Quartiles are good; I would be curious about deciles as well.
Unfortunately my primary data source, the US Bureau of Labor & Statistics, only reports 10th percentile, 25th percentile, median, 75th percentile and 90th percentile. I’m working on creating two different views: the “simple” view which just has a few relevant numbers, and the “full” view which has all the relevant data.
When I mouseover a line on the salary vs. age graph, the numbers are shown with the lowest salary on top. This is visually disconcerting as the lowest salary line is the bottom-most one on the graph.
I’ve gotten a few pieces of feedback on this. This is the default for how the chart generator API I’m using creates the legend. I’ll have to go in and update the code on that to reverse them.
It’s a bit confusing that the y-axis on the salary vs. age graph rescales to the occupation, especially since the lines are shown “rising up” from the x-axis. If I see the lines go up, it unintuitively does not mean that the salary is higher.
Do you mean like when you are looking at Job A, and then move over to look at Job B? If so, would it be more useful if the graph just consistently showed, say, $20,000 a year as the minimum and, say, $200,000 a year as the maximum, regardless of occupation? (Or any other arbitrary min/max)
There seem to be lots of duplicate categories at the “Individual Job” level, so less unique rows fit on a screen. Might be an easy way to filter these out.
This is an annoying quirk of how the BLS quantifies different positions (i.e. many positions have two separate ID codes but the same underlying data.) Version 2 will purge any redundancies like this.
I’m confused whether “entry level” means “no degree” and “post-grad” means “bachelors”
I could be more clear on this. “Entry level” means “no degree or bachelor” and “post-grad” means “masters or doctorate or equivalent”.
It would be nice to have a link on the “Individual Jobs” level to the definition of each job category used by the Bureau of Labor Statistics.
This has been updated. See below for further explanation:
How many years are you taking this from? Larger n makes things more robust but makes the data less relevant to the current job market.
This currently pulls from 2014 data. Version two will have the option to pull from several years and also will include a timeline to show whether salaries for a job are trending up or down.
I’d like to know the salaries of the top and bottom deciles for each job.
The “High Salary” and “Low Salary” from the individual job breakdown is actually the 90th decile and 10th decile, respectively. I just didn’t scale those according to age in the chart itself.
I don’t really know why i would care about the Category ID. It seems to be an unnecessary column. It is also confusing that it starts at 11 (not 1) when I sort in descending order.
Good point. At one point I had intended to use the category ID to link to the BLS’s definition of the job. But then I forgot! I have updated this. I should probably have the field itself be something more useful than the ID though.
I initially misinterpreted the “Entry Level Jobs” and “Post-Grad Jobs” as salaries
Just wanted to give you a shoutout. This is a great idea! And yes, has valuable non-overlap with 80k.
edit 1: forgot to say—if you can find data on the effect of a entering a job, that may be particularly useful. I have yet to come across such a data set, but look for one occasionally. For example, a highschool student may see your data and say wow, an Estimator has it good. Yet, estimators often have to have experience in other construction occupations first. So, if there is data from which you can select the population of high school students who have entered jobs, you can control for those factors.
Do you mean like when you are looking at Job A, and then move over to look at Job B? If so, would it be more useful if the graph just consistently showed, say, $20,000 a year as the minimum and, say, $200,000 a year as the maximum, regardless of occupation? (Or any other arbitrary min/max)
Thanks for the feedback! Some specific notes:
I’ve gotten a few pieces of feedback on this. This is the default for how the chart generator API I’m using creates the legend. I’ll have to go in and update the code on that to reverse them.
Do you mean like when you are looking at Job A, and then move over to look at Job B? If so, would it be more useful if the graph just consistently showed, say, $20,000 a year as the minimum and, say, $200,000 a year as the maximum, regardless of occupation? (Or any other arbitrary min/max)
This is an annoying quirk of how the BLS quantifies different positions (i.e. many positions have two separate ID codes but the same underlying data.) Version 2 will purge any redundancies like this.
I could be more clear on this. “Entry level” means “no degree or bachelor” and “post-grad” means “masters or doctorate or equivalent”.
This has been updated. See below for further explanation:
This currently pulls from 2014 data. Version two will have the option to pull from several years and also will include a timeline to show whether salaries for a job are trending up or down.
The “High Salary” and “Low Salary” from the individual job breakdown is actually the 90th decile and 10th decile, respectively. I just didn’t scale those according to age in the chart itself.
Good point. At one point I had intended to use the category ID to link to the BLS’s definition of the job. But then I forgot! I have updated this. I should probably have the field itself be something more useful than the ID though.
I’ve updated that to be more clear
Just wanted to give you a shoutout. This is a great idea! And yes, has valuable non-overlap with 80k.
edit 1: forgot to say—if you can find data on the effect of a entering a job, that may be particularly useful. I have yet to come across such a data set, but look for one occasionally. For example, a highschool student may see your data and say wow, an Estimator has it good. Yet, estimators often have to have experience in other construction occupations first. So, if there is data from which you can select the population of high school students who have entered jobs, you can control for those factors.
Cool, glad to hear of the improvements.
Yes, and I think that would work.