Data Science Salary Trends 2023

Introduction

Welcome to the Data Science Salary Trends 2023 dataset! This repository aims to provide valuable insights into the salary trends within the field of Data Science for the years 2021 to 2023. Whether you're a data enthusiast, analyst, or industry professional, this dataset can offer valuable information for understanding the salary dynamics in the Data Science job market.

About the Dataset

This dataset focuses on various aspects of employment, including work experience, job titles, employment types, company locations, and company sizes. Here's a brief overview of the data fields:

• work_year: Specific year of salary data collection (2021, 2022, or 2023).
• Experience_level: Level of work experience categorized as EN (Entry-Level), EX (Experienced), MI (Mid-Level), SE (Senior).
• Employment_type: Type of employment labeled as FT (Full-Time), CT (Contractor), FL (Freelancer), PT (Part-Time).
• Job_title: Job titles of the employees.
• Salary: Salary figures in their respective currency formats.
• Salary_currency: Currency code representing the salary.
• Salary_in_usd: Converted salary figures in USD for uniform comparison.
• Company_location: Location of the companies specified as country codes.
• Company_size: Size of the companies classified as "L" (Large), "M" (Medium), and "S" (Small).

Exploratory Data Analysis (EDA) Instructions

To perform the extra part of Exploratory Data Analysis (EDA) on this dataset, follow these steps:

1. Visualization:

   • Create visualizations to effectively communicate insights from the data.
   • Use tools like matplotlib, seaborn, or Plotly for generating plots.
   • Consider using interactive visualizations for a more engaging exploration experience.

   After completing your visualizations, continue with the following steps:

   Question 1: salary distribution wrt company size.

   

    

   Question 2: comparison between average salary of data engineer and data scientist.

   

    

   Question 3: average salary of da, ds, de based on employment type.

   

By following these steps, you'll be able to focus on the extra part of your Exploratory Data Analysis and gain valuable insights into the dataset.

Kindly, upvote if you find the dataset interesting. Thank you.

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Note: If you have any questions or suggestions regarding the dataset, feel free to reach out or open an issue in this repository. Your feedback is highly appreciated!