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The correct method to create a scatter plot using Seaborn is sns.scatterplot(). This method is specifically designed to visualize the relationship between two continuous variables. The function takes x and y as the input variables and data as the DataFrame from which these variables are extracted. Scatter plots are ideal for visualizing the correlation or relationship between two variables, helping identify patterns such as clustering or outliers. Why Other Options Are Incorrect: • A: sns.lineplot() is used to create line plots, which are appropriate for visualizing trends over time or continuous data but not for visualizing relationships between two independent variables like in a scatter plot. • C: sns.histplot() is used for creating histograms, which are useful for visualizing the distribution of a single variable, not for visualizing relationships between two variables. • D: sns.boxplot() is used for displaying the distribution of a variable and identifying outliers, but it is not used for visualizing relationships between two continuous variables. • E: sns.heatmap() is used to display a matrix of data values, typically for visualizing correlation matrices or other matrix-like data, but it is not suited for scatter plots of two variables.
If 30 $ 90 % 40 = c, then the value of 5 @ c # 20
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