https://github.com/narpat78/layoffs-data-cleaning-and-eda-using-sql
A SQL-based project to clean and analyze layoffs dataset. Focuses on standardizing data, handling nulls, converting data types, and performing exploratory queries for business insights.
https://github.com/narpat78/layoffs-data-cleaning-and-eda-using-sql
data-cleaning-and-preprocessing eda mysql mysql-workbench sql
Last synced: 10 months ago
JSON representation
A SQL-based project to clean and analyze layoffs dataset. Focuses on standardizing data, handling nulls, converting data types, and performing exploratory queries for business insights.
- Host: GitHub
- URL: https://github.com/narpat78/layoffs-data-cleaning-and-eda-using-sql
- Owner: narpat78
- Created: 2025-09-03T03:49:12.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-09-03T03:55:17.000Z (10 months ago)
- Last Synced: 2025-09-03T05:30:26.883Z (10 months ago)
- Topics: data-cleaning-and-preprocessing, eda, mysql, mysql-workbench, sql
- Homepage:
- Size: 6.84 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# SQL Layoffs Data Cleaning & EDA
This project focuses on cleaning and analyzing a layoffs dataset using **MySQL**. The goal is to standardize the data, handle missing values, remove duplicates, and perform exploratory queries to uncover insights into global layoff trends.
## Dataset Source
The dataset was imported into **MySQL Workbench** for cleaning and analysis.
- [Download Dataset](https://www.kaggle.com/datasets/swaptr/layoffs-2022)
## Steps Performed
1. **Data Cleaning** – removed duplicates, standardized values, formatted dates, and handled missing entries.
2. **Data Transformation** – converted datatypes, trimmed extra spaces, and normalized text fields.
3. **Exploratory Data Analysis (EDA)** – identified top companies by layoffs, yearly trends, and rolling totals.
## Tools Used
- MySQL Workbench
- SQL (DDL & DML queries, Window functions, CTEs, Ranking, Aggregations)