Distribution of Active Vehicles Across Dispatching Base Numbers

🚗 Violin Plot Analysis of Active Vehicles by Dispatching Base

This guide explains how to analyze Uber active vehicle data using a violin plot. You'll learn not just how to plot it—but how to interpret it like a data expert.

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📚 Table of Contents

• Introduction
• Code Example
• CLI Output
• Understanding Violin Plots
• Math Behind Distribution
• Analysis Strategy
• Interactive Sections
• Key Takeaways
• Related Articles

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📊 Introduction

The goal is to identify which dispatching base number has the most active vehicles using data visualization.

Instead of simple charts, we use a violin plot to capture:

• Distribution
• Density
• Median values

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💻 Code Example

import plotly.express as px from lecUberAnalysis import uber_foil map_active = px.violin( x='dispatching_base_number', y='active_vehicles', data_frame=uber_foil ) map_active.show()

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🖥️ CLI Output (Visualization)

Click to Expand Output

Plot rendered successfully
X-axis: dispatching_base_number
Y-axis: active_vehicles
Each violin represents distribution per base

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🎻 Understanding Violin Plots

A violin plot is a combination of:

• Box plot 📦
• Density plot 📈

Wider sections = more data points Narrow sections = fewer data points

Key components:

• Median line
• Distribution shape
• Spread of values

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📐 Math Behind Distribution (Simple)

1. Probability Density Function

\[ f(x) \]

This function shows how data is distributed.

Simple Explanation:

Instead of counting values, we estimate how densely values occur.

2. Kernel Density Estimation (KDE)

\[ \hat{f}(x) = \frac{1}{nh} \sum K\left(\frac{x - x_i}{h}\right) \]

Breakdown:

• \(n\): number of data points
• \(h\): smoothing factor
• \(K\): kernel function

Think of KDE like smoothing a histogram to make it continuous.

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🔍 How to Analyze the Plot

Step 1: Look at Width

Wider violin = more frequent values

Step 2: Check Height

Taller violin = higher range of active vehicles

Step 3: Observe Median

The central line shows typical value

Step 4: Compare All Bases

Find which base has:

• Highest median
• Largest spread
• Widest density

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📊 Example Interpretation

Base	Observation
B02512	High density at large values
B02617	Moderate distribution
B02764	Lower active vehicles

👉 Conclusion: Base with widest & highest violin likely has most vehicles.

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🧩 Interactive Exploration

What happens if data is skewed?

The violin becomes uneven, showing imbalance in distribution.

What if all values are same?

The violin becomes a thin line.

Why not use bar chart?

Bar charts hide distribution details.

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💡 Key Takeaways

• Violin plots show full data distribution
• Width indicates density
• Median helps identify typical values
• Best for comparing multiple categories

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🎯 Final Conclusion

Violin plots provide a powerful way to understand not just how many vehicles exist—but how they are distributed across different dispatching bases.

By focusing on density, spread, and median, you can confidently identify the base with the most active vehicles.