How can I create advanced visualizations using Seaborn in Jupyter?

How can I create advanced visualizations using Seaborn in Jupyter?

You can create advanced visualizations in Seaborn by using functions like pairplot, heatmap, and violinplot. Would you like a specific example?

Yes, can you show me how to create a heatmap?

Sure! First, you'll need to import Seaborn and Matplotlib. Then, you can use the heatmap function on a correlation matrix. Here's a quick example:

import seaborn as sns
import matplotlib.pyplot as plt

# Load dataset
flights = sns.load_dataset('flights')

# Create a pivot table
pivot_flights = flights.pivot_table(index='month', columns='year', values='passengers')

# Create a heatmap
sns.heatmap(pivot_flights, annot=True, fmt='d')
plt.show()

What does the annot=True parameter do?

The annot=True parameter adds the data values to each cell in the heatmap, making it easier to read the exact numbers.