Introduction

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Creating Scatter Plots in Python

Introduction

Scatter plots are a type of data visualization that displays the relationship between two variables. They are useful for identifying trends and patterns in data, as well as for exploring the relationship between different variables. In this tutorial, you will learn how to create scatter plots using the matplotlib library in Python.

Creating a Scatter Plot

To create a scatter plot, you will need to import the matplotlib.pyplot library and use the scatter() function. The scatter() function takes two arrays as input: one for the x-values and one for the y-values. The function will then plot a dot for each pair of values in the arrays.

 import matplotlib.pyplot as plt  # Create a scatter plot of y vs. x plt.scatter(x, y)  # Show the plot plt.show() 

Customizing the Scatter Plot

You can customize the appearance of your scatter plot by changing the size, color, and shape of the markers. You can also add labels to the axes and a title to the plot.

 # Change the marker size plt.scatter(x, y, s=100)  # Change the marker color plt.scatter(x, y, c='blue')  # Change the marker shape plt.scatter(x, y, marker='o')  # Add labels to the axes plt.xlabel('X-axis') plt.ylabel('Y-axis')  # Add a title to the plot plt.title('Scatter Plot of Y vs. X') 

Conclusion

Scatter plots are a powerful tool for visualizing the relationship between two variables. They are easy to create and can be customized to meet your specific needs. By understanding how to create scatter plots, you will be able to better understand your data and make more informed decisions.

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