Python Data Analysis Bootcamp class 4 - 02 Seaborn Lineplot

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A lineplot in Seaborn is a valuable choice when you want to visualize the trend or relationship between two continuous variables, typically time-series data or data with a natural ordering. It is particularly useful for showing how a variable changes over a continuous range or a sequence of data points. Lineplots excel in revealing patterns, trends, and fluctuations in the data, making them ideal for exploring and analyzing temporal or ordered datasets in data science applications.

Arguments of Interest:
style (optional): The style argument lets you control the line style (e.g., solid, dashed) of the lines. You can use it to make distinctions between lines more visually apparent.

markers (optional): The markers argument controls whether markers (e.g., points or dots) should be placed at data points along the lines. It can be useful for highlighting individual data points.

errorbar (optional): The errorbar argument determines the confidence interval around the line plot. You can set it to "sd" for standard deviation, "bootstrapped" for bootstrapped confidence intervals, or None to disable confidence intervals.

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