Data Visualization with Matplotlib and Seaborn

Data Visualization with Matplotlib and Seaborn

Matplotlib:

1. What is Matplotlib?

• Matplotlib is a versatile 2D plotting library for Python.
• It provides a wide range of plot types and customization options.

2. Basic Plotting:

• Create line plots, scatter plots, bar plots, and more using matplotlib.pyplot.

3. Customization:

• Customize plots with labels, titles, axes, and legends.
• Control colors, markers, and line styles.

4. Subplots and Layouts:

• Create multiple plots within the same figure using plt.subplot().
• Adjust layout using plt.subplots().

5. Save and Export:

• Save plots as image files using plt.savefig().

Seaborn:

1. What is Seaborn?

• Seaborn is a statistical data visualization library based on Matplotlib.
• It simplifies creating informative and attractive visualizations.

2. Built-in Themes and Color Palettes:

• Seaborn offers attractive themes and color palettes by default.
• Set themes using seaborn.set_style().

3. Statistical Plots:

• Create specialized plots like box plots, violin plots, and pair plots.
• Use functions like seaborn.boxplot() and seaborn.violinplot().

4. Categorical Plots:

• Create bar plots, count plots, and more for categorical data.
• Use functions like seaborn.barplot() and seaborn.countplot().

5. Regression and Distribution Plots:

• Visualize linear regression with seaborn.regplot() and seaborn.lmplot().
• Plot distributions using seaborn.distplot() and seaborn.kdeplot().

Example:

Here's a basic example illustrating the use of Matplotlib and Seaborn:

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

# Generate sample data
x = np.linspace(0, 10, 100)
y = np.sin(x)

# Matplotlib example: line plot
plt.plot(x, y, label="sin(x)")
plt.xlabel("X-axis")
plt.ylabel("Y-axis")
plt.title("Matplotlib Line Plot")
plt.legend()
plt.show()

# Seaborn example: scatter plot
sns.set_style("whitegrid")
data = sns.load_dataset("iris")
sns.scatterplot(x="sepal_length", y="sepal_width", hue="species", data=data)
plt.title("Seaborn Scatter Plot")
plt.show()
      

In this example, we use Matplotlib to create a line plot and Seaborn to create a scatter plot with color-coded data points.

Both Matplotlib and Seaborn offer extensive documentation and a variety of visualization options to suit different types of data and insights. These libraries are essential tools for effectively conveying information through visual representations.