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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 was a trivia master. She was afraid of the water. This was a person. He loved nachos. He slept around. This was a person. He  was a tailor. This was a person. She had a gun. This was a person. He  was a teacher. This was a person. She did not own a fridge. This was a person. He never carried cash. This was a person. She once robbed a bank. She loved MASH. This was a person. He helped people. This was a person. He ate a lot of kale. This was a person. She had tropical fish. This was a person. She was a crossword whiz. She knew a lot of cops. This was a person. He  collected figurines. This was a person. He made scrapbooks. This was a person. She  got a terrible haircut a few days ago and shaved  her  head to escape from it. She  did open mike. This was a person. He ate a lot of kale. He sang. This was a person. She had extensions. This was a person. He had extensions. He knew how to get free satelittle television. This was a person. He was kind of addicted to ebay. He helped people. This was a person. She was afraid of the water. This was a person. He had a lot of music on vinyl. This was a person. He  was a teacher. This was a person. He always had gum. He spent a lot of time with old people. This was a person. He played piano. This was a person. She plays fantasy football. This was a person. He was very good at cleaning. This was a person. He  had VD. This was a person. She had a bunch of cameras. She was polite to telemarketers. This was a person. She loved pot. This was a person. She  only ever had sex with one person. This was a person. She has two living parents. This was a person. She did not sleep with a pillow. This was a person. He spends a lot of time watching tennis. He loved MASH. This was a person. He  was kind of an awesome lover. This was a person. He never finished the book club book. This was a person. She looked like a cartoon. This was a person. He  played soccer every weekend. This was a person. She wore bow ties. This was a person. She  was afraid of flying. She  was a poet. This was a person. He had extensions. This was a person. She could play cricket. This was a person. She was a skilled woodcarver. She brought great food to social gatherings. This was a person. He  loved to make out. He  played soccer every weekend. This was a person. He slept around. This was a person. She  was a plumber. This was a person. He loved Elvis. This was a person. She ate a lot of raisins. This was a person. He ate a lot of fiber. This was a person. He was a wedding photographer. This was a person. He was a good dancer. This was a person. She had crazy hair colors. She had a green thumb. This was a person. She loved Elvis. This was a person. She was rebuilding an engine. This was a person. He ate a lot of raisins. He was sporty. This was a person. She was polite to telemarketers. This was a person. He did not sleep with a pillow. He never ate breakfast. This was a person. He always had gum. This was a person. She never finished the book club book. This was a person. She talked during movies. She always brought lunch. This was a person. He could play banjo. 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 played World of Warcraft This was a person. He loved oreos. He had bonsai trees. This was a person. She just had  her car stereo repaired. This was a person. She was a cat person. This was a person. She had just paid a crapload of money to get   her teeth fixed. This was a person. He  was a street vendor. This was a person. She  was a plumber. This was a person. She could play banjo. This was a person. He tutored kids. This was a person. He had an awesome home theatre. This was a person. She  was a virgin. This was a person. He spent a lot of time with old people. This was a person. She helped people. This was a person. She  played soccer every weekend. This was a person. He slept around. This was a person. She spent a lot of time with old people. This was a person. She can't watch the end of T2 without crying This was a person. She  was a mason. This was a person. He  was a drunk. He can't watch the end of T2 without crying This was a person. He wore Spandex. He went to the horseraces. This was a person. She could play cricket. She was very careful about conserving gasoline. This was a person. She could fix anything. This was a person. She had a gun. This was a person. He couldn't grow a mustache. This was a person. He  was a poet. This was a person. He was very good at cleaning. This was a person. She  was learning to speak French. She  could always get tickets. This was a person. She  was learning to speak French. This was a person. He was a crossword whiz. This was a person. She constantly wore sunglasses. This was a person. He always had gum. This was a person. She was the unofficial relationship guru among  her friends. She led the choir. This was a person. He could fall asleep anywhere. This was a person. He  was a historian. He just had  his car stereo repaired. This was a person. She  was a poet. She  went to church. This was a person. He  was a drunk. This was a person. He loved cigarettes. This was a person. She could fall asleep anywhere. This was a person. She was gluten intolerant.

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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