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 a DJ. He can't watch the end of T2 without crying

This was a person. He had long fingernails.

This was a person. She was a poet.

This was a person. She had crazy hair colors.

This was a person. She was a secret Buddahist.

This was a person. She was a skilled woodcarver.

This was a person. She was an expert barbecuer.

This was a person. She was sort of selfish in bed.

This was a person. She loved Elvis.

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

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

This was a person. She was always in a hurry. She had a lot of Beatles records.

This was a person. He had crazy hair colors.

This was a person. She overtipped.

This was a person. She excelled at woodworking.

This was a person. He helped strangers.

This was a person. He picked up litter.

This was a person. He was lactose intolerant.

This was a person. He had a hangover yesterday.

This was a person. He taught guitar.

This was a person. She helped people.

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

This was a person. He was rebuilding an engine. He talked during movies.

This was a person. He had extensions. He sang at parties.

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

This was a person. He loved chocolate.

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

This was a person. She had a podcast.

This was a person. He was very good at cleaning. He was left-handed.

This was a person. She had a lot of shoes.

This was a person. She had long fingernails.

This was a person. She was left-handed.

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

This was a person. She constantly wore sunglasses.

This was a person. She was working her way through all of the shows on Netflix. She knew a lot of cops.

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

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

This was a person. He scalped tickets

This was a person. He was a wedding photographer.

This was a person. He was learning to speak French. He was a tailor.

This was a person. She was afraid of flying.

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

This was a person. She never ate breakfast.

This was a person. He played chess.

This was a person. She was an expert barbecuer.

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

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

This was a person. She was polite to telemarketers.

This was a person. She was thrifty.

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

This was a person. She was a poet.

This was a person. She wore bow ties.

This was a person. She loved pot.

This was a person. She was polite to salesmen.

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

This was a person. She wore Spandex. She played World of Warcraft

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

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

This was a person. He was a mason.

This was a person. He was a street vendor.

This was a person. She wrote for the newspaper.

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

This was a person. He played World of Warcraft

This was a person. She was thrifty.

This was a person. He sang.

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

This was a person. He had a green thumb.

This was a person. He sang.

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

This was a person. He once robbed a bank. He was really good at geography.

This was a person. He had just paid a crapload of money to get teeth fixed. He helped the widow next door.

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

This was a person. She was sleeping with her ex. She was learning to use CAD software.

This was a person. She survived cancer.

This was a person. He had a lot of music on vinyl.

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

This was a person. She had crazy hair colors.

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

This was a person. She loved nachos.

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

This was a person. He snored.

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

This was a person. He has four overdue books. He had lice.

This was a person. She had extensions.

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

This was a person. She was a good dancer.

This was a person. She loved Elvis.

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

This was a person. She ate a lot of raisins. She loved nachos.

This was a person. She loved chocolate. She tutored kids.

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

This was a person. He lived on breakfast bars.

This was a person. She was good at job interviews. She had long fingernails.

This was a person. She could play cricket.

This was a person. She wanted to learn magic.

This was a person. She sang.

This was a person. He had VD.

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

This was a person. He plays fantasy football.

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

View a different tragedy with the Disaster Visualization Tool

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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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