This Analysis about a few things like:
- Correlation between salaries and experience level
- Distribution of data science jobs across different company locations
- Most Common Data Science Job Titles and Categories
- Trends in job titles and categories over the years
- Distribution of employment types and work settings
- How company size correlates with salaries and job roles
- How the data science job market has evolved over the years
- Building predictive model to estimate salaries based on various features in the dataset like experience level, company's location, company's size and others.
Kaggle Dataset Link: https://www.kaggle.com/datasets/hummaamqaasim/jobs-in-data
Link for downloading dataset: https://www.kaggle.com/datasets/hummaamqaasim/jobs-in-data/download?datasetVersionNumber=6
Link to my code in Kaggle: https://www.kaggle.com/datasets/danieldarbekov/data-science-jobs-and-salary-analysis/code?datasetId=4286850&sortBy=dateRun&tab=profile
RangeIndex: 9355 entries, 0 to 9354
Data columns (total 12 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 work_year 9355 non-null int64
1 job_title 9355 non-null object
2 job_category 9355 non-null object
3 salary_currency 9355 non-null object
4 salary 9355 non-null int64
5 salary_in_usd 9355 non-null int64
6 employee_residence 9355 non-null object
7 experience_level 9355 non-null object
8 employment_type 9355 non-null object
9 work_setting 9355 non-null object
10 company_location 9355 non-null object
11 company_size 9355 non-null object
dtypes: int64(3), object(9)
memory usage: 877.2+ KBThis project is licensed under the MIT License.