This Guardian dataset contains world population by country from 1950 to the present day, predictions of population increase or decrease up to 2100, and percentage rises and falls over three time spans. These are estimates from the United Nations.
See what the Guardian did with it here: http://www.theguardian.com/news/datablog/2011/may/06/world-population-country-un
Take a look at the data set before you upload it into Silk.
Do you see any problems with it as it stands?
Anything need filtering?
Remember what we said about how Silk needs the top line of a dataset to include the categories by which you want to sift it?
The existing lines 1 and 2 don’t give us that. Line 3 does, so you need to make that the top line of your dataset before you import it into Silk.
You’ll need to delete lines 1 and 2.
What about the columns?
Look at columns A and B. Do you need these codes? Will they mean anything to readers? Best delete them before importing.
You will see there are columns for each year from 1950, and also columns for predicted populations at points in the future.
Are there too many columns?
Knowing how the population grew year by year is less important than revealing the general trends, so perhaps taking one year from each decade makes more sense?
You can always try various combinations as you visualise the data and see what works best.
Even if you go decade by decade you still get a lot of columns, and maybe numbers are less important that percentage increases. As there are predictions going up to the end of the century, and three columns of percentage changes over the full range of data, we should probably keep to a total of about 10 columns.
Here’s one option:
You need to decide what you want to draw out of the data. What’s the story you want to present?
Do you notice any really significant rises in population? Any significant decreases? What about the USA? This data shows a predicted 26% decrease between 2011 and the end of the century. What implications does that have, if correct?
Try various combinations of data under various visualisations.
Note: Make sure you set the ‘Maximum items’ at a high enough figure to get all countries in, otherwise you’ll find some towards the end of the alphabet left out. You’ll find ‘Maximum items’ under the ‘More options’ tab.
I’ve published a few variants of table visualisations here: http://world-population-by-country-975870.silk.co/
Key is the decide what type of visualisation works best for the data and then, with each type of visualisation, to decide how much data you can include.
A map is an obvious one, but you need to keep the amount of data pared back for it to work.
By using the various filters, you can have some information presented when you hover your cursor over the country pin, and additional information presented if you click on that pin.
Here’s a visualisation with country, 2015 population, and percentage change between 1950 and 2100 revealed on hover-over:
Clicking reveals, in addition, 1950 and 2021 populations:
Here’s that map published: http://goo.gl/9DFOp6
One final visualisation: here’s a bar graph showing population by continent, and as a world total , contrasting 1950 populations with that predicted for 2100.
Notice anything about Europe? Can it really be the case that Europe’s population will fall by 2100? If so, that might put the current migration from Africa and the Middle East into a wider context. Or maybe the data needs to be revised in the light of current population shifts.
Here again is what the Guardian drew from that data: http://www.theguardian.com/news/datablog/2011/may/06/world-population-country-un#data