3D bar charts in Matplotlib - Step-by-Step Execution

Concept Flow - 3D bar charts

Prepare data arrays: x, y, z, dx, dy, dz

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Create 3D plot figure and axes

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Call bar3d() with data to draw bars

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Render 3D bars on plot

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Show or save the plot

The flow starts by preparing data arrays for bar positions and sizes, then creates a 3D plot, draws bars with bar3d(), and finally displays the chart.

Execution Sample

Matplotlib

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

x = [1, 2, 3]
y = [1, 2, 3]
z = [0, 0, 0]
dx = [0.5, 0.5, 0.5]
dy = [0.5, 0.5, 0.5]
dz = [0.5, 0.5, 0.5]

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

ax.bar3d(x, y, z, dx, dy, dz)
plt.show()

This code sets up a 3D plot and draws 3D bars at specified positions with given sizes.

Execution Table

Step	Action	Variables Used	Result
1	Prepare data arrays	x=[1,2,3], y=[1,2,3], z=[0,0,0], dx=dy=dz=[0.5,0.5,0.5]	Data arrays ready for bars
2	Create figure and 3D axes	fig, ax	3D plot area created
3	Call ax.bar3d()	x, y, z, dx, dy, dz	3D bars drawn at positions with sizes
4	Render plot	fig, ax	3D bar chart displayed
5	Exit	-	Plot window shown, execution ends

💡 Plot displayed and program ends after showing the 3D bar chart

Variable Tracker

Variable	Start	After Step 1	After Step 3	Final
x	undefined	[1, 2, 3]	[1, 2, 3]	[1, 2, 3]
y	undefined	[1, 2, 3]	[1, 2, 3]	[1, 2, 3]
z	undefined	[0, 0, 0]	[0, 0, 0]	[0, 0, 0]
dx	undefined	[0.5, 0.5, 0.5]	[0.5, 0.5, 0.5]	[0.5, 0.5, 0.5]
dy	undefined	[0.5, 0.5, 0.5]	[0.5, 0.5, 0.5]	[0.5, 0.5, 0.5]
dz	undefined	[0.5, 0.5, 0.5]	[0.5, 0.5, 0.5]	[0.5, 0.5, 0.5]

Key Moments - 3 Insights

Why do we need separate arrays for x, y, z and also for dx, dy, dz?

x, y, z define the starting position of each bar in 3D space, while dx, dy, dz define the size (width, depth, height) of each bar. This is shown in execution_table rows 1 and 3 where data arrays are prepared and used.

What does the 'projection="3d"' argument do when creating the axes?

It tells matplotlib to create a 3D plotting area instead of a flat 2D plot. This is essential for drawing 3D bars, as seen in execution_table row 2.

Why do we call plt.show() at the end?

plt.show() opens the window to display the plot. Without it, the plot won't appear. This is the final step in execution_table row 4.

Visual Quiz - 3 Questions

Look at the execution table, what variable holds the height of each 3D bar?

A z

B dz

C y

D dx

💡 Hint

Check the variable_tracker and execution_table rows 1 and 3 where dz is used for bar heights.

At which step are the 3D bars actually drawn on the plot?

A Step 3

B Step 1

C Step 2

D Step 4

💡 Hint

See execution_table row 3 where ax.bar3d() is called to draw bars.

If we change dx, dy, dz to larger values, what will happen to the bars?

A Bars will disappear

B Bars will move to new positions

C Bars will be taller and wider

D Bars will change color

💡 Hint

dx, dy, dz control bar sizes as shown in variable_tracker and execution_table.

Concept Snapshot

3D bar charts in matplotlib:
- Use ax.bar3d(x, y, z, dx, dy, dz)
- x,y,z = bar start positions
- dx,dy,dz = bar sizes (width, depth, height)
- Create 3D axes with projection='3d'
- Call plt.show() to display

Full Transcript

To create 3D bar charts in matplotlib, first prepare arrays for the positions (x, y, z) and sizes (dx, dy, dz) of each bar. Then create a figure and add 3D axes using projection='3d'. Use the ax.bar3d() function with these arrays to draw the bars. Finally, call plt.show() to display the chart. The variables x, y, z set where each bar starts, and dx, dy, dz set how big each bar is in width, depth, and height. This process is step-by-step shown in the execution table and variable tracker.