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 learning to use CAD software. She never carried cash.

This was a person. She had a bunch of tattoos. She loved to fish.

This was a person. She had been having trouble tying her shoes because she pulled a muscle in her abs.

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

This was a person. She was good at job interviews. She looked like a cartoon.

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

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

This was a person. He was lactose intolerant.

This was a person. She was a Mac evangelist.

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

This was a person. He chewed nicotine gum. He loved museums.

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

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

This was a person. He could play banjo.

This was a person. She was a wedding photographer.

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

This was a person. He excelled at woodworking.

This was a person. She has two living parents. She was sort of selfish in bed.

This was a person. She was polite to salesmen.

This was a person. He had bonsai trees.

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

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

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

This was a person. He picked up litter.

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

This was a person. He was divorced.

This was a person. She was a wedding photographer.

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

This was a person. She loved chocolate.

This was a person. She wore Spandex.

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

This was a person. She was awaiting judgement for a DUI last month. She only ever had sex with one person.

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 constantly wore sunglasses.

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

This was a person. He abused cars.

This was a person. She played piano. She always brought lunch.

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

This was a person. She was an awful driver. She never carried cash.

This was a person. He was a plumber.

This was a person. She was a hoarder.

This was a person. She went to the horseraces.

This was a person. He was good to people. He was going blind.

This was a person. She had crazy hair colors.

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

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

This was a person. He was a vegetarian.

This was a person. He couldn't grow a mustache. He had a lot of Beatles records.

This was a person. He was a historian.

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

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

This was a person. She kept buying vegetables, even though they always just went bad in her fridge.

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

This was a person. She loved fine dining.

This was a person. She ate a lot of raisins. She tutored kids.

This was a person. He had a gun.

This was a person. He slept around.

This was a person. She was an awful driver.

This was a person. She overtipped.

This was a person. He made pie.

This was a person. She was a skilled woodcarver.

This was a person. He was a trivia master.

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

This was a person. He had an unfortunate nickname.

This was a person. She had a green thumb.

This was a person. He was a cat person.

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

This was a person. He was a trivia master.

This was a person. He was a virgin.

This was a person. He was very good at cleaning. He led the choir.

This was a person. He had bonsai trees. He loved wine.

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

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

This was a person. She was a historian.

This was a person. She could play cricket.

This was a person. She kept buying vegetables, even though they always just went bad in her fridge.

This was a person. She had a lot of Beatles records. She was thrifty.

This was a person. He was afraid of flying. He was a crossword whiz.

This was a person. She was polite to telemarketers.

This was a person. She was a cheapskate.

This was a person. He was a cat person.

This was a person. He always had a clean car. He had crazy hair colors.

This was a person. He was a tailor.

This was a person. He played soccer every weekend. He was kind of addicted to ebay.

This was a person. He wore Spandex.

This was a person. She sang.

This was a person. He could fall asleep anywhere.

This was a person. She had a bunch of tattoos. She could fix anything.

This was a person. She helped people.

This was a person. He kept to himself mostly

This was a person. She was a cheapskate.

This was a person. He did not own a fridge. He never finished the book club book.

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

This was a person. She always made the mashed potatoes at family get-togethers. She was learning to use CAD software.

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

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

This was a person. She tutored kids.

This was a person. She has two living parents. She was learning to use CAD software.

This was a person. He had just paid a crapload of money to get teeth fixed. He excelled at woodworking.

This was a person. He was homophobic.

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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