The Data Science Industry Survey Analysis project aims to provide a comprehensive examination of the current landscape, trends, and challenges within the data science industry. By conducting a thorough survey targeting data science professionals and organizations, this project seeks to uncover valuable insights to inform strategic decision-making and industry best practices.
- Excel: Primary Data Cleaning
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- How does the demand for specific programming languages (e.g., Python, R, SQL) vary across different sectors or industries within the data science field?
- What are some job factors that contribute to job satisfaction and retention among data science professionals?
- What is the impact of a university degree in data science on the salary?
- How does the salary of the data professional defer based on sex, age and ethnicity?
The data underwent rigorous cleaning processes, including:
- Removing duplicates and handling missing values.
- Standardizing the format of categorical variables and converting data types for numerical analysis.
- Ensuring geographic data accuracy for subsequent geospatial analysis.
- Aggregating data where necessary to facilitate more efficient analysis.
- Creating a consistent naming convention for ease of interpretation and analysis.