Python - Matplotlib Pyplot Part 2: Scatter Plots

Scatter plots are useful for visualizing relationships between two variables.

Examples and Explanation

Basic Scatter Plot

plt.scatter([1, 2, 3, 4], [10, 20, 25, 30])

plt.title("Basic Scatter Plot")

plt.show()

Explanation: The scatter() function creates scatter plots with individual data points.

Customizing Scatter Points

sizes = [50, 100, 150, 200]

colors = ['red', 'blue', 'green', 'orange']

plt.scatter([1, 2, 3, 4], [10, 20, 25, 30], s=sizes, c=colors, alpha=0.5)

plt.title("Customized Scatter Plot")

plt.show()

Explanation: Adjusting size, color, and transparency of scatter points makes it easier to represent additional dimensions.

Overlaying Scatter and Line Plots

plt.plot([1, 2, 3, 4], [10, 20, 30, 40], linestyle='--')

plt.scatter([1, 2, 3, 4], [10, 20, 30, 40], color='red')

plt.title("Scatter and Line Overlay")

plt.show()

Explanation: Combining scatter and line plots provides a clearer representation of trends.