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. He was rebuilding an engine.

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

This was a person. She could play cricket.

This was a person. She wanted to learn magic.

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

This was a person. He did not sleep with a pillow. He chewed gum constantly.

This was a person. He overtipped.

This was a person. She played piano.

This was a person. She was an expert barbecuer.

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

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

This was a person. She loved cigarettes.

This was a person. She loved to fish.

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

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

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

This was a person. He was lactose intolerant.

This was a person. She was afraid of heights.

This was a person. She sang at parties. She ate the food at convenience stores.

This was a person. She once robbed a bank. She loved museums.

This was a person. He was a trivia master.

This was a person. He loved pot. He slept around.

This was a person. She was a pharmacist.

This was a person. She ate the food at convenience stores. She was a scout leader.

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

This was a person. She had a bunch of cameras. She always had a clean car.

This was a person. He picked up litter.

This was a person. He had a baby boy.

This was a person. She was a scout leader. She was diabetic.

This was a person. He was an awful driver. He did not sleep with a pillow.

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

This was a person. He wore bow ties.

This was a person. She went to church.

This was a person. He threw a lot of parties. He never ate breakfast.

This was a person. She was homophobic.

This was a person. He was the unofficial relationship guru among his friends.

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

This was a person. He was a hoarder.

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

This was a person. She was sleeping with her ex. She was working her way through all of the shows on Netflix.

This was a person. He played soccer every weekend.

This was a person. She prefered bread without crusts. She was very good at cleaning.

This was a person. She had crazy hair colors.

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

This was a person. He could play trumpet.

This was a person. She wore Spandex.

This was a person. She was lactose intolerant.

This was a person. He was a good dancer.

This was a person. He loved cigarettes.

This was a person. She was left-handed.

This was a person. She was a secret Buddahist. She was divorced.

This was a person. He was a pharmacist. He was afraid of the water.

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

This was a person. She loved chocolate. She wore Spandex.

This was a person. He taught guitar.

This was a person. She loved fine dining.

This was a person. He was a secret Buddahist.

This was a person. She was a translator. She could always get tickets.

This was a person. She played soccer every weekend.

This was a person. She was a good dancer.

This was a person. He was a dog person. He was a wedding photographer.

This was a person. He overtipped. He was good to people.

This was a person. She sang.

This was a person. He had a gun.

This was a person. She loved Elvis. She was a glassblower.

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

This was a person. He excelled at woodworking.

This was a person. She plays fantasy football. She loved museums.

This was a person. He was good to people.

This was a person. She has four overdue books.

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

This was a person. She was an expert barbecuer.

This was a person. She ate a lot of raisins. She was a hoarder.

This was a person. She survived cancer.

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

This was a person. She plays fantasy football.

This was a person. He could juggle. He was polite to salesmen.

This was a person. She was a vegetarian.

This was a person. He grew up on a farm. He had a lot of shoes.

This was a person. He went to the horseraces.

This was a person. He could fix anything.

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

This was a person. She never raised hervoice. She was a glassblower.

This was a person. He was a hoarder.

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

This was a person. He never carried cash. He was the richest of his friends.

This was a person. He was a poet. He was a DJ.

This was a person. He was rebuilding an engine. He can't watch the end of T2 without crying

This was a person. He made his own beer and was kind of stingy with it. He did not sleep with a pillow.

This was a person. She loved chocolate.

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

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

This was a person. She was afraid of heights.

This was a person. He had a green thumb.

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

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

This was a person. She scalped tickets She had a bunch of tattoos.

This was a person. He was a glassblower.

This was a person. He was gluten intolerant.

This was a person. He played piano.

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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