![]() ![]() These are not magic, but I think that they are helpful. The following is a simple scatter plot created using Matplotlib library. The purpose of S2 is to downsample the data S2 sample (3000000, 100000) plot (x S2,y S2, pch20, cex0.4, colrainbow (3, alpha0.1) z S2) This gives a different view that provides a similar, but not identical understanding of the two distributions. ![]() X-axis represents an attribute namely sepal length and Y-axis represents the attribute namely sepal width. The following represents a sample scatter plot representing three different classes / species for IRIS flower data set. The scatter plot would show how different types of food make people feel different levels of fullness, satisfaction, and energy. For example, a scatter plot could be used to visualize the relationship between different types of food and how they make people feel. scatter plots can also be used to visualize relationships between non-numerical data sets. The scatter plot would show how the weight and height of different people are related. Visualize the relationship between two variables For example, a scatter plot could be used to visualize the relationship between someone’s weight and their height.Outlier detection can be used to find errors in data, or to identify unusual data points that may require further investigation. Outliers are typically easy to spot on a scatter plot, as they will lie outside the general trend of the data. The scatter plot can then be analyzed to look for patterns and trends. To create a scatter plot, the data points are plotted on a coordinate grid, and then a line is drawn to connect the points. Detect outliers: Scatter plots are often used to detect outliers, or data points that lie outside the general trend.For example, scatter plots can be used to show the distribution of ages in a population, the distribution of heights in a population, or the distribution of grades in a classroom. ![]()
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