Strip plot

seaborn.stripplot() displays individual data points for a numerical variable across categories.
It’s a type of scatter plot where:

• The x-axis (or y-axis) shows categories
• The other axis shows numeric values
• Each dot represents one observation

It’s great for:

• Showing raw data instead of summary statistics
• Understanding data distribution, density, and outliers

Syntax:

sns.stripplot(    data=None,    x=None,    y=None,    hue=None,    order=None,    hue_order=None,    jitter=True,    dodge=False,    orient=None,    color=None,    palette=None,    size=5,    alpha=None,    marker='o',    linewidth=0,    **kwargs)

Parameters:

• data = DataFrame containing your data
• x, y = Categorical and numeric variables
• hue = Adds subcategories (colours)
• jitter = Adds random noise to avoid overlapping points (default: True)
• dodge = Separates hue categories side by side
• palette = Colour palette for hue
• size = Dot size
• alpha = Transparency (0 to 1)
• marker = Shape of the points
• linewidth = Outline thickness for points

Basic example

import seaborn as snsimport matplotlib.pyplot as plt​tips = sns.load_dataset("tips")​sns.stripplot(data=tips, x="day", y="total_bill")plt.show()

Each dot = one observation of total_bill for a given day.

Add hue (subgroups)

import seaborn as snsimport matplotlib.pyplot as plt​tips = sns.load_dataset("tips")​sns.stripplot(data=tips, x="day", y="total_bill", hue="sex", palette="Set2")plt.show()

• Dots are coloured by sex.
• Default behaviour: dots from different hue groups overlap slightly.

Separate subgroups (dodge)

import seaborn as snsimport matplotlib.pyplot as plt​tips = sns.load_dataset("tips")​sns.stripplot(data=tips, x="day", y="total_bill", hue="sex", dodge=True, palette="pastel")plt.show()

Dots for different hue groups appear side by side, avoiding overlap.

Control jitter (spread of points)

import seaborn as snsimport matplotlib.pyplot as plt​tips = sns.load_dataset("tips")​sns.stripplot(data=tips, x="day", y="total_bill", jitter=0.2)plt.show()

• jitter=True (default): spreads points horizontally for visibility.
• jitter=0: stacks points directly above each other (no spread).

Horizontal orientation

import seaborn as snsimport matplotlib.pyplot as plt​tips = sns.load_dataset("tips")​sns.stripplot(data=tips, x="total_bill", y="day", orient="h")plt.show()

Flips the orientation — useful for long category names.

Customise style and colors

import seaborn as snsimport matplotlib.pyplot as plt​tips = sns.load_dataset("tips")​sns.stripplot(    data=tips,    x="day",    y="total_bill",    hue="sex",    dodge=True,    palette="coolwarm",    size=6,    alpha=0.7,    linewidth=0.5,    edgecolor="black")plt.show()

• size → dot size
• alpha → transparency
• linewidth + edgecolor → outline styling