[Leejohnston]

matplotlib Quick Plotting Guide (Beginner-Friendly)

matplotlib is the main plotting library used in scientific Python. 
It lets you make graphs, charts, and visualisations easily.

This guide gives you the essential commands for science and data analysis.

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1. Importing matplotlib

The standard import:

Code:

import matplotlib.pyplot as plt

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2. Line Graph (Most Common)

Code:

x = [0, 1, 2, 3, 4]
y = [0, 2, 5, 7, 10]

plt.plot(x, y)
plt.xlabel("Time (s)")
plt.ylabel("Speed (m/s)")
plt.title("Speed-Time Graph")
plt.show()

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3. Scatter Plot

Used for data points and experiments.

Code:

plt.scatter(x, y)
plt.xlabel("Mass (kg)")
plt.ylabel("Force (N)")
plt.title("Force vs Mass")
plt.show()

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4. Bar Chart

Code:

labels = ["A", "B", "C"]
values = [5, 7, 3]

plt.bar(labels, values)
plt.title("Sample Bar Chart")
plt.show()

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5. Histogram (Distribution of Data)

Code:

data = [3, 4, 6, 7, 7, 8, 9, 10, 12]

plt.hist(data, bins=5)
plt.xlabel("Value")
plt.ylabel("Frequency")
plt.title("Histogram Example")
plt.show()

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6. Adding Gridlines

Code:

plt.grid(True)

Place it before plt.show().

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7. Changing Line Style & Color

Code:

plt.plot(x, y, linestyle="--", color="red")

Common line styles: 
• "-" solid 
• "--" dashed 
• ":" dotted 

Common colors: 
• "red" 
• "blue" 
• "green" 
• "black" 

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8. Multiple Lines on One Graph

Code:

plt.plot(x, y1, label="Trial 1")
plt.plot(x, y2, label="Trial 2")

plt.legend()
plt.show()

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9. Subplots (Multiple Graphs)

Code:

fig, axs = plt.subplots(2, 1)

axs[0].plot(x, y)
axs[1].scatter(x, y)

plt.show()

2 rows, 1 column of graphs.

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10. Saving a Graph to File

Code:

plt.savefig("graph.png", dpi=300)

Save before plt.show().

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11. Plotting with pandas

If you have a DataFrame:

Code:

df.plot(x="Time", y="Speed")
plt.show()

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12. Common Mistakes

❌ Forgetting plt.show() 
✔ You must show the graph 

❌ Using strings as numbers 
✔ Ensure x and y are numeric 

❌ Mismatched list lengths 
✔ x and y must be same length 

❌ Confusing scatter() with plot() 
✔ plot() = line graph 
✔ scatter() = points only 

❌ Saving graph after show() 
✔ save BEFORE show() 

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Summary

matplotlib lets you easily create:
• line graphs 
• scatter plots 
• bar charts 
• histograms 
• multi-plot layouts 
• saved images 

It is essential for data science, physics, simulations, and research.