Uber Drives Data Analysis

Project Overview

Uber Technologies, Inc. is a global ride-hailing company providing transportation and logistics services. This project analyzes Uber trip data to understand travel behavior, peak usage times, trip purposes, and location-based demand, helping derive actionable business insights.

Project Objective

The objective of this project is to:

• Analyze Uber ride patterns

• Identify peak travel times and days

• Understand trip duration and distance behavior

• Examine trip purposes and starting locations

• Provide data-driven business insights and recommendations

Dataset Description

The dataset contains Uber trip records from 2016, with the following features:

Column Name --------- Description

• START_DATE --------- Trip start date and time

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• END_DATE --------- Trip end date and time

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• CATEGORY --------- Business or Personal trip

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• START --------- Trip starting location

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• STOP --------- Trip ending location

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• MILES --------- Distance traveled (miles)

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• PURPOSE --------- Purpose of the trip

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Tools & Technologies Used

• Python

• Pandas & NumPy – Data manipulation

• Matplotlib & Seaborn – Data visualization

• SciPy – Statistical analysis

• google colab

• Tableau - Data Visualization

Key Insights

• Most Uber trips are short-distance (≤10 miles) and short-duration (≤30 minutes)

• Demand peaks during Afternoon and Evening hours

• Business trips dominate (~93%) and tend to be longer

• Friday is the busiest day

• December has the highest monthly trip volume

• Trip demand is concentrated in specific urban locations

Business Recommendations

• Optimize driver availability during peak business hours

• Strengthen corporate travel offerings

• Improve trip purpose and location data quality

• Focus operational planning on high-demand days and seasons

Limitations

• Dataset is skewed toward business trips

• Presence of unknown trip purposes and locations

• Analysis is based on a single year of data

Conclusion

This project demonstrates an end-to-end data analysis workflow, transforming raw Uber trip data into meaningful business insights. The findings can help improve operational efficiency, customer experience, and strategic decision-making.

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Tableau Dashboard Link :- https://public.tableau.com/app/profile/jiyansh.garg/viz/UberDriveDataAnalysis/Dashboard1