EnTC A3 Group 1 | B.Tech Sem 2

Student Daily Commute Analysis

Uncovering patterns, insights, and trends in student commuting behavior across Pune city through comprehensive EDA.

724 Records
16+ Visualizations
6 Transport Modes
Scroll to explore
Overview

Understanding the Problem

Students in Pune face significant challenges in daily commuting. This analysis quantifies these challenges and identifies actionable patterns.

Problem Statement

Students face long travel times, high costs, and unreliable transport. We aim to quantify these challenges and identify improvement opportunities.

Key Objectives

  • Analyze transport mode preferences
  • Identify peak commute patterns
  • Quantify cost vs. time trade-offs

Real-World Impact

Actionable insights for city planners, institutions, and transport authorities to improve student commute infrastructure.

Dataset

724 Student Records

Collected via Google Forms from students across various locations in Pune, capturing real-world commute experiences.

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Total Records
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Features
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Starting Points
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Transport Modes

Starting Point

Kothrud, Wakad, Baner, Pashan, Shivajinagar, SIT Lavale Campus, Other

Destination

Hinjewadi, Kharadi, Viman Nagar, Swargate, Pune Station, Other

Primary Transport

Metro, PMPML Bus, Cab, Two-Wheeler, Auto, Carpool

Time of Day

Morning Peak, Midday, Evening Peak, Night

Travel Time & Cost

20-119 minutes | ₹10-₹445 one-way

Delay Points

Hinjewadi Traffic, Chandni Chowk, University Circle, Yerawada Junction, Bus/Metro Wait

Sample Data Preview

Starting Point Destination Primary Mode Time of Day Travel Time Cost Satisfaction
Analysis

Visualizations

Interactive charts revealing patterns in student commute data.

Transport Mode Preferences

Distribution of students by their primary transport choice

Time & Cost Distribution

How commute duration and expenses vary across students

Delay Points & Satisfaction

Major bottlenecks and overall commute satisfaction

Average Metrics by Mode

Comparing travel time and cost across transport types

Correlation Analysis

Relationship between Travel Time, Cost, and Satisfaction

Mode Usage Patterns

How transport choices vary across time slots

Distribution Analysis

Understanding variance and outliers in commute data

Geographic Distribution

Student distribution and transport preferences by area

Multi-Dimensional Analysis

Exploring relationships between time, cost, and satisfaction

Key Insights

What the Data Reveals

Critical findings and actionable insights from our analysis.

Metro is the Winner

Lowest average cost (₹24) and fastest travel times (~41 min), making it the best value for money.

21% of students prefer Metro

Hinjewadi Traffic Crisis

Most reported bottleneck (17% of delays), followed by University Circle and Bus/Metro wait times.

83 delays reported at Hinjewadi

Cost-Time Trade-off

Cabs cost 10x more than Metro but save only ~5 minutes average - poor cost efficiency.

10x cost minimal time savings

Morning Peak Dominance

35% of commutes happen during morning peak (8-11 AM), the key optimization target.

254 trips during morning rush

Satisfaction Paradox

No strong correlation with cost or time - subjective factors like comfort matter significantly.

Average: 2.95/5 moderate satisfaction

Kothrud: The Hub

Highest commuter representation (15.7%), indicating significant outbound student population.

114 students from Kothrud area

Key Patterns

  • Metro dominates as preferred transport due to cost-effectiveness and reliability
  • Morning peak hours see the highest commute volume across all modes
  • Traffic bottlenecks significantly impact PMPML Bus users
  • Cost-time efficiency favors public transport over personal vehicles

Recommendations

  • Expand Metro coverage to underserved areas like Hinjewadi and Kharadi
  • Implement traffic management at identified bottleneck locations
  • Introduce dedicated bus lanes during peak hours
  • Consider student discount programs for public transport
Team

Meet the Team

EnTC A3 Group 1 | B.Tech Semester 2

TA
Developer

Tanmay Agarwal

PRN: 25070123158

Data Analysis, Visualization & Web Development

EDA Analysis Documentation
TG
Co-Developer

Tannishtha Gupta

PRN: 25070123049

Research, Data Collection & Presentation

Data Collection Presentation

Under the guidance of EDA Faculty: Mrs. Snehal Bhosale Ma'am

Symbiosis Institute of Technology, Pune