/Salary-App

Streamlit app for interactive data exploration and visualization.

Primary LanguageJupyter Notebook

Data Science Salary in 2023

Data science is one of the most exciting and in-demand fields in the job market. Data scientists, as well as other data-related jobs, command some of the highest salaries in the tech industry. However, data science salaries can vary significantly depending on various factors, such as experience, skills, job title, or company size.

Installation

To run the visualization app locally, follow these steps:

  1. Clone the repository:

       git clone https://github.com/A-A7med-i/Salary-App.git
  2. Navigate to the project directory:

       cd name of repository
  3. Install the required dependencies:

       pip install -r requirements.txt
  4. Run the script :

       streamlit run app.py

Data

Data Science Job Salaries Dataset contains 11 columns, each are:

  • work_year: The year the salary was paid.
  • experience_level: The experience level in the job during the year
  • employment_type: The type of employment for the role
  • job_title: The role worked in during the year.
  • salary: The total gross salary amount paid.
  • salary_currency: The currency of the salary paid as an ISO 4217 currency code.
  • salaryinusd: The salary in USD
  • employee_residence: Employee's primary country of residence in during the work year as an ISO 3166 country code.
  • remote_ratio: The overall amount of work done remotely
  • company_location: The country of the employer's main office or contracting branch
  • company_size: The median number of people that worked for the company during the year

Accessing the Data

You can access the dataset from Kaggle using the following URL: salary DS

Contributing

Contributions to this project are welcome. If you have any suggestions or improvements, please create an issue or submit a pull request.