Seaborn Overview: Statistical Data Visualization

Seaborn Overview

Seaborn builds on Matplotlib to simplify creation of attractive statistical graphics.

Installing Seaborn

pip install seaborn

Basic scatter with regression line

import seaborn as sns
import pandas as pd

tips = pd.DataFrame({
    "hours": np.random.randint(1, 10, 100),
    "score": np.random.randint(50, 100, 100)
})

sns.lmplot(x='hours', y='score', data=tips, aspect=1.5)
plt.title('Hours Studied vs. Score')
plt.show()

Pairplot (matrix of scatter + histograms)

iris = sns.load_dataset('iris')
sns.pairplot(iris, hue='species', height=2.5)
plt.show()

Distribution plot (hist + KDE)

sns.distplot(tips['hours'], kde=True, bins=10, color='orange')
plt.title('Distribution of Study Hours')
plt.show()