Vega-Altair Histogram Chart

Introduction

Vega-Altair package is a powerful tool for data visualization, particularly within Jupyter Notebooks. It has a wide range of charts and plots to explore and one of them is Histogram Chart. We've prepared several examples to demonstrate how Vega-Altair works:

• simple histogram chart
• histogram chart with pandas data
• an interactive histogram chart

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

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

• Vega-Altair Histogram Chart (opens in a new tab)
• Vega-Altair Interactive Histogram Chart (opens in a new tab)

Histogram Chart

Visualization with only vega-altair package:

# import packages 
import altair as alt 
from vega_datasets import data
 
# creating data
cars = data.cars()
 
# plot 
alt.Chart(cars).mark_bar().encode(
    alt.X('Horsepower:Q', bin=True),
    y='count()'
).properties(
    width=500
)

Histogram Chart with Pandas Data

Using vega-altair, create a histogram chart with pandas data:

# import packages 
import altair as alt 
import pandas as pd
 
# create data 
df = pd.DataFrame({
    'number': [2,4,6,8,10,12,14,16,18,20,22,24,26,28,30,32,34,36,38,40],
    'count': [4, 8, 11, 13, 16, 17, 18, 19, 21, 22, 24, 25, 26, 28, 30, 33, 34, 36, 37, 38]
})
 
# plot 
alt.Chart(df).mark_bar().encode(
    alt.X('number', bin=True),
    y = 'count'
).properties(
    width = 500
)

Interactive Histogram Chart

Regular charts are not very exciting. What about creating an interactive histogram chart with vega-altair and mercury packages? You can set chart color using mercury widgets. In this example we used Select (opens in a new tab).

# import packages 
import altair as alt 
from vega_datasets import data 
import mercury as mr 

# mercury widget 
select = mr.Select(value='blue', choices=['blue','red','green'], label="Choose chart color:")

# create data 
cars = data.cars()
 
# plot 
alt.Chart(cars).mark_bar(color=select.value).encode(
    alt.X('Horsepower:Q', bin=True),
    y='count()'
).properties(
    width=500
)

Now, you can easily convert your Jupyter Notebook into a Web App! Watch the video to see what it will look like.

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).