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Ultimate Visualization with Python
SectionΒ 5. ChapterΒ 5
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bookJoint Plot

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Note
Definition

Joint plot is a rather unique plot, since it combines multiple plots. It is a chart that shows the relationship between two variables along with their individual distributions.

A joint plot combines three elements:

  • a histogram on top (distribution of the x-variable);
  • a histogram on the right (distribution of the y-variable);
  • a scatter plot in the center (relationship between the two variables).

Here is an example:

Joint plot example

Data for the Joint Plot

seaborn.jointplot() uses three key parameters:

  • data β€” the DataFrame,
  • x β€” variable for the top histogram,
  • y β€” variable for the right histogram.

x and y may be column names or array-like objects.


              
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import seaborn as sns
import matplotlib.pyplot as plt

# Loading the dataset with data about three different iris flowers species
iris_df = sns.load_dataset("iris")

sns.jointplot(data=iris_df, x="sepal_length", y="sepal_width")
plt.show()
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The example is recreated by passing a DataFrame to data and specifying column names for x and y.

Plot in the Middle

The kind parameter controls the central plot type. Default: 'scatter'. Other options include: 'kde', 'hist', 'hex', 'reg', 'resid'.


              
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import seaborn as sns
import matplotlib.pyplot as plt

# Loading the dataset with data about three different iris flowers species
iris_df = sns.load_dataset("iris")

sns.jointplot(data=iris_df, x="sepal_length", y="sepal_width", kind='reg')
plt.show()
copy

Plot Kinds

Besides scatter, you can choose:

  • reg β€” adds a linear regression fit;
  • resid β€” plots regression residuals;
  • hist β€” bivariate histogram;
  • kde β€” two-variable KDE;
  • hex β€” hexbin plot showing density using colored hexagonal bins.
Note
Study More

As usual, you can explore more options and parameters in jointplot() documentation.

Also, it is worth exploring the mentioned topics:
residplot() documentation;
Bivariate histogram example;
Hexbin plot example.

Task

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  1. Use the correct function to create a joint plot.
  2. Use weather_df as the data for the plot (the first argument).
  3. Set the 'Boston' column for the x-axis variable (the second argument).
  4. Set the 'Seattle' column for the y-axis variable (the third argument).
  5. Set the plot in the middle to have a regression line (the rightmost argument).

Solution

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SectionΒ 5. ChapterΒ 5
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