecting value points along an axis
– Displays continuous (or semi-continuous) data serials
– Often used to visualize a trend in data over intervals of time
– Compared to column chart, line chart can handle more data serials 
and more data points (time points)
• Style variations
– Area chart https://datavizcatalogue.com/methods/area_graph.html
– Curved/smoothed line chart
– Stacked line/area chart
– Stack percentage line/area chart
– Circular line chart
• A basis for these more specialized chart types
– Kagi chart https://en.wikipedia.org/wiki/Kagi_chart
14
Reference:
•
https://datavizproject.com/data-type/line-chart/
•
https://datavizcatalogue.com/methods/line_graph.html
Basic Line Chart Variations
15
Area chart
Percentage area chart
Stacked line chart
3. Composition
• This category can be seen as a more specific comparison among 
parts of a whole.
• The visual shows the relative percentages or weights, rather than 
absolute values
• Major chart type
– Pie chart
– Tree map
• Alternative charts (that also emphasis the part to whole 
comparison)
– Stacked bar/column chart
– Stacked percentage bar/column
– Packed bubble/circle chart
– Dot matrix or waffle chart
– See some example in Excel from “data at work” chapter 9 
https://www.dataatworkbook.com/data-work-09-parts-whole-
composition-charts/
16
Pie Chart
• Features and usage
– A circular chart divided into sectors, illustrating proportions. The arc length of each sector 
(or its angle and area) is proportional to the value it represents
– To represent the different parts of a whole, or the % of a total
– Can be seen as a circular variation of the stacked percentage bar chart, but adding a 
perspective of 100%
– Capture and hold attention to the significant parts, but do not offer faster and precise 
readings or comparison
• Best practices
– Starting from the up-north point and going clockwise
– Order by percentages descending
• Critic on the pie chart
– https://priceonomics.com/should-you-ever-use-a-pie-chart/
• Try alternatives
–
If comparing among similar items, use columns chart, or adding % labels
–
If more than 7 items, use other types of charts (bar/column or tree map); or group the rest 
into other, and use a second chart or table to present other
– Have a set of pie charts? Try stacked column/bar chart to save space.
17
Reference
•
https://datavizproject.com/data-type/pie-chart/
•
https://datavizcatalogue.com/methods/pie_chart.html
•
https://en.wikipedia.org/wiki/Pie_chart
Pie Chart Variations
• Style variations
– Donut chart: hole in the center reserved for some key 
information, often the total 
https://datavizproject.com/data-type/donut-chart/
– Multilevel pie chart, sunburst 
https://datavizcatalogue.com/methods/sunburst_diagra
m.html
• A basis for 
– Polar area (or rose) chart or radial pie chart 
https://datavizproject.com/data-type/polar-area-chart/ -
uses length of the pie rather than angle of the pie
– Spie chart: uses both angle and length of the pie; adds 
a second measure for each data point (length of a pie)
18
https://en.wikipedia.org/wiki
/Pie_chart#Spie_chart
http://www.fusioncharts.com/char
t-primers/multi-level-pie-chart/
Nightingale chart
http://www.datavizcatalogue.com/met
hods/nightingale_rose_chart.html
Stacked Column/Bar for Composition
• Using a set of pie 
charts? Try 
stacked 
column/bar chart 
to save space.
19
https://www.trueup.io/layoffs
https://twitter.com/l__orenz/st
atus/1619669226691887108
Tree Map
• Tree maps are an alternative way of 
visualizing the hierarchical structure of 
a tree Diagram while also displaying 
quantities for each category via area 
size. 
– Each category is assigned a rectangle 
area with the subcategory rectangles 
nested inside.
– Tree map 
https://datavizcatalogue.com/methods/tr
eemap.html
• Use a tree map if there are many parts
• Style variations
– Convex tree map 
https://datavizproject.com/data-
type/convex-treemap/
– Packed bubble chart
20
https://www.visualcapitalist.com/80-
trillion-world-economy-one-chart/
https://finviz.com/map.ashx
Special Note: Packed Bubble Chart
• “Packed bubble chart” (Tableau) 
is different from scatterplot-
based bubble chart (see slide 
25)
– It looks like bubble chart but does 
not have the underlying x/y 
coordinates system.
