Where is the money ($)? C Programming or Python?
Last Updated: 2025 April 26 (Thu Apr 24 2025)
- C, embedded systems
- Python,
spyingdata mining - ‘Takeaway’ is an annoying word but I’m told I should write one
Let’s take a deeper look at annual compensation beyond averages and compare apples and oranges.
If you learned a programming language, how much money can you expect to earn from a specialization where the language is dominant?
What pay is a good starting point?
How will your skills appreciate with each year of experience? If not, at what point will there be a plateau?
Try out the code or run your own experiments at
https://git.projectsegfau.lt/scuti/stacksurvey
The data set (2024):
https://survey.stackoverflow.co/
C, embedded systems
Among C programmers, the magenta regression indicates an early-career professional working in any of the three specializations game/graphics programming, embedded systems, or hardware engineering will earn around $54,776 ± 21,000. With each year of experience, they earn $11,973 more.
Most C programmers who have responded to the survey are under the age of 34. Not as much data is available for professionals with more than 10 years of experience; therefore, beyond 10 years of experience, the model becomes unreliable.
About 57% of the variability in income is explainable by years of experience. Other sources of variability may include part-time positions or companies of different sizes.
Model details for the brave
+----------------------+
magenta regression line for C
coefficient = 11973.47
intercept = 54776.27
rmse = 21198.61
r2 score = 0.57
sample predictions:
[[132396.26294684]
[119937.35465744]
[ 64985.1549115 ]]
+----------------------+Python, spying data
mining
For data scientists, analysts and engineers using Python, the story is much different as the graphs look like a splash of water that bifurcates.
- their starting income is around $82,957.69 then an extra $10,378.53 with each year of experience
- or they earn $123,479.15 per year then an extra $2,573.62 with each year of experience.
- at any given point, the model is off by $40,000.
Unfortunately, 34-38% of the variability in incomes is explanable by years of experience. As the two regression lines are similarly performing, there may be a fork in the career path. Data scientists, analysts, and engineers are employed in a broad range of fields from advertising to finance and more. Therefore, how much they get paid may depend on that more than experience.
Model details
+----------------------+
red regression line for Python
coefficient = 2573.62
intercept = 123479.15
rmse = 39759.45
r2 score = 0.34
sample predictions:
[[126052.77118246]
[174951.60602361]
[187819.7204555 ]]
+----------------------+
+----------------------+
cyan regression line for Python
coefficient = 10378.53
intercept = 82957.69
rmse = 42374.26
r2 score = 0.38
sample predictions:
[[139882.01866593]
[117229.55243376]
[137277.30441955]]
+----------------------+‘Takeaway’ is an annoying word but I’m told I should write one
I’m not here to be a career counselor.
There’s more money in data science than low abstraction programming. While you shouldn’t be dissuaded from your passions, if you’re aiming for an income greater than $200,000 per year, you ought to come up with a plan of what to do after 10 years into your career.
Thanks for reading! Who doesn't love comments? Let me know what you think on my guestbook by e-mail or neocities.