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 wore a lot of hats.

This was a person. He loved to make out.

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

This was a person. She always had gum.

This was a person. She wore Spandex.

This was a person. He went to the horseraces. He spent a lot of time with old people.

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

This was a person. She had an awesome home theatre. She was a vegetarian.

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

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

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

This was a person. He was very careful about conserving gasoline.

This was a person. He could play trumpet.

This was a person. He was a glassblower.

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

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

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

This was a person. She was polite to salesmen. She had crazy hair colors.

This was a person. She only ever had sex with one person. She was always in a hurry.

This was a person. She was a virgin.

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

This was a person. She could play banjo. She tutored kids.

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

This was a person. She was a drunk.

This was a person. She did open mike.

This was a person. He chewed nicotine gum. He was going blind.

This was a person. He tutored kids.

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

This was a person. She did open mike.

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

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

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

This was a person. He was a drunk.

This was a person. She survived cancer.

This was a person. He was an awful driver.

This was a person. He was rough and tumble.

This was a person. She could juggle.

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

This was a person. She was a hoarder.

This was a person. He loved pot.

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

This was a person. He looked like a cartoon.

This was a person. He helped strangers.

This was a person. She snored. She was polite to telemarketers.

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

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

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 wrote for the newspaper. He ate a lot of fiber.

This was a person. She went to church.

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

This was a person. She had a hangover yesterday.

This was a person. He had a green thumb. He helped strangers.

This was a person. He has two living parents.

This was a person. She had tropical fish. She lived on breakfast bars.

This was a person. She had an unfortunate nickname.

This was a person. She had a twin.

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

This was a person. She looked like a cartoon.

This was a person. He could juggle.

This was a person. She loved oreos.

This was a person. He went to the horseraces.

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

This was a person. He was a translator.

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

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

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

This was a person. She was good to people.

This was a person. She was a Mac evangelist.

This was a person. He had crazy hair colors.

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

This was a person. He played World of Warcraft

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 lived on breakfast bars.

This was a person. He never finished the book club book. He had an unfortunate nickname.

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

This was a person. He did open mike.

This was a person. He loved to fish.

This was a person. He loved to make out.

This was a person. He could juggle.

This was a person. She could play banjo.

This was a person. She looked like a cartoon.

This was a person. He loved to fish.

This was a person. She was divorced. She could play trumpet.

This was a person. He had bonsai trees. He ate a lot of chinese food.

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

This was a person. He was a wedding photographer.

This was a person. He was a hoarder.

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

This was a person. He had braces on his teeth.

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

This was a person. She was a wedding photographer.

This was a person. He was a drunk.

This was a person. He was a cheapskate.

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

This was a person. He has four overdue books.

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

This was a person. She sang.

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

This was a person. She was an awful driver.

This was a person. He always brought lunch.

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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