Welcome to the next session on our journey through data visualization! Today, we will dip our toes into the Seaborn library, focusing on aesthetics and styling in our plots. In our previous session, we used Matplotlib to create some simple bar plots. Today, we'll see how Seaborn can help us create visually appealing plots effortlessly.

Defining an aesthetic style before creating your plot is an important aspect of any data visualization. The right choice of colors, sizes, and other aesthetic factors can make your plots more engaging, easy to interpret, and effective at conveying your intended insights.

We'll be looking at three essential elements of styling in Seaborn: figure style, color palette, and plot size. Think of it this way: you're about to paint a masterpiece, and Seaborn provides us with a studio full of tools. Are you ready to create beautiful plots with the Titanic dataset?

Seaborn is a data visualization library built on top of the Matplotlib library in Python. It offers a high-level and easier-to-use interface, as well as attractive and informative statistical graphics.

Let's start by importing Seaborn and setting the aesthetics for all the plots to whitegrid.

import seaborn as sns

# Set the seaborn default aesthetic parameters
sns.set(style="whitegrid")

The style='whitegrid' parameter in the sns.set() creates a white background with gridlines. Five other preset seaborn themes are available: darkgrid, whitegrid, dark, white, and ticks.

You can also set many more aesthetic parameters for your future plots using the sns.set() function. Some of the optional parameters that might customize your plots include:

• palette: Set this to any of the Seaborn color palettes or a custom color palette.
• font: Sets the font for all text in the plot.
• font_scale: Can be used to scale the size of the font elements.
• color_codes: If set to True, shorthand notation can be used for colors in the palette (like 'b' for blue).

For example, to set the palette to Blues, the font to Serif and scale it up 1.2 times, you can use:

sns.set(style="whitegrid", palette="Blues", font="Serif", font_scale=1.2)