How can I create advanced visualizations using Seaborn in Jupyter Notebook?

How can I create advanced visualizations using Seaborn in Jupyter Notebook?

You can create advanced visualizations in Seaborn by using functions like sns.pairplot(), sns.heatmap(), and customizing them with parameters.

Can you show me an example of a heatmap?

Sure! First, you need to import Seaborn and Matplotlib. Then, you can use the following code:

import seaborn as sns
import matplotlib.pyplot as plt

# Sample data
data = sns.load_dataset('flights')

# Pivot the data
pivot_data = data.pivot('month', 'year', 'passengers')

# Create a heatmap
sns.heatmap(pivot_data, annot=True, fmt='d')
plt.title('Number of Passengers per Month')
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.

How can I customize the color palette of the heatmap?

You can customize the color palette by using the cmap parameter. For example, sns.heatmap(pivot_data, cmap='coolwarm') will change the color scheme.