Small multiples (facet grid) in Matplotlib - Step-by-Step Execution

Concept Flow - Small multiples (facet grid)

Load data

↓

Choose variable to facet by

↓

Create grid layout

↓

Plot each subset in its grid cell

↓

Display all plots together

We split data by a variable, create a grid, and plot each subset in its own small plot, showing all plots together.

Execution Sample

Matplotlib

import matplotlib.pyplot as plt
import seaborn as sns

sns.set()
data = sns.load_dataset('tips')
g = sns.FacetGrid(data, col='time')
g.map(plt.hist, 'total_bill')
plt.show()

This code loads a dataset, creates a facet grid by 'time', plots histograms of 'total_bill' for each time, and shows the plots.

Execution Table

Step	Action	Evaluation	Result
1	Load dataset 'tips'	Data loaded with columns including 'time' and 'total_bill'	DataFrame with 244 rows
2	Create FacetGrid with col='time'	Unique 'time' values: ['Lunch', 'Dinner']	Grid with 2 columns for Lunch and Dinner
3	Map histogram of 'total_bill' to each facet	For Lunch: histogram bins calculated For Dinner: histogram bins calculated	Two histograms plotted separately
4	Show plot	All facets displayed side by side	Window with 2 histograms labeled Lunch and Dinner

💡 All subsets plotted; visualization complete

Variable Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	Final
data	None	DataFrame loaded	Same	Same	Same
g	None	None	FacetGrid object with 2 facets	Same	Same

Key Moments - 2 Insights

Why do we see two separate plots instead of one combined plot?

Because the FacetGrid splits data by the 'time' variable into Lunch and Dinner subsets, then plots each subset in its own grid cell as shown in execution_table step 2 and 3.

What does the map function do in the FacetGrid?

It applies the plotting function (here plt.hist) to each subset of data in the grid cells, creating separate histograms as shown in execution_table step 3.

Visual Quiz - 3 Questions

Look at the execution table, how many facets does the grid have after step 2?

A 1

B 2

C 3

D 4

💡 Hint

Check execution_table row for step 2 showing unique 'time' values and grid columns

At which step are the histograms for each subset created?

A Step 1

B Step 2

C Step 3

D Step 4

💡 Hint

Look at execution_table row describing mapping histograms to facets

If we changed col='time' to col='day', what would change in the execution table?

A Number of facets in step 2 would change to unique days

B Histograms would plot 'time' instead of 'total_bill'

C Data would be loaded differently in step 1

D No change at all

💡 Hint

FacetGrid splits data by the column specified in step 2

Concept Snapshot

Small multiples (facet grid) split data by a variable.
Create a grid layout with one plot per subset.
Use FacetGrid in seaborn to manage this.
Map plotting functions to each facet.
Shows multiple small plots side by side for easy comparison.

Full Transcript

Small multiples or facet grids help us see data split by a category. We load data, pick a variable to split by, then create a grid with one plot per category. Each plot shows data only for that category. In the example, we load the 'tips' dataset, split by 'time' (Lunch or Dinner), and plot histograms of total bills for each. The FacetGrid creates two plots side by side. This helps compare distributions easily. The map function applies the histogram to each subset. Finally, we show all plots together. This method is great to compare groups visually.