Python | How to make scatter plots in python

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Scatter plots

Scatter plots are a type of chart used to visualize the relationship between two variables. They display the data as a collection of points, where each point represents a pair of values for the two variables. Scatter plots are commonly used to identify patterns, trends, and outliers in the data.

In Python, you can create scatter plots using various libraries such as Matplotlib, Seaborn, and Plotly. Here's an example using Matplotlib:

import matplotlib.pyplot as plt

import numpy as np

# Generate some random data

x = np.random.randn(100)

y = np.random.randn(100)

# Create a scatter plot

plt.scatter(x, y)

# Set the title and axis labels

plt.title('Scatter Plot of Random Data')

plt.xlabel('X')

plt.ylabel('Y')

# Show the plot

plt.show()

In this example, we generate 100 random values for the x-axis and y-axis using NumPy. We create a scatter plot using plt.scatter(), where the first argument is the x-axis data and the second argument is the y-axis data. We then set the title and axis labels using plt.title(), plt.xlabel(), and plt.ylabel(), and display the plot using plt.show().

You can also customize the appearance of the scatter plot by specifying the color, size, and other options. For example, to change the color of the points to red, add color='red' to the plt.scatter() call. To change the size of the points to 50, add s=50.