Seaborn

Install packages

You can use both pip or astral/uv.

!uv pip install -q \
    pandas==2.3.2 \
    pandas-stubs==2.3.2.250827 \
    numpy==2.3.2 \
    matplotlib==3.10.6 \
    seaborn==0.13.2

Import packages

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns

sns.set_style("darkgrid")
sns.set_theme(style="darkgrid")

Usage

Plots

Load tips dataset.

tips = sns.load_dataset("tips")

tips.head()

	total_bill	tip	sex	smoker	day	time	size
0	16.99	1.01	Female	No	Sun	Dinner	2
1	10.34	1.66	Male	No	Sun	Dinner	3
2	21.01	3.50	Male	No	Sun	Dinner	3
3	23.68	3.31	Male	No	Sun	Dinner	2
4	24.59	3.61	Female	No	Sun	Dinner	4

Scatter Plot

sns.scatterplot(x="total_bill", y="tip", data=tips, color="#F79E6B")

plt.title("Total bill x tips")
plt.show()

Line Plot

sns.lineplot(x="size", y="total_bill", data=tips, color="#92A78C")

plt.title("Total bill by size")
plt.show()

Bar Plot

sns.barplot(
    x="day",
    y="total_bill",
    data=tips,
    color="#F7CD82",
    estimator=np.mean,
)

plt.title("Average bill per day")
plt.show()

Box Plot

sns.boxplot(x="day", y="total_bill", data=tips, color="#E0D5AD")

plt.title("Total bill per day")
plt.show()

Violin Plot

sns.violinplot(x="day", y="total_bill", data=tips, color="#F7CD82")

plt.title("Total bill per day")
plt.show()

Histogram Plot

sns.histplot(tips["total_bill"].tolist(), bins=10, kde=True)

plt.show()

KDE Plot

sns.kdeplot(tips["total_bill"].tolist(), fill=True)
plt.show()

Pair Plot

sns.pairplot(tips)
plt.show()

Heat Map

correlation = tips[["total_bill", "tip", "size"]].corr()
correlation

	total_bill	tip	size
total_bill	1.000000	0.675734	0.598315
tip	0.675734	1.000000	0.489299
size	0.598315	0.489299	1.000000

sns.heatmap(correlation, annot=True, cmap="coolwarm")
plt.show()

Customization

plt.figure(figsize=(10, 5))


sns.barplot(
    x="day",
    y="total_bill",
    data=tips,
    color="#F7CD82",
    estimator=sum,
)

plt.ylabel("Total bill")
plt.xlabel("Day")
plt.title("Total bills per day")
plt.show()