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https://github.com/mihirh19/uber-analysis

Uber's 2016 dataset analysis offers insightful information about the company's operations and user behaviour. Patterns and trends can be discovered by looking at variables like trip time, distance travelled, and pickup/drop-off locations. Uber may use this information to detect high-demand locations, increase overall efficiency, and optimise driver
https://github.com/mihirh19/uber-analysis

matplotlib numpy opendatasets pandas seaborn

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Uber's 2016 dataset analysis offers insightful information about the company's operations and user behaviour. Patterns and trends can be discovered by looking at variables like trip time, distance travelled, and pickup/drop-off locations. Uber may use this information to detect high-demand locations, increase overall efficiency, and optimise driver

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