Final answer:
To combine two scatter plots in Python, use the 'matplotlib' library to plot both sets of data. Differentiate the datasets with colors and add a legend for clarity. Customize the appearance as needed and label your plot for context.
Step-by-step explanation:
To combine two scatter plots in Python, you can use a library such as matplotlib, which is a widely used data visualization library. Here's a basic example of how you can accomplish this:
import matplotlib.pyplot as plt
# Data for the first scatter plot
x1 = [1, 2, 3, 4]
y1 = [10, 20, 25, 30]
# Data for the second scatter plot
x2 = [2, 3, 4, 5]
y2 = [30, 40, 50, 60]
# Create the first scatter plot
plt.scatter(x1, y1, color='blue', label='Dataset 1')
# Create the second scatter plot
plt.scatter(x2, y2, color='red', label='Dataset 2')
# Adding legend to differentiate the datasets
plt.legend()
# Show the combined plot
plt.show()
This will display a single figure with two scatter plots overlaid on each other. You can customize the appearance of the plots by changing the colors, markers, and other properties. The plt.legend() function is used to add a legend to the plot so that the two datasets can be distinguished. Remember to always label your axes and provide an appropriate title to make your plot informative.