Global Terrorism Database Analysis

Goal

Use GTD-like incident data to:

• Visualize incidents over time
• Compare regions
• Identify major trend changes

Important note

This is a sensitive dataset. Focus on high-level aggregated analysis and avoid sensationalizing.

Analysis pipeline

diagram GTD trend analysis pipeline mermaid

  flowchart LR
  A["Raw incidents"] --> B["Aggregate
(by year, region)"]
  B --> C["Visualize
(trend line, top regions)"]
  C --> D["Caveat
(missing/reporting bias)"]
  D --> E["Conclude
(high-level summary)"]

From raw incident records to a responsible, aggregated summary.

From the book

When McKinney hits missing values in the Bitly tz field, he doesn’t silently drop them — he buckets them as "Unknown" so the count is honest about what’s actually known. Do the same with incident data: a region with sparse or inconsistent reporting isn’t necessarily “safer,” it may just be under-recorded. Always caption aggregated charts with a note about missingness and reporting bias.

Step 1: Load

Load

import pandas as pd
 
df = pd.read_csv("data/gtd.csv")
print(df.head())

Step 2: Incidents by year

Incidents per year

import matplotlib.pyplot as plt
 
yearly = df.groupby("year").size()
 
plt.figure(figsize=(10, 4))
plt.plot(yearly.index, yearly.values)
plt.title("Incidents by year")
plt.xlabel("Year")
plt.ylabel("Count")
plt.tight_layout()
plt.show()

Step 3: Compare regions

Top regions

import seaborn as sns
import matplotlib.pyplot as plt
 
regions = df["region"].value_counts().head(10).reset_index()
regions.columns = ["region", "count"]
 
plt.figure(figsize=(10, 4))
sns.barplot(data=regions, x="count", y="region")
plt.title("Top regions by incident count")
plt.tight_layout()
plt.show()

Visualize it

sketch Incidents by year p5.js Pause Restart

A single amber line shows the overall trend across years; annotate any sharp turns.

Deliverable

• Overall trend
• Top regions by incidents
• Notes about missingness/reporting bias

🧪 Try It Yourself

Exercise 1 – Incidents per year

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Exercise 2 – Top regions by incident count

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Exercise 3 – Bucket missing region as “Unknown”

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