Tag: income

Best Charts for Income & Profit & Loss Statements

A few months back I wrote about how Rackspace confuses their shareholders using bad data visualization in their quarterly reports.

Mort Goldman — one of my dear readers — pointed me to this great tutorial by Kamil Franek where he shows 7 ways to visualize income and profit and loss statements. Please visit Kamil’s blog for the details, I just copied the visuals here to share with you.

Maybe we should forward them to Rackspace as well 😉

Kamil uses Google/Alphabet’s 2018 financial reports as data for his examples.

Here are two Sankey diagrams, with different levels of detail. Kamil argues they work best for the big picture overview.

Example of summarized Sankey diagram chart of an income statement

Example of detailed income statement Sankey diagram visualization

I dislike how most text 90 degrees rotated, forcing me to tilt my head in order to read it.

An alternative Kamil proposes is the well-known Waterfall chart. Kamil dedicated a whole blog post to creating good waterfalls.

Example of detailed income statement waterfall chart

One of my favorite visualization of the blog were these two combined bar charts. One showing the whole bars stacked, the other showing them seperately. The stacked one allows you to discern the bigger trend. The small ones allow for within category comparison.

Love it!

Not so much a fan of the next stacked area chart though. In my opinion, a lot of ink for very little information displayed.

Example of percentage revenue breakdown area chart

The colors in this next one are lovely though:

Example of percentage expenses breakdown area chart — The next scatter plot/bubble plot was one that I had not expected.

I love how this unorthodox visualization really add insights, showing how different cost categories have developed over time.

There are some things I would tweak to make the graph more visually appealing though. Particularly the benchmark line is too rough in my opinion.

Example of expenses changes breakdown scatter/bubble plot

Very often, you don’t need a specialized graph, but a well-formatted table might be much more effective.

Kamil shows two great examples. The first one with an integrated bar chart/sparkline, the second one relying strongly on color cues. I prefer the second one, as it better shows the hierarchy in the categories with the highlighted rows.

Example of income statement table with sparklines

Example of income statement table with conditional formatting

Kamil takes it a step further in the next table, but I think they become less and less insightful as more information is included:

Example of a detailed income statement table for change analysis — Kamil’s final recommendation is this key metrics dashboard. Though I like the general idea, I am not sure whether this one works for me. Particularly the line graphs on the right don’t provide much insight. I don’t know whether the last but one dot is 20% or 5% or 50% or 0%. The lack of reference points allows it to be any of these values.

Example of a summary dashboard for income statement key metrics

If you haven’t yet clicked through, definitely check out Kamil’s original post.

There he shares his perspective on the advantages and disadvantages of each of these visualization types, and where they work best in his experience.

Also check out Kamil’s earlier post on How to Visually Redesign Your Income Statement (P&L).

Two Tinder Experiments: An Unequal Economy

I’ve seen a fair share of Tinder experiments come by, for instance, someone A/B-testing attractiveness with and without facial hair, but these new two posts on Medium are the best I’ve come across so far.

In his first experiment, this self-proclaimed worst online dater went catfishing. He made a Tinder account using stock photos of attractive and less attractive and old and young guys, looking and sampled some like ratio’s.

Basically, his conclusion was that “Tinder actually can work, but pretty much only if you are an attractive guy”

The statistics of the first experiment:
https://worst-online-dater.tumblr.com/post/99441021279/tinder-experiments

In the second experiment, the author decided to treat Tinder as an economy and study it as an (socio-)economist would:

The wealth of an economy is quantified in terms its currency. […] In Tinder the currency is “likes”. […] Wealth in Tinder is not distributed equally. Attractive guys have more wealth in the Tinder economy (get more “likes”) than unattractive guys do. […] An unequal wealth distribution is to be expected, but there is a more interesting question: What is the degree of this unequal wealth distribution and how does this inequality compare to other economies?
Original Medium Post by Worst Online Dater

The author notes some caveats of this analysis. First and foremost, the data was collected in quite an unethical way, by asking questions to 27 of the matches with the fake accounts the author set up. Moreover, self-report bias is quite likely, as it’s easy to lie on Tinder. Still, the results are quite amusing:

Basically, “the bottom 80% of men are fighting over the bottom 22% of women and the top 78% of women are fighting over the top 20% of men”

The Lorenz curve shows the proportion of wealth owned by the bottom x% of a population. If wealth was equally distributed the curve would be perfectly diagonal (a 45 degree slope). The steeper the slope, the less inequal an economy. The below shows the curve for a perfectly equal economy, the US economy, and the estimated Tinder economy:

Similarly, the Gini coefficient can be used to represent the wealth equality of an economy. It ranges from 0 to 1, where 0 corresponds with perfect equality (everybody has the same wealth) and 1 corresponds with perfect inequality (one dictator with all the wealth). While most European countries, and even the US, score quite low on this Gini index, the Tinder economy is estimated to be much more towards the lower end.

Finally, based on the collected data, the author was able to reduce Tinder Male Attractiveness to a function of the number of likes received:

According to my last post, the most attractive men will be liked by only approximately 20% of all the females on Tinder. […] Unfortunately, this percentage decreases rapidly as you go down the attractiveness scale. According to this analysis a man of average attractiveness can only expect to be liked by slightly less than 1% of females (0.87%). This equates to 1 “like” for every 115 females.
The good news is that if you are only getting liked by a few girls on Tinder you shouldn’t take it personally. You aren’t necessarily unattractive. You can be of above average attractiveness and still only get liked by a few percent of women on Tinder. The bad news is that if you aren’t in the very upper echelons of Tinder wealth (i.e. attractiveness) you aren’t likely to have much success using Tinder. You would probably be better off just going to a bar or joining some coed recreational sports team.
Original Medium Post by Worst Online Dater

Mapping Median Household Incomes in the US

The US Census Download Center contains rich information on its countries demographic data. Here you can find a piece of R code that uses the highcharter package in R to create an interactive map showing the median household per country.