Presentation by Alycia Murugesson & Nokuthula Mabhena on how to make data attractive for the 5th Biennial SAMEA Conference. Covers data visualization and infographics.
4. Your data is only as good as
your ability to understand and communicate it, which
is why choosing the right visualization is essential.
–Data Visualization 101
14. Creating a data visualisation is a lot like cooking. You
decide what data you need, you collect it, you prepare
and clean it for use, and then you make the
visualisation and present your finished result.
–Data & Design
16. Interval Categorical Nominal Ordinal Qualitative
Term Grade
No. of
Learners
No. of
classes per
grade
Favourite
Activity
Educators
comment
1 Grade 4 280 4 Soccer
“Classes are too
crowded and it is
difficult to attend
to all learners”
2 Grade 6 190 4 Dancing
“We need more
textbooks, learners
have to share”
28. 0
50
100
150
200
250
300
350
Gr 3 Gr 4 Gr 5 Gr 6 Gr 7
NumberofLearners
Number of Learners per Grade
BAR/COLUMN
Useconsistent
colours
UsesuitableAxis
intervals
Descriptivetitle
Spacebars
appropriately
UseHorizontal
Labels
Orderdata
appropriately
Startthe
y-axisat0
34. PIE/DONUT
29%
21%20%
18%
12%
Grade 3 learners love playing soccer
When asked to indicate what after school activity is their favourite, 29%
chose soccer. Following was Netball, tennis and dance at 21%, 20% and
18% respectively
Soccer
Netball
Tennis
Dance
Other
37. LINE
GRADE 3
GRADE 4
GRADE 5
0
10
20
30
40
50
60
70
80
90
100
Term 1 Term 2 Term 3 Term 4
AveragePercentage Learners Maths Scores in 2014
38. GRADE 3
GRADE 4
GRADE 5
0
10
20
30
40
50
60
70
80
90
100
Term 1 Term 2 Term 3 Term 4
AveragePercentage Learners Maths Scores in 2014
LINE Labelthelines
directly
USETHERIGHT
HEIGHT
UsesolidLINES
only
Includeazero
baseline
39. LINE
GRADE 3
GRADE 4
GRADE 5
0%
20%
40%
60%
80%
100%
Term 1 Term 2 Term 3 Term 4
Grade 4 achieves highest gains in Maths scores
The Grade 4s improved their maths scores by over 60% from an average
score of 25% in Term 1 to 89% in Term 4
44. SCATTER/BUBBLE
0
10
20
30
40
50
0 20 40 60 80 100
ExtraClassesAttended
Learners’ Literacy Percentage
Extra classes contribute to higher literacy scores
Learners who attended over 25 extra literacy classes achieved a literacy score of
50% or more.
46. INFOGRAPHICS are essential for making
data attractive & can include a number
of different DATA VISUALISATIONS
47. Both data visualization and infographics turn data into
images that nearly anyone can easily understand –
making them invaluable tools for explaining the
significance of digits to people who are more visually
oriented.
– Jonsen Carmack
56. Bradley Hand ITC
Brush Script
Courier New
Comic Sans MS
Juice ITC
Kristen ITC
Lucida Console
Times New Roman
Trebuchet MS
Tempus Sans
Papyrus
Verdana
60. ADOBE COLOR CC https://color.adobe.com/
DESIGN-SEEDS http://design-seeds.com/
FONT SQUIRREL http://www.fontsquirrel.com/
FLATICON http://www.flaticon.com/
FREEPIK http://www.freepik.com/
Early forms of data visualisation can be found in the form of maps and graphs dating back to the 1600’s
Data Visualisation is defined as a process by which data is presented in a visual or graphical format. The goal is to effectively communicate information to a diverse audience, in the form of visual data which is easily consumed and digested.
Your data is only as good as your ability to understand and communicate it, which is why choosing the right visualization is essential
–Data Visualization 101
In order to succeed in visualising data, there are many factors to consider. This includes; knowing your data, understanding the power of visuals as well as learning how to create appropriate graphics. It is also important to be aware of common data visualisation mistakes to avoid.
If your data is misrepresented or presented ineffectively, key insights and understanding
are lost, which hurts both your message and your reputation. The good news is that you
don’t need a PhD in statistics to crack the data visualization code. This guide will walk you
through the most common charts and visualizations, help you choose the right
presentation for your data, and give you practical design tips and tricks to make sure
you avoid rookie mistakes. It’s everything you need to help your data make a big impact.
With the increase in the use of graphics to disseminate information, reporting is in the process of a transformation.
This involves the use of creative visuals to produce attractive reports,
grabbing the attention of readers and ensuring that findings are not ignored.
Communicating data using visuals allows evaluators to showcase trends, correlation and outliers in interesting ways.
It also draws attention to the differences which exist in comparative data.
Findings can be conveyed using numbers, but to highlight certain results, visuals drive the message.
To accurately create visualisations, it is important to understand your data. This involves identifying the types of data that can be visualised, ensuring that your data is consistent and accurate as well as aggregating data to discover trends, correlations and outliers.
It is necessary to know the type of data you are working with as it determines how it can be visually communicated.
Basic data groups include; quantitative (nominal, ordinal, interval and ratio), qualitative and categorical.
Data cleaning and aggregation
Data should be collected and processed thoroughly to ensure consistency which will produce accurate results for analyses.
Aggregation of data is necessary to identify patterns in your data which translate into key findings. These processes are necessary to isolate key messages to highlight using appropriate data visualisation.
Knowing your data helps with deciding which and how much data to illustrate when creating a visualisation. Consider these three questions
The first aspect to be considered is the type of graphic most appropriate to illustrate your data. Many different graphs and other visual methods can be utilised. The most commonly used graphs include:
Each of these graphs can be used in several ways to display different types of data. Quick and easy changes to the standard format of these graphs can improve the appearance, making it more visually attractive and appealing to readers.
In Grade 3 30% belonged to the low achievers, 33% belonged to the medium achievers and 33% belonged to the high achievers.
Data Visualisation is defined as a process by which data is presented in a visual or graphical format. The goal is to effectively communicate information to a diverse audience, in the form of visual data which is easily consumed and digested.
Your data is only as good as your ability to understand and communicate it, which is why choosing the right visualization is essential
–Data Visualization 101
In order to succeed in visualising data, there are many factors to consider. This includes; knowing your data, understanding the power of visuals as well as learning how to create appropriate graphics. It is also important to be aware of common data visualisation mistakes to avoid.
including graphs, charts, quotes, icons and pictures
Infographics use these elements combined with appropriate use of colour and fonts to present results and findings in a visually appealing graphic.
Use abobe color cc to find suitable colour combinations
Note grayscale printing
Don’t forget to provide context for your visuals and a supporting narrative.