Subplots for multiple charts in Data Analysis Python - Step-by-Step Execution

Concept Flow - Subplots for multiple charts

Start

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Create Figure and Axes with subplots()

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Plot chart 1 on Axes 1

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Plot chart 2 on Axes 2

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Adjust layout if needed

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Show or save the figure

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End

This flow shows how to create a figure with multiple charts using subplots, plot each chart on its own axes, adjust layout, and display the result.

Execution Sample

Data Analysis Python

import matplotlib.pyplot as plt

fig, axs = plt.subplots(1, 2)
axs[0].plot([1, 2, 3], [1, 4, 9])
axs[1].bar([1, 2, 3], [3, 2, 5])
plt.show()

This code creates a figure with two side-by-side charts: a line plot and a bar chart.

Execution Table

Step	Action	Object Created/Modified	Result/Output
1	Call plt.subplots(1, 2)	fig, axs	Figure with 1 row, 2 columns of Axes created
2	Plot line on axs[0]	axs[0]	Line plot with points (1,1), (2,4), (3,9) drawn
3	Plot bar on axs[1]	axs[1]	Bar chart with bars at x=1,2,3 and heights 3,2,5 drawn
4	Call plt.show()	Figure window	Displays figure with two charts side by side
5	End	-	Execution stops after showing the figure

💡 Figure displayed and script ends

Variable Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	Final
fig	None	Figure object created	Figure unchanged	Figure unchanged	Figure unchanged
axs	None	Array of 2 Axes objects	axs[0] has line plot	axs[1] has bar chart	Both Axes have their plots

Key Moments - 2 Insights

Why do we use axs[0] and axs[1] to plot instead of just axs?

Because plt.subplots(1, 2) returns an array of Axes objects, each representing a separate chart area. axs[0] is the first chart, axs[1] the second. See execution_table steps 2 and 3.

What happens if we call plt.show() before plotting on axs[1]?

The figure will display only the plots drawn before plt.show(). So axs[1] would be empty. See execution_table step 4 shows all plots after both are drawn.

Visual Quiz - 3 Questions

Look at the execution table, what does axs contain after Step 1?

A A Figure object

B A list of two Axes objects

C A single Axes object

D An empty list

💡 Hint

Check execution_table row 1: plt.subplots(1, 2) returns fig and axs array

At which step is the bar chart drawn on the figure?

A Step 1

B Step 2

C Step 3

D Step 4

💡 Hint

See execution_table row 3: axs[1] bar chart is drawn

If we change plt.subplots(1, 2) to plt.subplots(2, 1), how does axs change?

A axs becomes a 2-element array with vertical layout

B axs becomes a single Axes object

C axs becomes a 4-element array

D axs becomes empty

💡 Hint

plt.subplots(rows, cols) creates rows x cols Axes; changing to (2,1) stacks charts vertically

Concept Snapshot

Use plt.subplots(rows, cols) to create multiple charts in one figure.
It returns a Figure and an array of Axes.
Plot each chart on its Axes (e.g., axs[0], axs[1]).
Call plt.show() to display all charts together.
Adjust layout with plt.tight_layout() if needed.

Full Transcript

This lesson shows how to create multiple charts in one figure using matplotlib's subplots function. First, plt.subplots(1, 2) creates a figure with two side-by-side chart areas, returning a Figure object and an array of two Axes objects. We plot a line chart on the first Axes (axs[0]) and a bar chart on the second (axs[1]). Finally, plt.show() displays the figure with both charts. Variables fig and axs track the figure and axes states. Key points include understanding that axs is an array of Axes, and plotting must be done on each Axes separately before showing the figure.