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How To Facet a Scatter Plot with Altair?

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In this article, we will learn how to Facet a Scatter Plot with Altair. Let’s recall some concepts :

  • Altair is a statistical visualization library in Python. It is declarative in nature and is based on Vega and Vega-Lite visualization grammars. It is fast becoming the first choice of people looking for a quick and efficient way to visualize datasets. If you have used imperative visualization libraries like matplotlib, you will be able to rightly appreciate the capabilities of Altair.
  • A scatter plot (also called a scatterplot, scatter graph, scatter chart, scattergram, or scatter diagram) is a type of plot or mathematical diagram using Cartesian coordinates to display values for typically two variables for a set of data.

Here, we are making the scatter plot using Altair library. For this, we use Chart() function in Altair to load the data and then use the mark_point() function to make a scatter plot. We then use the aesthetics x and y-axis to encode() function. After making this scatter plot we will facet it with a grouped column values such as clusters.

Steps Needed

  1. Import Libraries (Altair).
  2. Create/Load data.
  3. Use Chart() to load data for plot.
  4. Use mark_point() to scatter plot.
  5. Use encode() for x and y axes.
  6. (Optional)Use properties() for setting width and height.
  7. Use facet() over scatter plot with clusters.

Examples 

Let’s understand the above-mentioned steps with the help of some examples :

Example 1: 

In this example, we draw a simple facet Scatter plot with some dummy data. That is shown below:

Below is the implementation:

Python3




# import libraries
import altair as alt
import pandas as pd
import numpy as np
np.random.seed(1)
  
# create data
df = pd.DataFrame({'X':np.random.randint(1, 10, 50),
                   'Y':np.random.randint(1, 10, 50),
                   'Cluster':np.random.randint(1, 5, 50)})
  
# Draw Facet Scatter Plot
alt.Chart(df).mark_point().encode(
    x=alt.X('X'),
    y=alt.Y('Y')
).properties(width = 200, height = 200).facet(
    'Cluster:N',
    columns = 2
)

Output:

 

Example 2 : (Iris Data From Vega Dataset)

Python3




# import libraries
import altair as alt
from vega_datasets import data
  
# load data
iris = data.iris()
  
# Draw Facet Scatter Plot
alt.Chart(iris).mark_point().encode(
    x = alt.X('sepalLength'),
    y = alt.Y('sepalWidth'),
    color = 'species'
).properties(width = 250, height = 250).facet(
    'species:N',
    columns = 3
)

Output:

 

Example 3 : (Cars Data From Vega Dataset)

Python3




# import libraries
import altair as alt
from vega_datasets import data
  
# load data
cars = data.cars()
  
# Draw Facet Scatter Plot
alt.Chart(cars).mark_point().encode(
    x = alt.X('Displacement'),
    y = alt.Y('Acceleration'),
    size = alt.value(100),
    color = 'Cylinders'
).properties(width = 250, height = 250).facet(
    'Origin:N',
    columns = 3
)

Output:


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Last Updated : 03 Jan, 2021
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