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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 has a suit at the cleaners. This was a person. She had crazy hair colors. This was a person. She was a wedding photographer. This was a person. He had bonsai trees. This was a person. She played a lot of social card games.  She has four overdue books.  This was a person. She  only ever had sex with one person. This was a person. He could play banjo. This was a person. She spends a lot of time watching tennis. She smoked pot at music festivals. This was a person. He  had a hangover yesterday. This was a person. She has a suit at the cleaners. This was a person. He took a lot of photos. This was a person. She was a hoarder. This was a person. She went to the horseraces. This was a person. He was an awful driver. This was a person. He had a lot of shoes. This was a person. He had bonsai trees. This was a person. He wore earphones all the time. This was a person. She was sporty. This was a person. She wrote for the newspaper. This was a person. He wanted to learn magic. He ate a lot of hot dogs. This was a person. She never drank coffee. This was a person. She  was training to run a marathon. This was a person. He sang at parties. This was a person. He  loved to make out. This was a person. He loved cigarettes. He was sporty. This was a person. He was a Mac evangelist. This was a person. He wore bow ties. This was a person. He was very good at cleaning. He played a lot of social card games.  This was a person. She slept around. This was a person. She ate a lot of fiber. This was a person. He has four overdue books.  This was a person. He  was sleeping with  his  ex. He  loved to make out. This was a person. She was the richest of  her friends. This was a person. He loved oreos. This was a person. She was a dog person. This was a person. He was afraid of heights. This was a person. He  was a street vendor. He has a suit at the cleaners. This was a person. She ate a lot of fiber. This was a person. She was working  her  way through all of the shows on Netflix. She just had  her car stereo repaired. This was a person. She had just paid a crapload of money to get    teeth fixed. This was a person. He  was a street vendor. This was a person. He was a hoarder. This was a person. He was a crossword whiz. This was a person. He  played soccer every weekend. He was afraid of heights. This was a person. He wrote for the newspaper. This was a person. She always made the mashed potatoes at family get-togethers. This was a person. She  was a street vendor. This was a person. He has a suit at the cleaners. This was a person. She had a green thumb. This was a person. He had a gun. This was a person. He could play harmonica. This was a person. He  had a personal injury lawsuit working its way through the courts. He was an awful driver. This was a person. She kept to herself mostly This was a person. She loved fine dining. This was a person. She had a gun. She threw a lot of parties. This was a person. He  kept buying vegetables, even though they always just went bad in  his fridge. This was a person. He taught guitar. This was a person. She had a green thumb. 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 never carried cash. This was a person. He could play cricket. This was a person. He  was a tailor. This was a person. He loved James Bond movies. This was a person. He was good at job interviews. This was a person. She had a lot of Beatles records. She was a secret Buddahist. This was a person. He ate a lot of chinese food. This was a person. He wore Spandex. This was a person. She had a twin. This was a person. She was rebuilding an engine. She had an awesome home theatre. This was a person. She was always in a hurry. This was a person. She loved chocolate. This was a person. She had braces on  her  teeth. She watched a lot of sports on TV, but never played them  herself. This was a person. He  was a poet. This was a person. She had tropical fish. This was a person. She  went to church. This was a person. He has a suit at the cleaners. This was a person. She ate a lot of raisins. This was a person. She was rebuilding an engine. This was a person. He  was a pharmacist. This was a person. He had a twin. He  had a personal injury lawsuit working its way through the courts. This was a person. She  always bought flowers for  her  desk. This was a person. He played piano. This was a person. He had an unfortunate nickname. This was a person. She  was a DJ. This was a person. She ate a lot of hot dogs. This was a person. He sang. This was a person. She  was a mason. This was a person. She was the richest of  her friends. This was a person. She  did open mike. She was kind of addicted to ebay. This was a person. He picked up litter.  He was balding. This was a person. He overtipped. This was a person. She was kind of addicted to ebay. This was a person. She wore earphones all the time. This was a person. He  was kind of an awesome lover. This was a person. She ate a lot of raisins. This was a person. He made scrapbooks. This was a person. She had an awesome home theatre. She lived on breakfast bars. This was a person. He  was sleeping with  his  ex. He  was a DJ. This was a person. He  was awaiting judgement for a DUI last month. This was a person. She wrote for the newspaper.

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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