– Bubble size may represent 
weights or percentages – this is 
similar, and may be an alternative, 
to pie charts
• Similar visualizations (showing 
weights or size)
– Tree map
– Word cloud
21
4. Distribution
• Show how data items distributed along a range of 
values, so patterns can be detected
• Basic chart type
– Histogram (1D) 
https://datavizproject.com/data-type/histogram/
– Scatter plot (2D)
• Alternatives
– Hex binning 
https://datavizproject.com/data-type/hexagonal-binning/
– Strip plot (univariate scatter plot, single-axis scatter plot): 
similar to scatter plots but there is only one axis for one 
measure. https://datavizproject.com/data-type/strip-plot/
– Dot map
– Area chart
22
Histogram
• A histogram is a chart that groups numeric 
data into bins, displaying the bins as 
segmented columns. They’re used to depict 
the distribution of a dataset: how often 
values fall into ranges.
• Variation
– Dot plot
• Reference
– https://datavizproject.com/data-type/histogram/
23
Scatter Plot
• Scatterplots use a collection of points placed in a 2D space (often with the Cartesian 
Coordinates) to represent data points. In this way we can detect how data points are related.
• Variations
– Bubble chart: adds more visual variable to each data points to represent more dimensions: usually size 
and color.
• Basis for
– Perceptual/positioning map
– Connected scatter plot
• Reference
– https://datavizproject.com/data-type/scatter-plot/
– https://chartio.com/learn/charts/what-is-a-scatter-plot/
24
Bubble Chart
• Bubble chart adds more visual variable to each data points on the scatter plot to represent more 
dimensions: usually a measure will be mapped to bubble size.
– Commonly used for perceptual/positioning map
• Example
– https://www.gapminder.org/tools/#$chart-type=bubbles
– https://twitter.com/kirkgoldsberry/status/1174020669299810304
– https://www.goodcarbadcar.net/2019-u-s-auto-manufacturer-sales-figures/
• Reference
– https://datavizcatalogue.com/methods/bubble_chart.html
– https://visage.co/data-visualization-101-bubble-charts/
– https://www.displayr.com/what-is-a-bubble-chart/
25
5. Relationship
• You want to show the relationship between each data item, how each one relates (or 
connects) to other items or the underlying context, from a spatial and positional 
perspective.
– Either 1D or 2D space
• Relationship is related to distribution, but emphasizes on individual entity and 
connection, not a summary view of groups
• Common uses
– Showing connections 
https://www.smashingmagazine.com/2023/01/guide-getting-data-visualization-right/
– Showing structures (hierarchy, network, linear)
– Showing flows (between steps/stages)
– Showing a pattern – related to distribution
• Common chart type
– Bubble chart/Scatter plot
– Strip plot
– Tree/network diagram
– Sankey diagram, funnel chart
• Alternatives
– Arc diagram https://datavizproject.com/data-type/arc-diagram/
– Chord diagram 
https://datavizproject.com/data-type/chord-diagram/
26
https://twitter.com/fminderop/st
atus/1751226199320203484
Diagrams
• Many diagrams are used to 
visualize relationships, and they 
can be data/information driven
• Specific cases
– Network diagram
– Sitemap in web design
– Organization structure
– Workflow
– Process
– System architecture
– Road map
– Strategy map
– Curriculum map
– Concept map
27
6. Profile
•
A “profile” consists of multiple (sometimes more) quantitative attributes that value the entity.
• Profiling is the representation of entities by creating an array of similar charts in which there are 
two readings: a reading of each individual profile and a comparison reading with other profiles. 
The integration and interdependence of these charts should lead us to consider them as a 
whole—as a single chart rather than as separate charts.
•
The purpose here is to emphasize the identification and comparison of general patterns, rather 
than individual data attribute or data point.
