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 didn't have a family.

This was a person. She excelled at woodworking.

This was a person. He was training to run a marathon.

This was a person. She sang.

This was a person. He picked up litter. He had a lot of shoes.

This was a person. She got a terrible haircut a few days ago and shaved her head to escape from it.

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

This was a person. She prefered bread without crusts. She always wore a hat.

This was a person. He was a hoarder. He was sporty.

This was a person. He had VD. He was a plumber.

This was a person. She picked up litter.

This was a person. She helped people. She prefered bread without crusts.

This was a person. She once robbed a bank.

This was a person. She loved fine dining.

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

This was a person. He was afraid of heights.

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

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

This was a person. She was divorced. She never drank coffee.

This was a person. He took a lot of photos.

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

This was a person. She was allergic to peanuts.

This was a person. She made scrapbooks. She was balding.

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

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

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

This was a person. She plays fantasy football. She was a loner.

This was a person. He was a scout leader.

This was a person. He had a green thumb.

This was a person. She wanted to learn magic. She was polite to salesmen.

This was a person. She excelled at woodworking.

This was a person. He had a lot of Beatles records.

This was a person. He was good at job interviews. He was polite to telemarketers.

This was a person. She played soccer every weekend. She had a gun.

This was a person. She always wore a hat. She sang at parties.

This was a person. He wore a lot of hats. He had a lot of shoes.

This was a person. She could play trumpet.

This was a person. He took a lot of photos.

This was a person. He lived on breakfast bars.

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

This was a person. She had a baby boy. She was learning to use CAD software.

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

This was a person. He had a podcast.

This was a person. He just had his car stereo repaired. He played piano.

This was a person. She smoked pot at music festivals. She had a sailboat as a teen.

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

This was a person. He was a trivia master.

This was a person. He was sort of selfish in bed. He did open mike.

This was a person. She was a dog person.

This was a person. He could play banjo.

This was a person. He was very careful about conserving gasoline. He always had gum.

This was a person. She was sleeping with her ex.

This was a person. She had a gun.

This was a person. She could play cricket.

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

This was a person. She collected figurines. She was a teacher.

This was a person. She abused cars.

This was a person. He was a DJ.

This was a person. She had tropical fish. She loved oreos.

This was a person. He did not sleep with a pillow.

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

This was a person. She always bought flowers for her desk.

This was a person. She prefered bread without crusts.

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

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

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

This was a person. She loved James Bond movies.

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

This was a person. He loved James Bond movies.

This was a person. She grew up on a farm.

This was a person. She was a trivia master.

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

This was a person. He made his own beer and was kind of stingy with it. He had braces on his teeth.

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

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

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

This was a person. She took careful notes after every meal. She had a lot of Beatles records.

This was a person. She was a Mac evangelist. She never raised hervoice.

This was a person. She had crazy hair colors.

This was a person. He called in sick to work 9 times last month and was written up at work.

This was a person. He was awaiting judgement for a DUI last month. He could always get tickets.

This was a person. He had a baby boy. He had been having trouble tying his shoes because he pulled a muscle in his abs.

This was a person. She could play trumpet. She loved nachos.

This was a person. She grew up on a farm.

This was a person. He was good at job interviews. He had crazy hair colors.

This was a person. She got a terrible haircut a few days ago and shaved her head to escape from it.

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

This was a person. He excelled at woodworking.

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

This was a person. He made pie.

This was a person. He kept to himself mostly

This was a person. He prefered bread without crusts.

This was a person. He helped people. He took a lot of photos.

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

This was a person. He had a lot of shoes.

This was a person. He made his own beer and was kind of stingy with it. He was a Mac evangelist.

This was a person. He ate a lot of chinese food. He grew up on a farm.

This was a person. He loved to fish.

This was a person. She was allergic to peanuts.

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

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