Analytics Vidhya
Published in

Analytics Vidhya

Is Passion the Only Factor That Influences Job Satisfaction for Developers?

Data Driven Approach Using Survey Data — Stackoverflow

From Unplash by Shrdhar Gupta

“If you do what you love, you’ll never work a day in your life.”

Many of you may have come across this famous singer Marc Anthony’s comment. I’m also one of those people who believes that you should do what makes you happy. The world, however, is big, and there are many different types of people working in various sectors, cultures, and job streams. There are some people who are fortunate enough to be content with what they do on a daily basis, and others who are not so fortunate.

Let’s take a look at what the data indicates using publicly available data from Stack overflow’s Annual Developers Survey for the year 2020. The survey was conducted in February 2020, before COVID-19 was declared a pandemic by the World Health Organisation, as indicated on the website. As a result, there is a slight chance for the outcomes during the pandemic and after the pandemic periods to differ.

This dataset contains responses from around 65,000 people who represent various categories of people. Let’s minimize our scope such that the dataset’s variability is reduced. I choose,

  • Full-time personnel who are Developers by profession
  • Aged between 15 and 60 years
  • Who has responded to the survey question about whether or not they are content with their employment.

This gave me a total of 28K respondents in my database. So let’s get to work sifting through the information.

The majority of people are satisfied with their jobs, as represented by the very satisfied and slightly satisfied blocks, with only around a quarter dissatisfied, as indicated by the slightly dissatisfied and very dissatisfied areas.

Image by Author: Satisfaction rates

In order to continue with the analysis, I divided the five groups above into three categories, each of which specifies whether a respondent is satisfied, unsatisfied, or undecided.

Here are some interesting facts discovered while analyzing the data.

1. Is it true that persons who code as a hobby have higher levels of job satisfaction than those who do not?

We can presume that persons who code as a hobby are those who are enthusiastic about it. As a result, there is a lower risk that he or she will be unsatisfied with the employment. The data, on the other hand, suggests otherwise.

Image by Author: Respondent percentages by hobbyist vs job satisfaction

The ratio of satisfaction to dissatisfaction does not alter significantly whether you do it as a hobby or not. That is to say, even if you are passionate about coding and are fortunate to have landed a job, there are other aspects that influence your job satisfaction.
Now that we’ve established this fact, let’s go on to the next step.

2. Is the percentage of satisfied and unsatisfied respondents similar across countries?

The questions were answered by people from 150 different nations. The majority of the participants are from the United States (24%), India ( 10%), the United Kingdom ( 7%), and Germany (7%).
In order to decrease analytical error, I will only look at nations with at least 30 respondents, which will include 70 countries.

Image by Author: Top 10 of each highest satisfied and unsatisfied rates having nations

Satisfaction levels varied from 70 to 75 percent, while dissatisfaction levels were between 30 and 50 percent.
The majority of respondents appear to be satisfied in most countries, but the 30–50 percent ranges are worth investigating.

3. Does your age or gender have an effect on the distribution of job satisfaction rates?

Millennials are often stereotyped as a generation that jumps from job to job, and is easily dissatisfied. As a result, it’s possible that age plays a role in this. Furthermore, there are fundamental variances between male and female, which could result in a distinction. As a result, these characteristics may have an impact on satisfaction and dissatisfaction rates.

Image by Author: Distributions of Age and Gender

Because the average age is similar across all categories and the satisfied to unsatisfied ratio does not differ significantly between men and women, we may assume that there is no substantial difference in job satisfaction across ages or gender.

4. Is there a link between working hours and job satisfaction?

Image by Author: Distribution of respondents across work week hour bins

We divide the work week hours into four equal ranging bins in order to analyze the data.Most people appear to work somewhere between 28.5 and 49 hours each week. When looking at satisfaction and dissatisfaction rates, it appears that if you work less or more (28 hours per week or more than 69.5 hours per week), the dissatisfaction rate increases. The best option appears to be the midway ground.

