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UBER DATA ANALYSIS by TeamOverFlow

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This project aims to:

  • Visualize Uber's ridership growth in NYC in 2014 and 2018.
  • Visualize pickup coordinates in a real-time map.
  • Characterize the demand based on the identified data from the dataset.
  • Estimate the predicted fare using the extracted features from the dataset using two ML Models.
  • Compare UBER and LYFT on the basis of the number of service cars available and the number of customers in each service.

REQUIREMENTS: The code is written in a Jupyter Notebook with a Python 3.9 kernel and in addition, it requires the following packages:

SNIPPETS FROM THE NOTEBOOK:

map

PICKUP LOCATIONS of UBER CUSTOMERS

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Heat Map of UBER RIDES

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