How can I use Seaborn with Matplotlib for data visualization?

How can I use Seaborn with Matplotlib for data visualization?

You can use Seaborn to create beautiful statistical graphics that integrate well with Matplotlib. First, install Seaborn using pip install seaborn. Then, you can create plots using Seaborn functions and customize them with Matplotlib.

Can you show me an example of a scatter plot using Seaborn?

Sure! Here's a simple example:

import seaborn as sns
import matplotlib.pyplot as plt

# Load an example dataset
iris = sns.load_dataset('iris')

# Create a scatter plot
sns.scatterplot(data=iris, x='sepal_length', y='sepal_width', hue='species')
plt.title('Iris Sepal Length vs Width')
plt.show()

What if I want to customize the colors and style?

You can customize the colors and style by using the palette parameter and setting the style with sns.set_style(). For example:

sns.set_style('whitegrid')
sns.scatterplot(data=iris, x='sepal_length', y='sepal_width', hue='species', palette='deep')

Can I save the plot as an image file?

Yes, you can save the plot using plt.savefig('filename.png') before calling plt.show(). This will save your plot as a PNG file.