Day 22 of the #30DayMapChallenge - Null. Here is a map showing the world according to human impact. The darker an area, the greater the human impact. The light areas are our "Null" areas - areas untouched by humans. #DataScience #humanity #Datavisualization #ClimateCrisis

Day 13 of the #30DayMapChallenge - 5 minute map. Where do the world's carbon dioxide emissions come from? Lighter areas indicate areas with higher emissions. This map was made with #Python using #matplotlib. #DataScience #Data #DataVisualization #ClimateAction #ClimateEmergency

Day 14 of the #30DayMapChallenge - Hexagons. This map shows the population density of London. It maps population from low (dark red - 100 people) to high (white - 10,000 people). Made with #Python using #matplotlib, #Pandas and #Numpy. #DataScience #DataVisualization #Map

Day 9 of the #30DayMapChallenge - Space. Topography map of Mars with some labelled features. This map was made with #Python using #Numpy and #matplotlib. #DataScience #DataVisualization #solarsystem #Mars #thefinalfrontier

Day 6 of the #30DayMapChallenge - Network. Mapping the world's flight paths and airports. This map shows 67,663 routes between 3,321 airports. Made with #Python using #matplotlib. #DataScience #DataVisualization

Day 1 of the #30daymapchallenge - Points. Here is a map showing the world's ports. Made with #Python using #matplotlib and #Numpy. #DataScience #DataVisualization #Map #Geography #dataviz #data #DataScientist

Westeros, but in google maps format

Population density of South America.