Seaborn Bar Chart

Introduction

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

• simple bar chart
• bar chart with numpy data
• bar chart with pandas data
• an interactive bar 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 Bar Chart (opens in a new tab)
• Seaborn Interactive Bar Chart (opens in a new tab)

Bar Chart

Example with just seaborn:

# import packages 
import seaborn as sns
 
# create data 
y = [1.5,3.8,5.7,7.1,2.9]
 
# plot 
_ = sns.barplot(y)

Bar Chart with Numpy Data

Show numpy data as bar chart using seaborn:

# import packages 
import seaborn as sns
import numpy as np
 
# create data 
y = np.array([3.6,5.4,2.1,6.9,1.9])
 
# plot 
_ = sns.barplot(y)

Bar Chart with Pandas Data

Create a bar chart using seaborn with pandas data:

# import packages 
import seaborn as sns
import pandas as pd 
 
# create data 
df = pd.DataFrame({'count': [1,2,3,4,5], 'value': [3.4,5.1,6.7,4.3,8.1]})
 
# plot 
_ = sns.barplot(df, x='count',y='value')

Interactive Bar Chart

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

# import packages 
import seaborn as sns 
import mercury as mr 

# mercury widget
number = mr.Numeric(value=5, min=4, max=10, label="How many bars?", step=1)

# create data 
all_y = [7, 10, 1, 3, 8, 5, 7, 9, 3, 2]
y = all_y[0:int(number.value)]
 
# plot 
_ = sns.barplot(y)

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

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).