Using the Alteryx for CARTO connector, we brought bike trip data from Transport for London and weather data from Met Office into CARTO. With Builder, we explored the bike trip and weather data, and then visualized the results.
The maps below visualize different dimensions of our analysis and each one is equiped with a set of widgets to facilitate deeper exploration.
The first map visualizes London bike trips connected from start station to end station over a one week time period. Using this map, you can isolate trips by station of origin (Start Station), destination station (End Station), follow the trip of a particular bike (Bike ID), and the length of the trip (Duration). You can also explore the bike trips for a certain time period using the Torque time-series slider.
The second map aggregates a year of bike trips to each London ward. The point symbols are scaled by the total number of bike trips to, from, or inside of each ward (click a point to see the breakdown). The lines connect wards that had either inbound or outbound trips between them scaling the line symbol by trips between any two wards. You can explore the connections between wards by filtering on either Trip Start Ward or Trip End Ward.
The third map shows a years worth of bike accident data augmented with weather data. Each accident is color coded according to severity. Using the widgets, you can filter by time period and/or various atmospheric conditions like wind speed, temperature, weather, and more. For additional context, we added in bike route data from OpenStreetMap. This map is a great example of how combining two datasets (in this case bike accidents and weather), with the ability to filter using widgets, really helps dig into the why and the how.
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Happy Bike Trip Mapping!
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