In How Many Links are Too Many Links, O’Reilly radar shows us this unfortunate bubble chart. (click on the image to see a bigger version)
I say unfortunate for the lack of a better word without sounding harsh.
Just in case you are wondering what that chart is trying to tell (which is perfectly fine)
Nick Bilton, who constructed this chart, got curious and went to the top 98 websites in the world and found out how many links they have on their home page. Then he used charting tools like processing to create the bathing bubbles you are seeing aside.
The conclusion ?
Too many bubbles can drown you. And also, top web sites have lots and lots of links on their home pages.
But seriously, apart from looking really pretty, does this chart actually provide that conclusion?
I think Nick and the O’Reilly radar team could have much better with a simpler and fortunate chart selection.
A histogram of # of links on popular home pages
like the one below would have been very easy to read and get the point.

I showed some dummy data in the histogram, but when you create 2 histograms, one for popular sites (ranked below 5000) and one for not-so-popular sites (>5000) you can easily make the point and use the bubbles for a warm bath.
A better alternative is to show a scatter chart
with site rank on one axis and # of links on home page on another axis, that way a conclusion like Top Sites Links More can be easily established.

Even a bar chart with number of links on each home page
could have been better than umpteen bubbles

You could easily add a bar with “avg. number of links on non-popular sites” to contrast the linking behaviour of large sites wrt small sites.
But alas, we are treated to an unfortunate bubble chart that does nothing but look pretty (and ridiculously large)
What do you think ? How many bubbles are too many ?
Recommended Reading on Bubble Charts: Travel Site Search Patterns in Bubbles, Good Bubble Chart about the Bust. Olympic Medals per Country
















6 Responses to “Nest Egg Calculator using Power BI”
Wow! What a Powerful article!
Hello Chandoo Sir
your file does not work with Excel 2016.
how can I try my hands on this powerful nest egg file ?
thanks
Ravi Santwani
@Ravi... this is a Power BI workbook. You need Power BI Desktop to view it. See the below tutorial to understand what Power BI is:
https://chandoo.org/wp/introduction-to-power-bi/
As always, superb article Chandoo... 🙂
Just one minor issue:
While following your steps and replicating this calculator in PowerBI, I found that the Growth Pct Parameters should be set as "Decimal number" not "Whole Number"
OR
we have to make corresponding adjustments in the Forecast formulas (i.e. divide by 100) to get accurate results.
You are right. I used whole number but modified the auto created harvester measure with /100 at end. Sorry I did not mention it in the tutorial.
Instead of
[Growth Pct 1 Value]/12
the monthly rate has to be
(1+[Growth Pct 1 Value])^(1/12)-1
It's a slight difference but in 30 years the future value will be $100k less.