Python Data Anlaysis Bootcamp class 4 - 01 Seaborn Barplot

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Barplots in Seaborn are typically used when you want to visualize and compare categorical data, such as showing the distribution of a particular variable across different categories or groups. They are particularly useful for displaying the central tendency and variability within each category, making it easier to discern patterns and trends in the data. Additionally, barplots are a suitable choice when you want to emphasize the discrete nature of the categories, as the bars clearly demarcate each category's value.

Arguments of Interest:
ci (optional): The ci argument controls the confidence interval around the estimated statistic (mean, median, etc.). You can set it to "sd" for standard deviation, "bootstrapped" for bootstrapped confidence intervals, or None to disable confidence intervals.

estimator (optional): This argument determines how the data within each category is summarized. By default, it uses the mean to compute the bar heights, but you can choose other aggregation functions like median, sum, etc., by specifying the appropriate function. The mean is used my default.

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