Data Visualization - Discover Boxplots

exercise-viz-boxplots.md

Data Visualization - Discover: Boxplots

Iteration 1:

Research what boxplots are, what information they convey, and why they are useful.

Iteration 2:

Open a notebook and load the Titanic dataset:

import seaborn as sns
df = sns.load_dataset("titanic")

Iteration 3:

Render some boxplots, and try to answer the following questions

• a) Is there a relationship between age and pclass (passenger class)? (e.g. did passengers in 1st class tend to be older than those in 2nd and 3rd class?)
• b) Did passengers who survived tend to be younger or older than those who didn't?
• c) How does ticket fare vary across passenger classes — and which class has the most outliers?

Bonus:

• Display other types of plots using that same dataset

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Solutions

Question A

plt.figure(figsize=(4, 6))
sns.boxplot(data=titanic_df, x='pclass', y='age')
plt.xlabel('Passenger Class')
plt.ylabel('Age')
plt.title('Age Distribution by Passenger Class')
plt.show()

Result:

Question B

plt.figure(figsize=(4, 6))
sns.boxplot(data=titanic_df, x='survived', y='age')
plt.xlabel('Survived')
plt.ylabel('Age')
plt.title('Age Distribution by Survival')
plt.show()

Result:

Question C

plt.figure(figsize=(4, 12))
sns.boxplot(data=titanic_df, x='pclass', y='fare')
plt.xlabel('Passenger Class')
plt.ylabel('Fare')
plt.title('Fare Distribution by Passenger Class')
plt.show()

Result: