Data Cleaning and Exploration with SQL

This SQL script performs data cleaning and exploratory data analysis on a layoffs table to prepare it for further insights. The process includes the following steps:

Data Sources

• Layoffs Dataset: layoffs.csv

How to Use

1. Download the layoffs.csv file.
2. Import the CSV file into a MySQL database.
3. Execute the following SQL script.

1. Data Cleaning

• A staging table (layoffs_staging2) is created as a copy of the original layoffs table.
• The script identifies and removes duplicate rows.
• Leading and trailing whitespaces are removed from text columns.
• Inconsistencies in the industry and country columns are addressed.
• The date column is converted to a proper DATE format.
• Null and blank values in key columns are handled.
• Redundant columns are dropped.
• The final cleaned dataset is stored in layoffs_staging2.

2. Exploratory Data Analysis (EDA)

The script also includes exploratory data analysis to provide insights into the cleaned data. Key areas of investigation include:

• Identifying companies and industries with the highest layoff numbers.
• Analyzing layoffs as a percentage of company size.
• Examining the relationship between funds raised and layoffs.
• Calculating monthly layoff trends.
• Determining the top 5 companies with the most layoffs per year.

Preview