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
Last synced: 6 months ago
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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
- Host: GitHub
- URL: https://github.com/mihirh19/uber-analysis
- Owner: mihirh19
- License: mit
- Created: 2023-06-28T04:25:05.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-09-19T17:05:14.000Z (over 2 years ago)
- Last Synced: 2025-04-02T00:45:26.545Z (10 months ago)
- Topics: matplotlib, numpy, opendatasets, pandas, seaborn
- Language: Jupyter Notebook
- Homepage: https://deepnote.com/@mihirh21/uber-analysis-4a787782-2a67-46b8-b041-73b60a0740d6
- Size: 680 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0