Data-Science-Jobs-and-Salary-Analysis

Description

This Analysis about a few things like:

1. Correlation between salaries and experience level
2. Distribution of data science jobs across different company locations
3. Most Common Data Science Job Titles and Categories
4. Trends in job titles and categories over the years
5. Distribution of employment types and work settings
6. How company size correlates with salaries and job roles
7. How the data science job market has evolved over the years
8. Building predictive model to estimate salaries based on various features in the dataset like experience level, company's location, company's size and others.

Links

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

About Dataset

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+ KB

License

This project is licensed under the MIT License.