http://idi.kennesaw.edu/it7113/


https://www.edocr.com/v/lonn6pal/

Data Chart Types
IT 7113 Data Visualization
J.G. Zheng
Fall 2024
http://idi.Kennesaw.edu/it7113/
https://www.edocr.com/v/lonn6pal/

https://towardsdatascience.com/how-did-i-classify-50-chart-types-by-purpose-a6b0aa5b812d

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

http://en.wikipedia.org/wiki/Chart

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.

http://datavizproject.com/


http://www.datavizcatalogue.com/


https://www.data-to-viz.com/


http://chartmaker.visualisingdata.com/

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.

https://public.tableau.com/app/profile/josh.weyburne/viz/CookBook/VizCookbook


https://public.tableau.com/app/profile/andy.kriebel/viz/VisualVocabulary/VisualVocabulary


https://public.tableau.com/app/profile/kevin.flerlage/viz/TheTableauChartCatalog/TableauChartExamples

Tableau Specific Chart Catalog
• Tableau Cook Book by Josh Weyburne
– https://public.tableau.com/app/profile/josh.weybu
rne/viz/CookBook/VizCookbook
• Visual Vocabulary by Andy Kriebel
– https://public.tableau.com/app/profile/andy.krieb
el/viz/VisualVocabulary/VisualVocabulary
• The Tableau Chart Catalog by Kevin
Flerlage
– https://public.tableau.com/app/profile/kevin.flerla
ge/viz/TheTableauChartCatalog/TableauChartEx
amples
6

https://extremepresentation.com/design/7-charts/


https://www.qlik.com/blog/third-pillar-of-mapping-data-to-visualizations-usage


https://www.perceptualedge.com/blog/?p=2080


https://excelcharts.com/classification-chart-types/


https://www.dataatworkbook.com/


https://www.juiceanalytics.com/chartchooser


https://policyviz.com/2014/09/09/graphic-continuum/


https://www.informationisbeautifulawards.com/showcase/611-the-graphic-continuum


https://www.ft.com/vocabulary


https://ft-interactive.github.io/visual-vocabulary/


http://experception.net/

Chart Categorization Quick Refs
7
• 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
• https://ft-interactive.github.io/visual-
vocabulary/ (interactive)
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.

http://extremepresentation.com/design/7-charts/


https://www.qlik.com/blog/third-pillar-of-mapping-data-to-visualizations-usage


https://www.perceptualedge.com/blog/?p=2080

Choose a Chart
8
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

http://www.excelcharts.com/blog/classification-chart-types/


https://www.dataatworkbook.com/data-work-07-how-choose-chart-graph/

Jorge Camoes Version
9
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

https://www.qlik.com/blog/third-pillar-of-mapping-data-to-visualizations-usage


http://www.excelcharts.com/blog/classification-chart-types/

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
10
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)

https://www.dataatworkbook.com/data-work-08-sense-order-data-comparison-charts/

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
11

https://www.tableau.com/about/blog/2017/1/viz-whiz-when-use-lollipop-chart-and-how-build-one-64267


https://datavizproject.com/data-type/butterfly-chart/


https://www.investopedia.com/dot-plot-4581755


https://datavizproject.com/data-type/bar-chart/


https://datavizcatalogue.com/methods/bar_chart.html


https://chartio.com/learn/charts/bar-chart-complete-guide/

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
12
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
13
Horizontal bar chart
Stacked column chart
Stacked percentage chart
Vertical column chart
(clustered)

https://www.dataatworkbook.com/data-work-11-change-over-time/

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/
14

https://datavizcatalogue.com/methods/area_graph.html


https://en.wikipedia.org/wiki/Kagi_chart


https://datavizproject.com/data-type/line-chart/


https://datavizcatalogue.com/methods/line_graph.html

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
15
Reference:
•
https://datavizproject.com/data-type/line-chart/
•
https://datavizcatalogue.com/methods/line_graph.html
Basic Line Chart Variations
16
Area chart
Percentage area chart
Stacked line chart

