This research project aimed to investigate reasons why women are generally more disadvantaged in the workplace than men.
The project is separated into 3 parts of comparison between genders: years of experience, job titles, and annual salary.
For each section, I identify the discrepancy in data, or the lack thereof, and explain its social causes and impact using peer-reviewed research.
The analysis of specific job titles' correlation with higher pay can be found at https://payyup.wordpress.com/job-title/. I used pandas and matplotlib to aggregate and filter the top 5 and top 20 highest earning words in a job title and the distribution of two genders (m/f) who own these titles.
This research uncovered many "silent" variables like unpaid maternity leave and statistical discrimination in the workforce. Some of these factors cause mothers to step down from the workforce permanently. Other factors cause female workers not as likely to get promotable projects as their male counterparts. Not to mention the prevailing sexual harassment that females experience in the workplace (STEM female workers especially due to work environments that are majority male).
Full reporting and analysis of this research could be found https://payyup.wordpress.com