Data Analysis using Excel Analyze job talent pool in data domain

1. What is data type of each of these columns? Why? (Identify if they are numerical

or categorical and also their sub-categories)

- Work year

- Remote Ratio

- Salary

- Experience Level

2. What are the top 10 roles with the highest average salary in USD in 2023? (Draw

a bar chart to visualize – Also include table or data labels on the chart)

3. Draw a bar chart for the top 10 most prevalent job titles in 2023, showing the

values in percentage instead of count (calculated as count of the role divided by

total number of roles). Include a table or data labels on the chart. What is the

most prevalent job title?

4. For “Data Scientist” role, find the followings for salary in USD in year 2023:

4.1.What is the max salary?

4.2.What is the min salary?

4.3.What is the average salary?

4.4.What is the standard deviation of salary?

5. How has the average salary (in USD) and total number of jobs for the 'Data

Scientist' role fluctuated in recent years? Draw a combo chart (clustered column-

line on secondary axis) showing the total number of jobs by bars and the average

salary by line for "data scientist" to visualize the changes over the years (From

2020 to 2023).

6. How is the talent pool for the 'Data Scientist' role distributed across companies of

different sizes in 2023? Please draw a pie or bar chart showing the percentage of

'Data Scientist' roles in small, medium, and large companies, in 2023.

7. Compare the percentage of remote-ratio (No remote work, partially remote, fully

remote) of all job titles in 2023 by drawing a pie chart (Show the values in

percentage format, calculated as the count of jobs in each category divided by

the total count of jobs). Compare and discuss the results.

8. Draw a scatter plot showing the salary in USD based on years of experience for

the 'Data Scientist' role in 2023. Analyze whether there is any correlation

between these two variables. Discuss your answer.