safleoedd terfynol

Interactive viz:
Final rankings (safleoedd terfynol)

Description:

A visualisation showing the final TOP10 rankings for the Tour de France 2018, highlighting the final time splits. This years tour put the riders in the seat for some 83 hours, 17 mins and 13 seconds (or three and a half days!) over 23 days (21 stages with just two rest days).

Viz type:

A simple chart made using a shape and some text, nothing special….

How:

As with most of my vizzes most work goes into bringing out the text I wish to emphasise  by spending a bit of time formatting of each of the text dimensions – slow and a bit annoying but worth it.

TOP Spot info square:

Welshes own Geraint Thomas wins this years tour by nearly 2 mins.

Source of dataviz: 

Cyclingnews.com

thanks for reading,

hope this has been useful.

Adam

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Proportion of 1sts

Interactive viz:
Proportion of 1sts

Description:

A visualisation showing the proportion of 1st class honours degree issued by UK providers in 2016/17, redesigned for the #SWDChallenge July18 – a makeover month

Viz type:

A simple Bar chart nothing special, but (in my opinion) a slightly improved version from the pink vertical bar visualisation.

Source of dataviz: 

UK REFORM

thanks for reading,

hope this has been useful.

Adam

Drip drop

Interactive viz:
UK HE | Water consumption | Estates Management Record

Description:

A visualisation showing the water consumption of UK HE providers in 2016/7 adding a little context to how much it equates to, to try and get my head round how much water that really is!

Viz type:

A simple Bar chart and some BANs and use of images for illustration.

How:

This one uses a simple upside down bar chart and an awful lot of floating images and text!

The only cheeky bit of formatting used is the fixed axis min and max. the Min is set to 0 and the max is set to the largest provider consumption (not the total vol), this enables the viz to open with the ‘total consumption’ but then alter based on the provider selection as you interact with the data.

The only other thing to do then is create the BAN’s to float on top of the images managed by dashboard filter actions to change the figures as you explore the providers consumption.

The contextual info relating to the no. swimming pools and no. of baths, is a couple of simple calcs to work out the vols based on the value (m3) measure created by a couple of google queries of “how much water does a standard 50m swimming pool/ standard bath hold?”

Blog:

A tour around the estate

Source of dataviz: 

How do UK providers manage their estates

thanks for reading,

hope this has been useful.

Adam

Pedal Power

Interactive viz:
UK HE | No. of cycle spaces | Estates Management Record

Description:

A visualisation showing which UK HE providers have created the most number of designated cycle spaces across their estates – Yes this is a stat!!!!

Viz type:

A simple Shape mark with some semi creative use of some labels and discrete measures.

How:

Well this one uses a simple custom shape to plot the provider as a flaticon ‘bike’ image. Using the RANK function you can create a rank of the measure (value), drop that on the filter to show only the TOP10, Next copy this as a discrete measure and use it on the column shelf allowing you to nest the 10-1 ranking along the top.

To achieve the volume and provider detail that sits under the bike image, simply drop the value and the provider on labels, format them and set the alignment as bottom centre to sit them under the bike image.

simply a viz of ‘filtering’ and ‘faffing’ with labels and ‘formatting’! but i think it is stronger and more fun than a simple rank order list!

Blog:

A tour around the estate

Source of dataviz: 

How do UK providers manage their estates

Who’s got the most buildings?

Interactive viz:
UK HE | No. Buildings | Estates Management Record

Description:

A visualisation showing which UK HE providers have the most number of buildings across their estates.

Viz type:

A humble Bar chart is the basis for this viz, with a bonus top for the ‘building’.

How:

Inspired by a Simon Beaumont visualisation for one of his #Makeovermonday vizzes I thought the estates no. buildings data set was a lovely source to present the data as a cityscape inspired depiction of the volume of buildings a provider boasts on their estate.

To achieve this viz you simply create a dual axis chart, the first being a bar, the second axis a ‘shape’ (you can assign different shapes to different categories e.g. location to create the impression of differing building types) but this viz looked cleaner with just using a ‘triangle’ or ‘play’ icon coloured the same as the bar.

Making use of a syncronised duel axis also gives you the flexibility to use multiple and differing positioned labels, the bar labels to provide the name of the ‘provider/HEI’, and the volume of buildings under the shape measure axis.

The background of the worksheet is set to a pinky hue to give the cityscape look.

Blog:

A tour around the estate

Source of dataviz: 

How do UK providers manage their estates

UKHE | Total Site Area (Hectares)

Interactive viz:
UK HE | Total Site Area (Hectares) | Estates Management Record

Description:

A visualisation of the total site area in hectares UK providers a mass across their estates.

Viz type:

It seemed shame not to use a tree map for this viz, given a tree map lends itself to present hierarchical data (UK region) along with representing area very well in a nod to a topological map.

How:

For this viz I’ve done nothing special to present the data, its a simple ‘show me’ tree map, with colour (light grey to dark grey) representing high (dark) to low (light) volume of hectares. The viz is strengthened in terms of interactivity with a few ‘actions’ enabling for filtering of the main viz (bottom) to show a specific region by clicking on the regional tree map overview viz (top).

Blog:

A tour around the estate

Source of dataviz: 

How do UK providers manage their estates

Thanks for reading, hope it was useful.

Adam

Hours spent in congestion | European cities

Interactive viz:

MOM wk20_In a JAM_congested cities

Description:

#Makeovermonday wk 20 – this weeks had a very simple, tiny weeny little dataset, and I like it when its like that!

Traffic jams struck me as a must for this dataset, so instantly wished to visualise this as a unit chart, I therefore made the necessary tweaks to the data source to allow for presentation of multiple cars to denote hours, to achieve this you need a row id for each category (city in this case) to reflect the number of cars you wish to show

for example, the original dataset lookedwas:

and it needs to look like this (city=London example):

Takeaway:

• London tops out this selection of European cities where it is estimated that a commuter spends an average of 74 hours stuck in congestion (based on 240 commuting days)
• That’s an average of 18.5 minutes per day, an equivalent of 2.1 days per year!

Source:

Euronews.com

Tag:

#Makeovermonday