The Banana massacre Tragedy Casualties Visualization Tool - Cockeyed.com

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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. She was polite to salesmen.

This was a person. She had just paid a crapload of money to get teeth fixed.

This was a person. She always had a clean car.

This was a person. He was rebuilding an engine.

This was a person. He had a green thumb.

This was a person. She plays fantasy football.

This was a person. He loved to fish.

This was a person. He made scrapbooks.

This was a person. She never drank coffee. She prefered bread without crusts.

This was a person. She loved fine dining.

This was a person. She sang.

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

This was a person. He was thrifty.

This was a person. She wore bow ties. She loved rollerblading.

This was a person. He was a cat person.

This was a person. She was rough and tumble. She played chess.

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

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

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

This was a person. She wore bow ties.

This was a person. She wore a lot of hats.

This was a person. He got thrown off of a golf course.

This was a person. He wore a lot of hats. He wore bow ties.

This was a person. She played chess.

This was a person. She was kind of addicted to ebay.

This was a person. She was good to people.

This was a person. She helped strangers.

This was a person. She was a cheapskate.

This was a person. She sang.

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

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

This was a person. She loved James Bond movies.

This was a person. He was rough and tumble. He knew how to get free satelittle television.

This was a person. He was a secret Buddahist.

This was a person. He was a drunk.

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

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

This was a person. She was a hoarder.

This was a person. He was sleeping with his ex.

This was a person. He always brought lunch.

This was a person. She never raised hervoice.

This was a person. He loved to make out.

This was a person. He got out of jail two years ago and never reunited with his family. He called in sick to work 9 times last month and was written up at work.

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

This was a person. He had crazy hair colors.

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

This was a person. He had extensions.

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

This was a person. He wrote for the newspaper.

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

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

This was a person. She was a Mac evangelist.

This was a person. He was playing nine games of Words with Friends on his phone.

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

This was a person. She did open mike. She was afraid of the water.

This was a person. He played soccer every weekend.

This was a person. She helped people.

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

This was a person. He picked up litter.

This was a person. He made pie.

This was a person. She helped people.

This was a person. She was kind of addicted to ebay.

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

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

This was a person. He got thrown off of a golf course.

This was a person. He loved oreos.

This was a person. She loved oreos.

This was a person. He occasionally shop lifted. He was really good at geography.

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

This was a person. He did not own a fridge.

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

This was a person. He was left-handed.

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

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

This was a person. She could fall asleep anywhere.

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

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

This was a person. She taught guitar.

This was a person. He was an awful driver.

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

This was a person. He was allergic to peanuts.

This was a person. She never ate breakfast.

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

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

This was a person. He had an awesome home theatre.

This was a person. She had an unfortunate nickname. She made scrapbooks.

This was a person. She was a historian.

This was a person. She was polite to telemarketers.

This was a person. He can't watch the end of T2 without crying He constantly wore sunglasses.

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

This was a person. She scalped tickets She loved James Bond movies.

This was a person. He overtipped.

This was a person. He helped people.

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

This was a person. She played World of Warcraft She loved rollerblading.

This was a person. He was 4 days sober.

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

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

This was a person. She sang at parties. She has four overdue books.

This was a person. She played World of Warcraft

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.

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