Layoff Data Cleaning and Exploration (using MySQL)

This repository documents a project exploring a dataset of global layoffs. The project follows two key phases:

1. Data Cleaning:

• Utilized MySQL queries to clean and pre-process the data, ensuring its accuracy and consistency for further analysis.
• Implemented techniques such as removing duplicates, standardizing data formats (e.g., dates, job titles), and handling missing values using appropriate methods (e.g., deletion, imputation).
• Included code snippets and explanations to demonstrate the applied data cleaning procedures.

2. Exploratory Data Analysis (EDA):

• Leveraged SQL queries to explore trends and patterns within the cleaned data.
• Analyzed aspects like:
  • Identifying industries most affected by layoffs.
  • Investigating temporal patterns in layoffs (e.g., seasonal trends).
  • Exploring other relevant factors contributing to layoffs (if available in the data).

Tools:

• MySQL
• SQL

The cleaned data is prepared for further exploration and potential use in predictive modeling or other data science applications.