#datathatinterestsme

British Prime Ministers 1905-2019

British Prime Ministers 1905-2019_boris.png

British Prime Ministers 1905-2019

Interactive viz

Source: Wikipedia


Description

Well I was frankly ecstatic to get my first VOTD on 1st July 2019. British Prime Ministers 1905-2019 – WHO’s NEXT?

VOTD.png

After a month of hustings, the race to replace Theresa May as leader of the Conservative Party has reached its climax. Boris Johnson has been named as the new UK Prime Minister on Tuesday 23rd July 2019.

On 6th July, voting opened up to the Conservative Party’s 160,000 members, who have chosen the winner. The final deadline for party members to vote was the week ending Sunday 21 July. The candidate achieving more than 50 per cent of the vote among party members was declared leader of the Party. The winner, and new Prime Minister.

Viz Type

Curvy timeline with plenty of hover over interactivity.

The challenge and ‘how I constructed the viz’

How on earth do you show a time range spanning over 100 years?

With a curvy time line of course! for which which all credit goes to the method created by Ken FlerlageCurvy timeline

If you want to construct a time line like this, have a good read of this very informative post detailing the method as I think it looks really cool, and enables you to fit in all those years by snaking them up/down the page.

thanks for reading

Adam

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#datathatinterestsme

IRONVIZ MUSIC 2019

MUSIC FUNDAMENTALS_IRONVIZ MUSIC

Music theory fundamentals

Interactive viz


Description

Tableau really triggered a wave of enthusiasm for this IRONVIZ contest, blending peoples love for music with their passion for vizzing, frankly the level of submission has been unbelievable, there have been some exceptional visualisations covering classical to gangster rap. and everything in between.

For me it also struck a ‘chord’, some know that my educational background is in Music and the academic study thereof. My musical journey began back in 1985 when I picked up a trumpet at the tender age of 5 to have lessons at school. My first Trumpet was given to me by a family member whom gigged jazz standards for many years. I loved that battered old horn, and it inspired me to progress through many classical orchestras, swing bands, brass bands and the occasional covers bands.

Slightly later I began to learn the Piano, and completed all the necessary grades and exams in both performance and theory to get me into university to do a Bachelor of Arts in Music and later a Master of Music by Research in Electro Acoustic Composition and Sonic Arts. Which inadvertently led me to where I am today in data visualisation, having spent many hours exploring music and sound, data analysis and computer science techniques. with a goal to building live improvising systems to jam with – All in the name of Art.

However I have rarely blended Viz with Music, so really looked forward to submitting something for this round.

Question was – where to start? I had so many ideas but decided to really take the concept back to some fundamentals of music theory and practice, rather than an analysis piece of dataviz using big or complex data sets. The challenge I decided to set myself was one of attempting to present some of the key fundamental building blocks of music theory and understanding, as a learning (Educational) tool for understanding a little bit about music and how it works.

  • What are chords, how are they made up (I only had time to look at Major chords but would like to expand this at some point to cover the full circle of fifths diagram with Minor chords and key signatures too)
  • If you know what notes make up simple chords, how could you actually play these (on a piano for example).
  • The medium for music is aural not visual and you can’t grab hold of it, however how could I bring the visual to the table and introduce an explanation of what sound looks like and how it works?

I have been very occupied with the notion of KISS and the principle of keeping a visualisation simple to enable easier perception, interpretation and comprehension of data. I feel my approach to this IRONVIZ, is no different. However it took some very non KISS Tableau techniques to try and visually achieve a somewhat simple resulting viz in the time frame.

 

Viz Type

  • Buttons – Circle mark types
  • Circle of Fifths – Radar chart
  • Piano keys – Custom chart
  • Piano key notes – Floating mark type circle on a custom x y dataset
  • Sine Wave – Line chart

 

A quick ‘how I constructed the viz’

Key techniques for creating this dashboard were as follows;

  • Radar Chart – go to resource Ellen Blackburn – Information lab Data School – A simple way to make a radar chart
  • Piano Keys – totally indebted to Klaus Shulte and Lodovic Tavernier’s TC19 talk where they introduced me to spotify Coordinator – a A visual interface for turning an SVG into XY co-ordinates, in their talk on “Creating advanced unique charts”
  • I also reached out to the legend that is Ken Flerlage to help me get the correct trigonometry calcs working achieve the sine waves.

The Circle of fifths

I admit a took a bit of a short cut with this and floated the polygon shapes on top of a base chart which depicts the circle of fifths. Mainly because i didn’t want to go back and data prep.

The Keyboard

keyboard

  • The output from Spotify Coordinates, spits out a a csv for X and Ys, with a bit of clean up and generation of a Path Column it is fairly easy to render this pretty cool piano in tableau using simple X and Y data – crazy hey!

The sine wave

Frequency_calc

 

The data

There really isnt much of it, a few rows Alteryx’d for the 12 rows of data relating to the chords and related notes used for the circle of fifths and actions throughout, The keyboard coordinates which were helpfully generated for me by coordinator, and a few rows to log each of the 12 frequencies relating to each of the notes on an octave, and a densification table to allow the curve to be plotted on the sine wave (line).

Thanks for reading, drop me a message if any of this sounds interesting.

