Link to guided project: https://app.dataquest.io/m/348/guided-project%3A-clean-and-analyze-employee-exit-surveys/11/next-steps
Link to notebook: https://github.com/bhvya1505/Cleaning-and-Analysing-Employee-Exit-Survey/blob/master/Basics.ipynb
I would like to know if there is a way to find any meaningful correlation between the two results.
Hey @bhavya
Great project!!, very well structured. It was a good read.
Just a few suggestions. One, you can customize the size of your plots to look bigger. The plots are key points you are trying to show, hence they should stand out. Second,
You could try the same analysis you did for the service category and age category on other columns (will maybe have to convert it into categorical) and observe the trend. In the end you could conclude the general subset of people dissatisfied with their jobs based on various categories and their intersection. 
Thanks
Raj Tulluri