Control Marker Features

Once you understood how to plot a basic scatterplot with seaborn, you might want to customize the appearance of your markers.

You can super easily customize color, transparency, shape and size of markers in your charts.

Libraries

First, we need to load a few libraries:

seaborn: for creating the scatterplot
matplotlib: for displaying the plot
pandas: for data manipulation

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

plt.rcParams["figure.dpi"] = 300

Dataset

Since scatter plot are made for visualizing relationships between two numerical variables, we need a dataset that contains at least two numerical columns.

Here, we will use the iris dataset that we load directly from the gallery:

path = 'https://raw.githubusercontent.com/holtzy/The-Python-Graph-Gallery/master/static/data/iris.csv'
df = pd.read_csv(path)
df.head()

	sepal_length	sepal_width	petal_length	petal_width	species
0	5.1	3.5	1.4	0.2	setosa
1	4.9	3.0	1.4	0.2	setosa
2	4.7	3.2	1.3	0.2	setosa
3	4.6	3.1	1.5	0.2	setosa
4	5.0	3.6	1.4	0.2	setosa

Control Marker Shape

In order to change the shape of the marker, you need to provide:

marker: the shape of the marker

There are actually lots of different shapes available. Here are a few examples:

'o': circle
's': square
'+': plus
'x': cross
'D': diamond
'h': hexagon
'p': pentagon
'v': triangle_down
'^': triangle_up
'<': triangle_left
'>': triangle_right
all numbers from 1 to 4
and many more...

You can find them by running the following code:

from matplotlib import markers
print(markers.MarkerStyle.markers.keys())

fig, ax = plt.subplots(figsize=(8, 6))
sns.regplot(
    x=df["sepal_length"],
    y=df["sepal_width"],
    marker="+",
    fit_reg=False,
    ax=ax
)

plt.show()

Changing Color, Transparency and Size of Markers

You can also change the other features of markers in a plot thanks to scatter_kws.

This argument accepts a dictionary of argument names and their values. These values will be exclusively used to style the dots. For example, scatter_kws={"color" : "red", "alpha" : 1.5} will render the line red and with an opacity of 0.3.

color : color of the markers
alpha : opacity of the markers
s : size of the markers

fig, ax = plt.subplots(figsize=(8, 6))
sns.scatterplot(
    x=df["sepal_length"],
    y=df["sepal_width"],
    color="skyblue",
    alpha=1,
    s=100,
    edgecolor="black",
    lw=3,
    ax=ax
)
plt.show()

Going further

This post explains how to customize the appearance of the markers in a scatter plot with seaborn.

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