Adam

 

 

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#VisualisingHE

Fun and frolics with HESA Finance

KFI OverviewV2_final.png

Key Financial Indicator (KFI) Scorecard

Interactive viz

Source – HESA Finance


Description

Back in March 2019 HESA ‘sprung’ a never-before-public release of HE provider institutional finances. Prior to 2019 this level of institutional data has been available to key contacts within institutions through HEIDIPlus platform within institutions – and paying customers. However as part of HESA’s open data programme we can access and visualise more than ever before.

Key Financial Indicators or KFI’s for short, are compiled using information provided to HESA as part of the HESA Finance record. The KFI’s defined and shown below are a set of ratios extracted from the finance record. They are not performance indicators and take no account of provider-level characteristics such as the range of subjects taught or the types of provision provided.

My aims for this viz was to hone my KISS (Keep it stupidly simple) approach to data viz design, all effort were to try to pack a punch with simple clear presentation of data and key provider level takeaways from the indicators.

 

Viz Type

  • Coloured BAN
  • BAN (up and down arrows)
  • trend line
  • distribution chart (bar)

 

A quick ‘how I constructed the viz’

There isn’t much going on here in terms of techniques, however a couple of things to mention are:

  • Coloured BAN – avg(1)
  • up and down arrows – copy this into your custom format: ‘▲0.0%;▼0.0%’
  • Love thy Containers – Thanks to both Elena and Lorna i’m beginning to love the container

For the coloured BAN,

  • Add Avg(1) and set the axis from 0-1
  • turn the mark type to bar
  • set the size to max
  • Add a calc provide a 1 or 0 for setting colour: eg [Benchmark Value Ratio]>=[Provider Value (Ratio)] then ‘0’ else ‘1’ END

avg1

For the layout I embraced my inner container love to achieve the clean look and control over the dashboard elements (text and charts)

containers2

  • Each metric is a container with 2 containers within it, one for the metrics header, one for the charts, the charts one set to distribute evenly. Each container has the height set (40, 200) to ensure they are distributed evenly per metric.

 

#VisualisingHE blog post published here: Frolicking with Finance

Thanks for reading

Adam

 

 

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#Makeovermonday

#Makeovermonday | C02 Emissions per capita

Co2 emissions per capita.png

World C02 Emissions

Interactive viz

Source –World Bank


Description

Makeovermonday wk22 2019 looked at Co2 emissions per capita. This week I decided to go for clean and simple and try and present the whole dataset in one visual, drawing out the TOP10 countries (in red), this week following a more #SWDChallenge styled visual, showcasing a clear headline, key takeway, and presentation of the data subject.

Viz Type

Bar code chart (utilising the Gantt mark type)

A quick ‘how I constructed the viz’

Key technique for creating this dashboard were

  • Gantt chart mark

To do this simply select a gantt mark type and add country onto detail

Adam

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#Makeovermonday

#Makeovermonday | Bear attacks in North America

Bear attacks in North America_MOM2019wk21.png

Bear attacks in North America

Interactive viz

Source – Wikipedia
NOTE: The data was collected, prepared, and distributed by Ali Sanne on data.world.


Description

Makeovermonday wk 21, This weeks dataset was fairly simple but I wanted to make a visual statement with the visualisation, so opted for creating a human footprint to depict the charting of the human fatalities with hover over capabilities to see relevant details.

Viz Type

  • Running sum (line chart)
  • BANS
  • Bars
  • filled shape

A quick ‘how I constructed the viz’

The only key technique worth noting here is the creation of filled shapes to create the footprint. For that I thank Kevin for his great post and method described in his blog creating filled shape charts in tableau.

Adam

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#Makeovermonday

#Makeovermonday | NASA Space station space walks

Spacewalks.png

Boldly leaping where few have ventured before

Interactive viz

Source – Space station spacewalks


Description

Makeovermonday Wk16 2019, brief: Visualise the international space station spacewalks.

I decided to throw data viz good practice ‘into space’ for this week MOM and have a go at an arc chart. Why? well simply because I fancied doing one and it looks a little like a leap…..

Viz Type

  • Arc Chart
  • Packed bubble…

A quick ‘how I constructed the viz’

For this dashboard the techniques used for this viz revolve around creating the arc chart, the rest were simple design and faffing to do my best to produce an engaging viz.

Rather than re quote a how to on arc charts here is my go to for how to make em: doingdata.org

Adam

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#datathatinterestsme

#Ironviz Europe | Plastic

Plastic

Plastic

Interactive viz

Source – Plastic Pollution


Description

For Ironviz Europe I decided to take a very simple approach: #TableauKISS stylee. Which for me meant sticking to what I know by aspiring to produce a clean viz that ticked judging criteria of; design, story telling and analysis by KEEPING IT STUPIDLY SIMPLE! No fancy charts, just pretty much out of the box tableau, but focusing on the clarity of design and ease of reading.

Viz Type

  • A line chart with annotations
  • A stacked 100% bar chart with side labels
  • A scatter plot and zoom in with cluster analysis (see how I)
  • A bar chart
  • And a slightly funky bar chart to group to try and create a TOP5

 

A quick ‘how I constructed the viz’

There really isn’t not much technical stuff happening here, but here’s a summary of the techniques:

  • cluster
  • actions
  • standard formatting, highlights using the box colour

For the cluster zoom in, I have simply floated a second scatter plot above a speech bubble image with an action filter on the clusters to act as a zoom in

cluster

How did it do?

TOP10 🙂

Adam

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