Categorical Plots (barplot, countplot)

Categorical plots help you visualize data grouped by categories, such as days of the week, product types, or survey responses.
In Seaborn, two commonly used functions for categorical data are:

• barplot(): Shows the average value of a numeric variable for each category.
• countplot(): Shows how many times each category appears.

A bar plot is useful when you want to compare average values across categories.
By default, Seaborn's barplot() calculates the mean for each category.

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import seaborn as sns
import matplotlib.pyplot as plt

tips = sns.load_dataset("tips")

sns.barplot(data=tips, x="day", y="total_bill")
plt.title("Average Total Bill by Day")
plt.show()

A count plot is useful when you want to see how many times each category appears in the dataset. Unlike a bar plot, countplot() does not require a numeric y-value because it counts the rows automatically.

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sns.countplot(data=tips, x="day")
plt.title("Count of Records by Day")
plt.show()

• Use barplot() when you want to compare averages or other aggregated values.
• Use countplot() when you want to see frequency counts of each category.