Seaborn Scatter Chart

Introduction

Seaborn is a tool used for creating visual charts, specifically designed to work smoothly with Jupyter Notebook. Among its offerings is the Scatter Chart, a commonly used visualization method. We've prepared some examples to illustrate how they appear and function for your reference.

• simple scatter chart
• scatter chart with numpy data
• scatter chart with pandas data
• an interactive scatter chart

If you need any information about Seaborn check their docs: Seaborn Docs (opens in a new tab).

All of code examples are availabe as Jupyter Notebooks in our GitHub repositiory:

• Seaborn Scatter Chart (opens in a new tab)
• Seaborn Interactive Scatter Chart (opens in a new tab)

Scatter Chart

Example with just seaborn:

# import packages 
import seaborn as sns
 
# create data 
x = [3, 9, 9, 7, 2, 10, 9, 6, 6, 10]
 
# plot 
_ = sns.scatterplot(x)

Scatter Chart with Numpy Data

Show numpy data as scatter chart using seaborn:

# import packages 
import seaborn as sns 
import numpy as np 
 
# create data 
x = np.array([3, 9, 7, 4, 3, 1, 10, 7, 10, 6])
 
# plot 
_ = sns.scatterplot(x)

Scatter Chart with Pandas Data

Create a scatter chart using seaborn with pandas data:

# import packages 
import seaborn as sns 
import pandas as pd 
 
# create data 
df = pd.DataFrame({ 'value': [4, 3, 6, 4, 1, 5, 10, 2, 1, 3]})
 
# plot 
_ = sns.scatterplot(df)

Interactive Scatter Chart

Static charts are boring. Let's create an interactive scatter chart using seaborn and mercury packages. You can modify data range conveniently with mercury widgets. In this example we used Slider (opens in a new tab).

# import packages 
import seaborn as sns 
import mercury as mr

# mercury widget
slider = mr.Slider(value=10, min=8, max=20, label="How many dots?")

# create data
all_x = [22, 6, 17, 13, 10, 3, 17, 21, 22, 22, 9, 11, 10, 12, 16, 16, 4, 6, 14, 9]
x = all_x[0:slider.value]
 
# plot 
_ = sns.scatterplot(x)

Now, you can transform your Jupyter Notebook into a Web App effortlessly! Watch this video to see how it look.

Deploying Web App is very easy that you can do it in 3 steps:

Congrats! You just created your own Web App and you can share your Jupyter Notebooks with nontechnical users. If you need more information about deploying the Web App check Mercury Cloud Documentation (opens in a new tab).