I have introduced the term "Data Practitioner" as a generic job descriptor because we have so many different job role titles for individuals whose work activities overlap including Data Scientist, Data Engineer, Data Analyst, Business Analyst, Data Architect, etc.
For this story we will answer the question, "How much do we get paid?" Your analysis and data visualizations must address the variation in average salary based on role descriptor and state.
Kaggle Link: https://www.kaggle.com/datasets/juanmerinobermejo/data-jobs-dataset/code
Hide Assignment Information Instructions I have introduced the term "Data Practitioner" as a generic job descriptor because we have so many different job role titles for individuals whose work activities overlap including Data Scientist, Data Engineer, Data Analyst, Business Analyst, Data Architect, etc.
For this story we will answer the question, "How much do we get paid?" Your analysis and data visualizations must address the variation in average salary based on role descriptor and state.
Notes:
- You will need to identify reliable sources for salary data and assemble the data sets that you will need.
- You will complete these visualizations in Python with only the matplotlib package.
- Your visualization(s) must show the most salient information (variation in average salary by role and by state). Again, I want no more than two - visualizations, so think how to display the data.
- For this story you must use a code library and code that you have written in R, Python or Java Script (additional coding in other languages is allowed). Post generation enhancements to you generated visualization will be allowed (e.g. addition of kickers and labels).
- Again, I want no more than two visualizations, so think how to display the data.
- Provide your visualizations and a single paragraph about how they answer the question along with8 conclusions about that question.