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 had a bunch of cameras.

This was a person. She loved cigarettes. She was sporty.

This was a person. He was lactose intolerant.

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

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

This was a person. She had an unfortunate nickname.

This was a person. She loved to make out.

This was a person. She sang.

This was a person. She was rough and tumble. She picked up litter.

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

This was a person. She had a podcast. She was polite to telemarketers.

This was a person. He couldn't grow a mustache.

This was a person. He played piano.

This was a person. She was a scout leader.

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

This was a person. She had a hangover yesterday.

This was a person. She loved cigarettes. She sang at parties.

This was a person. He had a green thumb.

This was a person. He could fall asleep anywhere.

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

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

This was a person. He could play trumpet.

This was a person. He was homophobic. He was lactose intolerant.

This was a person. He was a good dancer.

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

This was a person. He was a good dancer. He wore a lot of hats.

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 once robbed a bank.

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

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

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

This was a person. She had a baby boy.

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

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

This was a person. He was polite to salesmen.

This was a person. She never raised hervoice.

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

This was a person. He loved to fish.

This was a person. She was a hoarder.

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

This was a person. She was an expert barbecuer.

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

This was a person. She had a green thumb.

This was a person. He never drank coffee.

This was a person. She was an expert barbecuer.

This was a person. He occasionally shop lifted.

This was a person. She sang at parties. She spends a lot of time watching tennis.

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

This was a person. He has two living parents.

This was a person. She got out of jail two years ago and never reunited with her family.

This was a person. She loved pot.

This was a person. She was a vegetarian.

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

This was a person. He had a hangover yesterday.

This was a person. He was rough and tumble.

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

This was a person. He was a pharmacist. He scalped tickets

This was a person. She had bonsai trees. She was polite to salesmen.

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

This was a person. She never drank coffee.

This was a person. He could fix anything.

This was a person. She wrote for the newspaper.

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

This was a person. She loved Elvis.

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

This was a person. He once robbed a bank.

This was a person. She was a translator. She couldn't grow a mustache.

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

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

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

This was a person. She played soccer every weekend.

This was a person. He never drank coffee.

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

This was a person. She has four overdue books.

This was a person. He plays fantasy football.

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

This was a person. He was a pharmacist.

This was a person. She had bonsai trees.

This was a person. She played chess.

This was a person. She had a baby boy.

This was a person. He never carried cash.

This was a person. He talked during movies.

This was a person. He was a cheapskate. He made scrapbooks.

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

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

This was a person. She wore bow ties. She had a sexy phone voice.

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

This was a person. He was a pharmacist.

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

This was a person. He was a mason. He was an awful driver.

This was a person. She was a trivia master. She loved James Bond movies.

This was a person. He was divorced.

This was a person. She looked like a cartoon.

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

This was a person. He prefered bread without crusts.

This was a person. He can't watch the end of T2 without crying He had braces on his teeth.

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

This was a person. He led the choir. He played chess.

This was a person. She was a pharmacist.

This was a person. She was left-handed. She chewed nicotine gum.

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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