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 just had the bandages removed from plastic surgery. He loved fine dining.

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

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

This was a person. He was a translator.

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

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

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

This was a person. She played piano.

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 volunteered at a middle school, because she had a crush on one of the other tutors.

This was a person. She was polite to salesmen.

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

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

This was a person. She overtipped.

This was a person. He once robbed a bank.

This was a person. She had tropical fish.

This was a person. He loved chocolate.

This was a person. He loved James Bond movies.

This was a person. He occasionally shop lifted. He couldn't swim.

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

This was a person. She could juggle.

This was a person. She had a podcast.

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

This was a person. She was polite to salesmen.

This was a person. She wrote for the newspaper.

This was a person. She loved James Bond movies. She knew a lot of cops.

This was a person. She abused cars.

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

This was a person. She overtipped.

This was a person. She sang.

This was a person. He was a translator. He was a trivia master.

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

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

This was a person. She had extensions. She knew how to get free satelittle television.

This was a person. She played World of Warcraft She excelled at woodworking.

This was a person. She scalped tickets

This was a person. He has two living parents.

This was a person. He was afraid of flying. He was a pharmacist.

This was a person. She threw a lot of parties.

This was a person. She had a twin.

This was a person. He was very good at cleaning.

This was a person. She was living with her sister.

This was a person. She had VD. She was a DJ.

This was a person. She didn't get along with animals.

This was a person. He could play banjo.

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

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

This was a person. She had an unfortunate nickname. She spends a lot of time watching tennis.

This was a person. He loved nachos. He always wore a hat.

This was a person. She was allergic to peanuts. She ate a lot of hot dogs.

This was a person. He snored.

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

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

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

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

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

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

This was a person. She never carried cash. She had an awesome home theatre.

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

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

This was a person. She had VD.

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

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

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

This was a person. She was allergic to peanuts.

This was a person. She collected figurines.

This was a person. She volunteered at a middle school, because she had a crush on one of the other tutors.

This was a person. He helped strangers.

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

This was a person. She taught guitar.

This was a person. She had a lot of Beatles records. She helped people.

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

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

This was a person. He was sleeping with his ex. He did open mike.

This was a person. He was a hoarder. He ate the food at convenience stores.

This was a person. She was the unofficial relationship guru among friends.

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

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

This was a person. He was homophobic.

This was a person. She was a street vendor.

This was a person. He had a twin.

This was a person. He never carried cash.

This was a person. She was learning to speak French. She scalped tickets

This was a person. She loved to fish.

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

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

This was a person. She wrote for the newspaper. She was gluten intolerant.

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

This was a person. He loved Elvis.

This was a person. He was divorced.

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

This was a person. She had been having trouble tying her shoes because she pulled a muscle in her abs. She was kind of an awesome lover.

This was a person. He had a baby boy.

This was a person. She never carried cash.

This was a person. She occasionally shop lifted. She fixed bikes.

This was a person. She was homophobic.

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

This was a person. He could fix anything. He loved Elvis.

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

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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