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Olympics Data Analysis

Goal

Section titled “Goal”

Use Olympics medals/athletes data to:

  • Rank countries by medals
  • See trends over years
  • Identify top sports

Analysis pipeline

Section titled “Analysis pipeline”
diagram Olympics medal analysis pipeline mermaid
From raw results to a ranked leaderboard of countries and sports.

Step 1: Load

Section titled “Step 1: Load”
Load
import pandas as pd
 
df = pd.read_csv("data/olympics.csv")
print(df.head())

Step 2: Basic counts

Section titled “Step 2: Basic counts”
Medal counts
medals = df.groupby("country").size().sort_values(ascending=False).head(10)
print(medals)

Step 3: Plot top countries

Section titled “Step 3: Plot top countries”
Top countries
import matplotlib.pyplot as plt
 
plt.figure(figsize=(10, 4))
plt.bar(medals.index, medals.values)
plt.title("Top 10 countries by medals")
plt.xticks(rotation=25)
plt.tight_layout()
plt.show()

Visualize it

Section titled “Visualize it”
sketch Top countries by medal count p5.js
Horizontal bars rank countries from most to fewest medals.

Deliverable

Section titled “Deliverable”
  • Top 10 countries
  • Change over years
  • Sports that contribute most

🧪 Try It Yourself

Section titled “🧪 Try It Yourself”

Exercise 1 – Medal counts per country

Section titled “Exercise 1 – Medal counts per country”

Exercise 2 – Top N ranking

Section titled “Exercise 2 – Top N ranking”

Exercise 3 – Medals by year (trend)

Section titled “Exercise 3 – Medals by year (trend)”

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