We mentioned that the ``seaborn`` is based on the ``matplotlib``.  That is why all ``seaborn`` styles are set using ``matplotlib`` functions. 

We can use the ``axes_style()`` function with no arguments to see which functions are used for the current style. 

And then, we have the opportunity to adjust the desired parameters manually and create our unique style! 

To change individual **style settings manually**: 

```python
import seaborn as sns
# Setting the unique style
sns.set_style('style_name', {'axes.facecolor': 'red', 'grid.color': 'black',...})
```

**Try this code to look at the customized plot:**

import seaborn as sns
import numpy as np
import matplotlib.pyplot as plt

# Generate random data for the line plot
x = np.linspace(0, 10, 100)
y = np.sin(x)

# Set the style of the plot using sns.set_style()
sns.set_style('whitegrid', {'axes.facecolor': 'lightgrey', 'grid.color': 'white', 'grid.linewidth': 1})

# Create the line plot using sns.lineplot()
sns.lineplot(x = x, y = y, color = 'blue')

# Add a title and axis labels to the plot
plt.title('Lineplot')
plt.xlabel('X-axis')
plt.ylabel('Y-axis')

# Display the plot
plt.show()

Together we will make the first dive into visualization based on a seaborn library. We will learn how to build simple plots and how to customize them. You will cope faster with tasks if you know something about pandas. Do not hesitate, and let's go!

In this section, we will learn about the seaborn library and build our first plot! We will also learn about the friendship between the pandas and the Seaborn.

We continue learning plots with Seaborn.\n\nYou will learn some more new plots and even build 3-variable plot!

Plots seem so boring without customization...\nIn this section, we will learn how to make our plots perfectly styled!!

I'm an Artist, that's how I See it!

Task

First Dive into seaborn Visualization

I'm an Artist, that's how I See it!

Task