Bar Plots in Seaborn

What is barplot in Seaborn?

Seaborn’s barplot typically plots:

• An aggregate (default is mean)
• An uncertainty interval (confidence interval)

This is different from Matplotlib bars where you usually plot raw totals.

diagram How barplot builds one bar mermaid

  flowchart LR
  A["All rows for
one category"] --> B["Aggregate
(mean by default)"]
  B --> C["Draw one bar"]
  A --> D["Estimate uncertainty"]
  D --> E["Draw error bar
(95% confidence interval)"]

Every row in a category gets averaged into one bar height, plus a confidence interval line on top.

From the book

McKinney runs sns.barplot(x=\"tip_pct\", y=\"day\", data=tips, orient=\"h\") and points out: “Because there are multiple observations for each value in the day, the bars are the average value of tip_pct. The black lines drawn on the bars represent the 95% confidence interval.” Add hue= to split each bar further by another category, like time.

Example: mean total bill by day

Seaborn barplot

import seaborn as sns
import matplotlib.pyplot as plt
 
tips = sns.load_dataset("tips")
 
plt.figure(figsize=(7, 4))
sns.barplot(data=tips, x="day", y="total_bill")
plt.title("Mean total bill by day")
plt.tight_layout()
plt.show()

Add hue

barplot with hue

import seaborn as sns
import matplotlib.pyplot as plt
 
tips = sns.load_dataset("tips")
 
plt.figure(figsize=(7, 4))
sns.barplot(data=tips, x="day", y="total_bill", hue="sex")
plt.title("Mean total bill by day and sex")
plt.tight_layout()
plt.show()

Change estimator (sum, median, etc.)

Custom estimator

import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np
 
tips = sns.load_dataset("tips")
 
plt.figure(figsize=(7, 4))
sns.barplot(data=tips, x="day", y="total_bill", estimator=np.median)
plt.title("Median total bill by day")
plt.tight_layout()
plt.show()

Visualize it

The whisker on top of each bar is the confidence interval — it tells you how much the average might wobble if you resampled the data:

sketch Bars with confidence-interval error bars p5.js Pause Restart

Bar height is the group mean; the whisker on top shows the uncertainty around that mean.

Tips

• Use barplot for comparing group summaries.
• Use countplot when you want raw counts.
• If you already aggregated your data with Pandas, consider Matplotlib bars.

Next

Continue to Count Plots for a simpler case: bars that just count rows per category, no aggregation needed.

🧪 Try It Yourself

Exercise 1 – Mean by Category

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Exercise 2 – Split Each Bar by Time

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Exercise 3 – Change the Estimator

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