–
Insight comes from observation of the whole rather from the individual chart/data item.
– https://www.dataatworkbook.com/chapter-13-profiling/
• Commonly used in 
– Portfolio analysis
– Scoring system
– Visualization of large quantities of data
• Basic chart type
– Radar/spider chart
– Heat map
• Alternatives
– Small multiples https://en.wikipedia.org/wiki/Small_multiple
– Parallel coordinates http://www.datavizcatalogue.com/methods/parallel_coordinates.html
– Radial column chart (polar histogram) https://datavizproject.com/data-type/radical-histogram/
– Nightingale chart (polar area) chart 
http://www.datavizcatalogue.com/methods/nightingale_rose_chart.html
28
https://public.tableau.com/app/profile/dataviz
ard/viz/TheShiftingPoliticalLandscape/Shift
Radar/Spider Chart
• As known as: Spider Chart, Web Chart, Polar Chart, Star Plots, 
snowflake chart
•
Features
– All axes are arranged radially, with equal distances between each other.
– Sort of like area chart but categories are arranged radially.
– The area usually forms a unique shape pattern to represent the item profile.
• Reference
– https://www.storytellingwithdata.com/blog/2021/8/31/what-is-a-spider-chart
• Some critics
– http://blog.scottlogic.com/2011/09/23/a-critique-of-radar-charts.html
– http://peltiertech.com/spider-chart-alternatives/
– https://community.tableau.com/ideas/1458
29
http://www.datavizcatalogue.c
om/methods/radar_chart.html
Source: Yahoo Finance
https://simplywall.st/stocks/us/media/
nasdaq-googl/alphabet
Heat Map
• A heat map is a colored representation of data displayed in a context (usually a table, matrix, 
X/Y chart (scatter plot), map, etc.) http://en.wikipedia.org/wiki/Heat_map
•
It is not a chart by itself, but it is used together (overlay) with other types of visuals such as 
tiled/tree map, or maps.
• Often used for a single measure with a large number of data points.
• Examples
30
Key Readings and Resources
• The basic four categories of charts by 
purposes: 
– https://www.qlik.com/blog/third-pillar-of-
mapping-data-to-visualizations-usage
– and more examples 
https://alexgonzalezc.dev/posts/data-
visualization-principles.html
• Tableau recommendation - Which chart or 
graph is right for you?
– https://www.tableau.com/sites/default/files/media
/which_chart_v6_final_0.pdf
31
Additional Good Resources
• More tips and practices
– How to Choose the Right Data Visualization Types https://www.datapine.com/blog/how-to-choose-the-right-data-
visualization-types/
– Best Excel Charts Types for Data Analysis, Presentation and Reporting https://www.optimizesmart.com/how-to-select-best-
excel-charts-for-your-data-analysis-reporting/
– Google data visualization guidelines https://m2.material.io/design/communication/data-visualization.html
–
https://blog.hubspot.com/marketing/types-of-graphs-for-data-visualization
–
https://towardsdatascience.com/how-did-i-classify-50-chart-types-by-purpose-a6b0aa5b812d
• Good tools and references
– Data catalog: http://www.datavizcatalogue.com
–
Ferdio: http://datavizproject.com
–
From Data to Viz: https://www.data-to-viz.com
– Chart make directory: http://chartmaker.visualisingdata.com
•
Effective Data Visualization: The Right Chart for the Right Data
–
https://www.amazon.com/Effective-Data-Visualization-Right-Chart/dp/1506303056/
•
Visage How to Design series
–
https://visage.co/data-101-refresher-course/
–
https://visage.co/data-visualization-101-line-charts/
–
https://visage.co/data-visualization-101-area-charts/
–
https://visage.co/data-visualization-101-bar-charts/
–
https://visage.co/data-visualization-101-pie-charts/
–
https://visage.co/data-visualization-101-scatter-plots/
–
https://visage.co/data-visualization-101-bubble-charts/
–
Free eBook: How to design charts and graphs https://visage.co/content/data-visualization-101/
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