https://www.dataatworkbook.com/data-work-09-parts-whole-composition-charts/

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/
17

https://priceonomics.com/should-you-ever-use-a-pie-chart/


https://datavizproject.com/data-type/pie-chart/


https://datavizcatalogue.com/methods/pie_chart.html


https://en.wikipedia.org/wiki/Pie_chart

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.
18
Reference
•
https://datavizproject.com/data-type/pie-chart/
•
https://datavizcatalogue.com/methods/pie_chart.html
•
https://en.wikipedia.org/wiki/Pie_chart

https://datavizproject.com/data-type/donut-chart/


https://datavizcatalogue.com/methods/sunburst_diagram.html


https://datavizproject.com/data-type/polar-area-chart/


https://en.wikipedia.org/wiki/Pie_chart#Spie_chart


http://www.fusioncharts.com/chart-primers/multi-level-pie-chart/


http://www.datavizcatalogue.com/methods/nightingale_rose_chart.html

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)
19
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

https://www.trueup.io/layoffs


https://twitter.com/l__orenz/status/1619669226691887108

Stacked Column/Bar for Composition
• Using a set of pie
charts? Try
stacked
column/bar chart
to save space.
20
https://www.trueup.io/layoffs
https://twitter.com/l__orenz/st
atus/1619669226691887108

https://datavizcatalogue.com/methods/treemap.html


https://datavizproject.com/data-type/convex-treemap/


https://www.visualcapitalist.com/80-trillion-world-economy-one-chart/


https://finviz.com/map.ashx

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
21
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
22

https://datavizproject.com/data-type/histogram/


https://datavizproject.com/data-type/hexagonal-binning/


https://datavizproject.com/data-type/strip-plot/

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
23

https://datavizproject.com/data-type/histogram/

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/
24

https://datavizproject.com/data-type/scatter-plot/


https://chartio.com/learn/charts/what-is-a-scatter-plot/

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/
25

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/


https://datavizcatalogue.com/methods/bubble_chart.html


https://visage.co/data-visualization-101-bubble-charts/


https://www.displayr.com/what-is-a-bubble-chart/

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/
26

https://www.smashingmagazine.com/2023/01/guide-getting-data-visualization-right/


https://datavizproject.com/data-type/arc-diagram/


https://datavizproject.com/data-type/chord-diagram/


https://twitter.com/fminderop/status/1751226199320203484

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/
27
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
28

https://www.dataatworkbook.com/chapter-13-profiling/


https://en.wikipedia.org/wiki/Small_multiple


http://www.datavizcatalogue.com/methods/parallel_coordinates.html


https://datavizproject.com/data-type/radical-histogram/


http://www.datavizcatalogue.com/methods/nightingale_rose_chart.html


https://public.tableau.com/app/profile/datavizard/viz/TheShiftingPoliticalLandscape/Shift

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
29
https://public.tableau.com/app/profile/dataviz
ard/viz/TheShiftingPoliticalLandscape/Shift

https://www.storytellingwithdata.com/blog/2021/8/31/what-is-a-spider-chart


http://www.datavizcatalogue.com/methods/radar_chart.html


https://simplywall.st/stocks/us/media/nasdaq-googl/alphabet


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

Radar/Spider Chart
• As known as: Spider Chart, Web Chart, Polar Chart,
Star Plots, snowflake chart
• Features
– 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/wh
at-is-a-spider-chart
30
http://www.datavizcatalogue.com
/methods/radar_chart.html
Source: Yahoo Finance
https://simplywall.st/stocks/us/media/
nasdaq-googl/alphabet
Some critics of radar charts
• 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

http://en.wikipedia.org/wiki/Heat_map

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
31

https://www.qlik.com/blog/third-pillar-of-mapping-data-to-visualizations-usage


https://alexgonzalezc.dev/posts/data-visualization-principles.html


https://www.tableau.com/sites/default/files/media/which_chart_v6_final_0.pdf

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
32

https://www.datapine.com/blog/how-to-choose-the-right-data-visualization-types/


https://www.optimizesmart.com/how-to-select-best-excel-charts-for-your-data-analysis-reporting/


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


http://www.datavizcatalogue.com/


http://datavizproject.com/


https://www.data-to-viz.com/


http://chartmaker.visualisingdata.com/


https://www.amazon.com/Effective-Data-Visualization-Right-Chart/dp/1506303056/


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/


https://visage.co/content/data-visualization-101/

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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