Sharpeville Massacre Tragedy Casualties Visualization Tool - Cockeyed.com

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Disaster Casualties Visualization Tool: Sharpeville Massacre: 1960

69 Dead Men and Women

The Sharpeville massacre at the police station in the South African township of Sharpeville. After a day of demonstrations the South African police opened fire on the crowd of black protesters killing 69 people.

This was a person. She constantly wore sunglasses. She had bonsai trees.

This was a person. She could play banjo.

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

This was a person. He scalped tickets

This was a person. She was the richest of her friends. She had a bunch of cameras.

This was a person. He sang at parties.

This was a person. She had a gun.

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

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

This was a person. She just had her car stereo repaired.

This was a person. She could juggle.

This was a person. He had long fingernails.

This was a person. She was an awful driver.

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

This was a person. She went to church.

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

This was a person. She loved to fish.

This was a person. She did not own a fridge.

This was a person. He was working his way through all of the shows on Netflix. He loved to fish.

This was a person. He once robbed a bank.

This was a person. He was an expert barbecuer.

This was a person. He was homophobic.

This was a person. He was a Mac evangelist.

This was a person. She chewed gum constantly.

This was a person. She loved James Bond movies.

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

This was a person. She was a skilled woodcarver. She lived on breakfast bars.

This was a person. She was cockeyed.

This was a person. He was working his way through all of the shows on Netflix.

This was a person. She was an expert barbecuer.

This was a person. He never ate breakfast.

This was a person. She had VD.

This was a person. He slept around. He played chess.

This was a person. He knew how to get free satelittle television. He played guitar on the streets for money.

This was a person. He was a trivia master.

This was a person. He made pie.

This was a person. He could play cricket.

This was a person. He was a cheapskate.

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

This was a person. She overtipped. She chewed nicotine gum.

This was a person. She did open mike. She was a Mac evangelist.

This was a person. He was a DJ.

This was a person. She loved cigarettes.

This was a person. She was a historian.

This was a person. She wanted to learn magic.

This was a person. He was a pharmacist.

This was a person. She sang. She went to the horseraces.

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

This was a person. She loved cigarettes.

This was a person. She was polite to telemarketers.

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

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

This was a person. He got thrown off of a golf course.

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

This was a person. She loved oreos.

This was a person. She was a cat person. She kept to herself mostly

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

This was a person. She had extensions.

This was a person. He made his own beer and was kind of stingy with it.

This was a person. She never raised hervoice.

This was a person. She looked like a cartoon. She wore a lot of hats.

This was a person. She was a poet. She scalped tickets

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

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

This was a person. She was good at job interviews. She loved wine.

This was a person. She loved James Bond movies. She loved to fish.

This was a person. He was a cheapskate. He played chess.

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

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

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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The Weight of Clothing

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