The Happy Land Fire Tragedy Casualties Visualization Tool - Cockeyed.com

Cockeyed.com

How much is Inside?
Pranks!
Community & Citizenship
Height Weight Chart
Science Club
Incredible Stuff
How To Guides
Travel

About
Contact

Disaster Casualties Visualization Tool: The Happy Land Fire: 1990

87 Dead Men and Women

The Happy Land fire was an arson fire that killed 87 people trapped in an unlicensed social club, 1990.

This was a person. She was a mason.

This was a person. He was good to people.

This was a person. He was rough and tumble.

This was a person. He wrote for the newspaper. He never drank coffee.

This was a person. She never carried cash.

This was a person. She has two living parents.

This was a person. She loved pot.

This was a person. He was a teacher.

This was a person. She helped strangers.

This was a person. She was rough and tumble.

This was a person. She always bought flowers for her desk. She made her own beer and was kind of stingy with it.

This was a person. She had an unfortunate nickname.

This was a person. He knew a lot of cops. He was divorced.

This was a person. He played a lot of social card games. He got thrown off of a golf course.

This was a person. He had a hangover yesterday.

This was a person. He just had the bandages removed from plastic surgery.

This was a person. She was thrifty. She could play banjo.

This was a person. He took careful notes after every meal.

This was a person. She was left-handed. She helped strangers.

This was a person. She ate a lot of chinese food.

This was a person. He always had gum. He spends a lot of time watching tennis.

This was a person. He wore Spandex.

This was a person. He had a twin. He was a virgin.

This was a person. She once robbed a bank.

This was a person. He chewed gum constantly.

This was a person. She loved wine. She always brought reusable bags into the store.

This was a person. He just had the bandages removed from plastic surgery.

This was a person. He was rough and tumble. He was a cheapskate.

This was a person. He picked up litter.

This was a person. He was a wedding photographer. He was polite to telemarketers.

This was a person. She was the unofficial relationship guru among friends.

This was a person. She was a trivia master. She was afraid of heights.

This was a person. She was an awful driver.

This was a person. She was polite to telemarketers. She did not own a fridge.

This was a person. He made pie. He lived on breakfast bars.

This was a person. She loved oreos. She ate a lot of chinese food.

This was a person. She spent a lot of time with old people.

This was a person. He loved pot.

This was a person. He was a virgin.

This was a person. She knew how to get free satelittle television. She helped strangers.

This was a person. She could play cricket.

This was a person. She had a bunch of cameras.

This was a person. She was a mason.

This was a person. He was cockeyed. He played guitar on the streets for money.

This was a person. She played a lot of social card games.

This was a person. He excelled at woodworking. He was convinced he was color blind.

This was a person. She loved wine.

This was a person. He had a bunch of tattoos. He talked during movies.

This was a person. She was a dog person.

This was a person. He chewed gum constantly.

This was a person. He could play cricket.

This was a person. He was the richest of his friends. He was homophobic.

This was a person. He always had a clean car. He wore Spandex.

This was a person. He has two living parents.

This was a person. She didn't have a family. She was afraid of flying.

This was a person. She has four overdue books.

This was a person. She constantly wore sunglasses.

This was a person. She was cockeyed.

This was a person. He was good at job interviews.

This was a person. He kept to himself mostly He loved nachos.

This was a person. He didn't have a family. He volunteered at a middle school, because he had a crush on one of the other tutors.

This was a person. He threw a lot of parties.

This was a person. She dropped her work laptop last week, destroyed it and couldn't sleep for days.

This was a person. He brought great food to social gatherings.

This was a person. She always wore a hat.

This was a person. He collected figurines.

This was a person. She was a poet.

This was a person. She was divorced.

This was a person. He was rebuilding an engine.

This was a person. She was a glassblower.

This was a person. She could play banjo.

This was a person. She ate a lot of fiber.

This was a person. She ate the food at convenience stores. She had just paid a crapload of money to get teeth fixed.

This was a person. She knew how to get free satelittle television.

This was a person. He was sporty. He led the choir.

This was a person. He had a podcast.

This was a person. He always brought reusable bags into the store.

This was a person. He was a wedding photographer.

This was a person. She had a sexy phone voice.

This was a person. He helped people. He wrote for the newspaper.

This was a person. She made her own beer and was kind of stingy with it.

This was a person. He had a bunch of cameras.

This was a person. He kept to himself mostly

This was a person. He was a wedding photographer.

This was a person. He had bonsai trees. He was polite to telemarketers.

This was a person. He never drank coffee.

This was a person. She prefered bread without crusts. She loved pot.

View a different tragedy with the Disaster Visualization Tool

Jonestown | The Titanic | Kent State Shootings | My Lai | Lockerbie bombing | Kent State Shootings | Tiananmen Square Massacre | The Banana massacre | The Boyd Massacre | Mountain Meadows massacre | Kfar Etzion Massacre | Sharpeville Massacre | The Miami Showband Massacre | The Novocherkassk massacre | Tokyo Subway Sarin attack | Sinking of the Titanic | The Happy Land Fire | Brooklyn Bridge stampede | 1990 Pilgrim Stampede | Luxor hot air balloon crash |

Mouse-over body descriptions are randomly generated, intended to inject humanity into the raw number of dead. It cannot accurately represent the actual people who died in the tragedy.

The Oatmeal Markup | Antiques Roadshow - The Ultimate "Neat Stuff" Show | Iphone vs. Kia | Let us Dilute that For You | Razor and Blades Business Model | Short-Circuiting the Facebook Tease Video Link | Other Websites Besides Healthcare.org which are Broken | Visualizing the Price of a Television | Personal account of working for commision at Banker's Life Insurance | The Three Problems with Child Car Seats | How Much Time is Really Left in the Basketball Game? | Who Uses Their Turn Signal? | Other Web Problems not related to Healthcare.org | The Cross-Section of a Couch | Comparing the Price of Used Car to the Price of a New Car | Rental Car Keys are Horrible | The Actual Amount of Time it Takes | Incorrect Shelf Prices at Walmart | Two Prices for Auto Body Repair | Roadside Sobriety Test | Cash in your Pennies | Get it Together Walmart | Price Increases at Fast Food Restaurants | Yard Sale is Shoe Store Scam | Disaster Casualties Visualization Tool | Walmart vs Target: 2013 | The 146 Drugs in Walmart's $4 Prescription Drug Plan | Email Concealer Codes | accumulating credit card debt | Selling a Structured Settlement | The Torn-up Credit Card Application ! Kirby Vacuum Cleaners

Photographic Height/Weight Chart

The Weight of Clothing

The Television Commercial Database

Cockeyed home page | Contact | Terms and Conditions | Updated February 27, 2013 Copyright 2013 Cockeyed.com