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Statistical Visualization with Seaborn

bookPlotting Pairwise Relationships

The PairGrid is a subplot grid for plotting pairwise relationships in a dataset.

It creates a matrix of axes where each variable in the dataset is shared across a row and a column.

  • Diagonal: shows the univariate distribution of a single variable (since x=y);
  • Off-Diagonal: shows the bivariate relationship between two different variables.

Controlling the Grid

Unlike pairplot (which is fully automatic), PairGrid requires you to map plots to specific sections explicitly.

  • g.map_diag(func): plots on the diagonal (e.g., sns.histplot);
  • g.map_offdiag(func): plots on all non-diagonal cells (e.g., sns.scatterplot);
  • g.map_upper(func) / g.map_lower(func): plots specifically in the upper or lower triangle of the grid.

Example

Here we create a grid where the diagonal shows histograms and the lower triangle shows density contours.


              
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import seaborn as sns
import matplotlib.pyplot as plt

# Load dataset
df = sns.load_dataset('penguins')

# 1. Initialize the grid
g = sns.PairGrid(df, hue='species')

# 2. Map plots to specific regions
g.map_diag(sns.histplot)        # Diagonal: Histograms
g.map_offdiag(sns.scatterplot)  # Off-diagonal: Scatterplots

g.add_legend()
plt.show()
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Task

Swipe to start coding

Create a customized grid to analyze the relationships between penguin measurements.

  1. Set the style to 'ticks'. Change the figure background color to 'lightpink' ('figure.facecolor').
  2. Initialize the PairGrid (g):
    • Use the df dataset.
    • Color the data points by 'species' (hue).
    • Use the 'rocket_r' palette.
    • Set diag_sharey=False (this allows diagonal plots to have their own Y-axis scale).
  3. Diagonal plots: map sns.histplot to the diagonal using .map_diag(). Add a KDE curve (kde=True).
  4. Off-diagonal plots: map sns.scatterplot to the rest of the grid using .map_offdiag(). Set the point border width (linewidth) to 0.9 and the border color (edgecolor) to 'purple'.
  5. Add the legend and display the plot.

Solution

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SectionΒ 1. ChapterΒ 19
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bookPlotting Pairwise Relationships

Swipe to show menu

The PairGrid is a subplot grid for plotting pairwise relationships in a dataset.

It creates a matrix of axes where each variable in the dataset is shared across a row and a column.

  • Diagonal: shows the univariate distribution of a single variable (since x=y);
  • Off-Diagonal: shows the bivariate relationship between two different variables.

Controlling the Grid

Unlike pairplot (which is fully automatic), PairGrid requires you to map plots to specific sections explicitly.

  • g.map_diag(func): plots on the diagonal (e.g., sns.histplot);
  • g.map_offdiag(func): plots on all non-diagonal cells (e.g., sns.scatterplot);
  • g.map_upper(func) / g.map_lower(func): plots specifically in the upper or lower triangle of the grid.

Example

Here we create a grid where the diagonal shows histograms and the lower triangle shows density contours.


              
123456789101112131415

            
import seaborn as sns
import matplotlib.pyplot as plt

# Load dataset
df = sns.load_dataset('penguins')

# 1. Initialize the grid
g = sns.PairGrid(df, hue='species')

# 2. Map plots to specific regions
g.map_diag(sns.histplot)        # Diagonal: Histograms
g.map_offdiag(sns.scatterplot)  # Off-diagonal: Scatterplots

g.add_legend()
plt.show()
copy
Task

Swipe to start coding

Create a customized grid to analyze the relationships between penguin measurements.

  1. Set the style to 'ticks'. Change the figure background color to 'lightpink' ('figure.facecolor').
  2. Initialize the PairGrid (g):
    • Use the df dataset.
    • Color the data points by 'species' (hue).
    • Use the 'rocket_r' palette.
    • Set diag_sharey=False (this allows diagonal plots to have their own Y-axis scale).
  3. Diagonal plots: map sns.histplot to the diagonal using .map_diag(). Add a KDE curve (kde=True).
  4. Off-diagonal plots: map sns.scatterplot to the rest of the grid using .map_offdiag(). Set the point border width (linewidth) to 0.9 and the border color (edgecolor) to 'purple'.
  5. Add the legend and display the plot.

Solution

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Everything was clear?

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Thanks for your feedback!

SectionΒ 1. ChapterΒ 19
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