I'm one of the editors on this — and would be happy to answer any questions...
To address the obvious: It's a lot of data. A pixel (roughly) for each of the 255 industries we chose to cover the private sector, for each month, for each of the past ten years. Sadly, it may bring your browser to its knees. I've tried some tricks to try and keep things moving along smoothly, but if anyone has any brilliant perf. ideas that aren't already incorporated, I'm all ears.
Obviously not a short term solution for this set of charts, but have you tried rendering this data on canvas? Looking at timeline, the framerate chokes whenever it has to render and recalc styles for all of those svg dom elements. A shorter term solution might be something like fabric.js's svg rasterizing http://fabricjs.com/svg-caching (no promises... just a thought).
I bet rendering this many points would really scream if you could use WebGL (though it would definitely be understandable if that doesn't have broad enough support for NYT).
Really awesome work though... any chance you could blog about your tricks or the making of this particular article?
For the first few minutes, I found these charts confusing, because the horizontal axis is labeled “<- Lower Wages Industries Higher Wages ->”, but within each chart, it represents time.
I’d recommend adding some kind of explanation/legend for this.
You're quite right that we're double-coding along the X-axis (and the Y-axis as well to a lesser extent). The introduction and the "How to read this chart" tooltip should help explain that, as should the year legend within each mini-chart ... but if you have a concrete idea about where we could place additional explanation to make it clearer, let me know.
(Note that you'll want to adjust those wages for inflation, and those jobs for population growth, depending on what you're doing.)
But our versions aren't really "cleaned up" in any meaningful way. The BLS already seasonally adjusts the jobs numbers for their CES series, which is super handy. Instead, go to the original source here:
... and walk through the wizard to pick which data points you'd like to include in your query. One big tip, once you're on the results screen, is to click on "More Formatting Options", and then choose the "Multi-series table" format. That'll give you something much easier to pipe into Excel or into a database.
The scroll effects at the top of the page make my browser weep. I keep getting stuck in weird half-states with the charts moving in and out of the intro text. The hovers are quite laggy. This is Chrome on a Macbook Pro.
Hi! This is the Market Economics Fairy! I would like to respond to whatever it is you're thinking, but I honestly don't know what exactly you're thinking! Increasing the supply of something almost always makes the price go down relative to what it would be otherwise! But then more trades take place too, so more gains from trade are generated, which is wonderful! More people getting paid high programmer salaries can increase the average per-person salary across the whole economy, even if it means the price per programmer goes down! So it's totally consistent for an altruist who wants more people to be paid more to try to introduce more people to programming jobs! The same with decreasing unemployment across the whole economy and increasing unemployment among programmers! But I don't know if that's the part you were confused about! Sincerely, the Market Economics Fairy!
Uuuhhh, correct me if I'm wrong, but if the number of actual jobs are going up (rather than job openings), it means demand and supply rose roughly in tandem.
On the other hand, there's simultaneously a lack of wage rises in most of the technology industry combined with extreme worker shortages in some parts of the industry, so it makes me think there's some vast inefficiency lurking somewhere keeping trades from clearing. My personal theory is: it's the Bay Area real estate markets. If we had a housing crunch in the place where companies want to hire workers that was observed to eat up most (though not all) available salary increases as increased rents, thus causing it to be uneconomical for employed experts in other areas to open their jobs by leaving for higher salaries in the industry's major center, leaving companies in the center locked in a zero-sum struggle to hire a shrinking pool of rich workers while increasing portions of the industry's labor force outside that one geographic area sit underutilized... it would look a lot like reality.
These "altruistic" individuals seem to have increased the job base by ~70% without a large negative impact on salaries, which is still well, well above the national average, and still affords a very comfortable lifestyle.
In other words, these "altruistic" individuals have vastly grown the number of people who can earn a comfortable life without large negative impact on the rest.
So between these guys and yourself, who is altruistic, and who is "altruistic" with scare quotes? Who is creating greater good for more people, and who is watching out for themselves?
I think the high salaries are attracting a lot of the code school grads who lack a lot of the fundamentals of CS. Anecdotally, I see these grads take 25-30% pay cuts for a developer position and employers are happy to take the discount in exchange for "on-the-job" training.
Think of it this way: when you use one statistic to describe both software engineers and programmers, it's going to look bad when there's an explosion of programmers, even if the number of and pay for software engineers remained the same.
The graph at the top of this page includes line charts for each industry, shaped by their change in employment over the last decade. The individual lines are placed on the x axis (horizontally) based on the average wages paid in that industry. They are placed on the y axis (vertically) based on the percentage change in employment since the start of the recession in December 2007.
If you scroll past the initial confusion, you get to all of the graphs plotted separately with nice titles.
I really enjoyed this, and thought the data was well presented. The first few graphs with the hundreds of lines were definitely more confusing (I didn't parse out the lower/higher wages aspect at first pass), but the walkthrough of all major industries with the dozens of subcategories as individual plots was quite interesting and clear.
I like the intent of this chart, but the Y-axis is a mess. Combining percent change from 2007 (as units for the y-axis) with roll-overs of actual numbers that contain data pre-2007 is very unintuitive.
To address the obvious: It's a lot of data. A pixel (roughly) for each of the 255 industries we chose to cover the private sector, for each month, for each of the past ten years. Sadly, it may bring your browser to its knees. I've tried some tricks to try and keep things moving along smoothly, but if anyone has any brilliant perf. ideas that aren't already incorporated, I'm all ears.