The Banana massacre 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 Banana massacre: 1928

100 Dead Men and Women

The Banana massacre was a massacre of striking workers for the United Fruit Company on December 6, 1928 in the town of Ciénaga, Colombia. The number of dead has not been accurately noted.

This was a person. He was a drunk.

This was a person. He kept to himself mostly He was polite to telemarketers.

This was a person. She never finished the book club book.

This was a person. She was working her way through all of the shows on Netflix.

This was a person. He was working his way through all of the shows on Netflix.

This was a person. She survived cancer.

This was a person. He was learning to speak French.

This was a person. He could fix anything.

This was a person. He didn't have a family.

This was a person. He went to church.

This was a person. She had a baby boy. She finished reading all of the works of Homer.

This was a person. She loved to make out. She was always in a hurry.

This was a person. She always wore a hat.

This was a person. He wanted to learn magic.

This was a person. She wore earphones all the time. She was a vegetarian.

This was a person. He always had a clean car. He always had gum.

This was a person. He watched a lot of sports on TV, but never played them himself.

This was a person. He was a mason.

This was a person. She was a trivia master.

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

This was a person. He did not sleep with a pillow. He had bonsai trees.

This was a person. She was an expert barbecuer.

This was a person. He had tropical fish. He threw a lot of parties.

This was a person. She had a gun.

This was a person. She was an awful driver.

This was a person. She had a hangover yesterday.

This was a person. She did not own a fridge. She ate the food at convenience stores.

This was a person. He was always in a hurry.

This was a person. He was a hoarder.

This was a person. She played chess.

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

This was a person. She has a suit at the cleaners.

This was a person. She had a bunch of tattoos. She watched a lot of sports on TV, but never played them herself.

This was a person. He was rough and tumble.

This was a person. She was rebuilding an engine.

This was a person. He collected figurines. He was a virgin.

This was a person. She smoked pot at music festivals.

This was a person. He had extensions. He led the choir.

This was a person. He ate a lot of kale.

This was a person. She was a cat person.

This was a person. She loved fine dining.

This was a person. He didn't get along with animals.

This was a person. He was a crossword whiz. He knew a lot of cops.

This was a person. She had a lot of music on vinyl.

This was a person. She was kind of an awesome lover.

This was a person. She was a secret Buddahist.

This was a person. He was a plumber.

This was a person. She was allergic to peanuts.

This was a person. He abused cars.

This was a person. He did open mike. He was kind of addicted to ebay.

This was a person. He ate a lot of fish.

This was a person. He ate a lot of raisins. He always wore a hat.

This was a person. He occasionally shop lifted. He was diabetic.

This was a person. He volunteered at a middle school, because he had a crush on one of the other tutors.

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

This was a person. She wore Spandex. She overtipped.

This was a person. She never carried cash.

This was a person. She was a dog person.

This was a person. She had tropical fish.

This was a person. He always bought flowers for his desk.

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

This was a person. She ate a lot of chinese food. She was the unofficial relationship guru among her friends.

This was a person. She helped strangers.

This was a person. She volunteered at a middle school, because she had a crush on one of the other tutors. She was a DJ.

This was a person. He was a drunk.

This was a person. She occasionally shop lifted.

This was a person. She was working her way through all of the shows on Netflix. She had a lot of Beatles records.

This was a person. He ate a lot of hot dogs.

This was a person. She was awaiting judgement for a DUI last month.

This was a person. He was a hoarder. He wore a lot of hats.

This was a person. She had an unfortunate nickname. She had a lot of shoes.

This was a person. He was very careful about conserving gasoline. He played a lot of social card games.

This was a person. He played chess.

This was a person. He wore earphones all the time.

This was a person. He threw a lot of parties. He could play banjo.

This was a person. He was afraid of heights.

This was a person. He dropped his work laptop last week, destroyed it and couldn't sleep for days. He was kind of an awesome lover.

This was a person. He didn't have a family.

This was a person. He was lactose intolerant.

This was a person. He could fall asleep anywhere.

This was a person. He ate a lot of chinese food. He never finished the book club book.

This was a person. She had an unfortunate nickname.

This was a person. She loved oreos.

This was a person. She was a Mac evangelist. She was the richest of her friends.

This was a person. He picked up litter. He abused cars.

This was a person. He was a historian. He wore a lot of jewelry.

This was a person. He tutored kids. He led the choir.

This was a person. She had a personal injury lawsuit working its way through the courts.

This was a person. She had a green thumb.

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

This was a person. She always made the mashed potatoes at family get-togethers.

This was a person. She was playing nine games of Words with Friends on her phone.

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

This was a person. He was polite to salesmen.

This was a person. She had a lot of shoes. She was diabetic.

This was a person. She snored.

This was a person. She was polite to telemarketers.

This was a person. She had VD. She did open mike.

This was a person. She was a plumber.

This was a person. He was polite to salesmen. He always had a clean car.

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

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