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Inside Airbnb: Visualizing data that includes geographic locations

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Inside Airbnb: Visualizing data that includes geographic locations
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Inside Airbnb: Visualizing data that includes geographic locations [EuroPython 2017 - Talk - 2017-07-13 - Anfiteatro 1] [Rimini, Italy] This talk is about creating visualizations for data that includes geographical locations. We will be using data from InsideAirbnb.com to represent the current status of Airbnb listings in Mallorca. We will show practical examples of different visualizations of geographical data: First, we will start with how to use bokeh to overlay data on google maps. We will use examples to show how the GMapPlot interface works. We will briefly explain how to use it, and what are its limitations. Then, we will talk about plotting shapefiles with holoviews. Shapefiles are files that describe the shape of maps. We will explain how to deal with shapefiles. For instance, we will describe how we use shapefiles to group geographical data by regions. We will also briefly explain how holoviews works and how it can be used to display geographical data. Moreover, we will talk about using datashader and geoviews to visualize big data. First, we will briefly introduce datashader, bin based plotting and the datashader Pipeline. After that, we will show how to create plots with geoviews: how is the Interface, a few use cases and some examples. Finally, we will move to plotting big data on interactive maps. Eventually we will finish with dynamic maps for visualizing time series: we will explain how do we do it and show some examples of how to build an interactive dashboard for visualizing geographical data that varies over time