Let’s see whether gender and doing this as a pastime have any bearing on the outcomes.

Image by Author: Hobby-Gender-Work hour classifcation of rate of dissatisfied repondents. Highlighted is the count of respondents < 30

Men who work more than 69.5 hours per week without coding as a pastime appear to be the most dissatisfied, followed by women who work more than 49 hours per week. Women, whether they do it as a hobby or not, have become unsatisfied. There is insufficient data to determine women who work more than 69.5 hours per week and do not have a coding interest.

Overall, it appears that working more or fewer hours has led to unhappiness, and whether or not one is a hobbyist, as well as gender, may have an impact on dissatisfaction in relation to working hours.

5. What are the key factors which people look for in a job?

“Imagine that you are deciding between two job offers with the same compensation, benefits, and location. Of the following factors, which 3 are MOST important to you?”

This is one interesting question asked at the survey.

Image by author: Most important factors when looking for a job

As developers, it’s no surprise that the working languages/ frameworks/ technologies are of paramount importance. Then there’s the workplace culture, and thirdly, there’s the work schedule flexibility. These appear to be consistent across persons who are content, unsatisfied, diverse age groups, and genders.

Another interesting question is ,

“In general, what drives you to look for a new job? Select all that apply.”

Image by Author: Fraction of responses for factors looked when applied for a new job

Better compensation, the desire to learn new technology, curiosity, growth, work-life balance, and so seems to be the most important aspects of an employment. This tendency was essentially identical among all respondents, disgruntled persons, job seekers, and others.

However, because this is a problem that should be closely linked to the countries where people work, let’s look at countries where the majority of respondents are satisfied against countries where the majority of respondents are dissatisfied.

If we look at the top 5 to 6 countries with the highest satisfaction ratings (Lithuania, Denmark, Latvia, Norway and Sweden), we can see that the top common criteria are,

  • desire to work with innovative technology
  • Better remuneration
  • curiosity in other options

where as, the common characteristics for

  • higher compensation
  • better work-life balance

can be found in the top 5 to 6 nations with the greatest dissatisfaction rates (China, Dominican Republic, Egypt, United Arab Emirates, Chile and Bangladesh).

So it appears that even dissatisfied employees in countries with higher satisfaction rates are looking for new jobs to work with new technology with better remuneration and for the sake of curiosity, whereas dissatisfied people in countries with higher dissatisfaction rates are more focused on a better work-life balance as well as better pay.


So, based on this short exploratory research, we can assume that it is not only your passion that makes you happy at work, but also other things such as the technology you deal with, salary, and a better work-life balance. Gender and age have no direct impact on this, but when it comes to working hours, people tend to be unsatisfied with a little gender distinction as well.

It’s worth noting that as the data is dissected into more dimensions, the data becomes sparse. With more data better accuracy could be gained. If you need further in-depth study of the code, you can get it from the GitHub repository.

Further, this is a straightforward exploratory analysis that explains what the dataset portrays. In order to get conclusions, statistical analysis should be carried out, and algorithmic approaches could be employed to portray higher level interactions between variables.




Analytics Vidhya is a community of Analytics and Data Science professionals. We are building the next-gen data science ecosystem

Recommended from Medium

Predicting Credit Card Fraud From Transaction Information

What Are The New Features/plans Indulged In Microsoft Outlook 2016

A Simple Guide to Object Oriented Programming for Data Scientist

Getting started with Statistics

Why and when should you invest in a business intelligence software?

Exploratory Data Analysis for Digital Marketing with Seaborn

Data Analytics and Its Applications in Various Domains

Understanding the 5 Stages of Data Analysis Using a Simple Online Survey About Favourite Colors |…

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
Dinusha Dissanayake

Dinusha Dissanayake

Data Scientist

More from Medium

Three decades of Lego — a data science project

My journey into Data Science

The First Step to become a Data Scientist

What is Data Science?