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29 lis 2023 · The matplotlib.pyplot.scatter () plots serve as a visual tool to explore and analyze the relationships between variables, utilizing dots to depict the connection between them. The matplotlib library provides the scatter () method, specifically designed for creating scatter plots.
matplotlib.pyplot.scatter(x, y, s=None, c=None, marker=None, cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, *, edgecolors=None, plotnonfinite=False, data=None, **kwargs)[source] #. A scatter plot of y vs. x with varying marker size and/or color.
With Pyplot, you can use the scatter() function to draw a scatter plot. The scatter() function plots one dot for each observation. It needs two arrays of the same length, one for the values of the x-axis, and one for values on the y-axis:
In this tutorial, you'll learn how to create scatter plots in Python, which are a key part of many data visualization applications. You'll get an introduction to plt.scatter (), a versatile function in the Matplotlib module for creating scatter plots.
The scatter () function in Matplotlib allows you to create these plots with ease, offering a wide range of customization options to make your visualizations both informative and visually appealing. Let’s start with a basic example of how to create a simple scatter plot using Matplotlib:
This example showcases a simple scatter plot. import matplotlib.pyplot as plt import numpy as np # Fixing random state for reproducibility np . random . seed ( 19680801 ) N = 50 x = np . random . rand ( N ) y = np . random . rand ( N ) colors = np . random . rand ( N ) area = ( 30 * np . random . rand ( N )) ** 2 # 0 to 15 point radii plt ...
scatter(x, y)# A scatter plot of y vs. x with varying marker size and/or color. See scatter.
