Title and Labels¶

Titles and axis labels provide context for your plots.

Setting Title¶

```python import matplotlib.pyplot as plt import numpy as np

x = np.linspace(-6, 6, 100) y = np.sin(x)

fig, ax = plt.subplots(figsize=(12, 3)) ax.plot(x, y) ax.set_title("Sine Curve") plt.show() ```

Get the current title:

python print(ax.get_title()) # "Sine Curve"

Title Formatting¶

python ax.set_title("Sine Curve", fontsize=20, fontweight='bold', color='navy')

Position the title:

python ax.set_title('Title', loc='left') # Left-aligned ax.set_title('Title', loc='right') # Right-aligned ax.set_title('Title', pad=20) # Add padding above

Setting Axis Labels¶

```python import matplotlib.pyplot as plt import numpy as np

x = np.linspace(0, 1, 100) y = x + x**2

fig, ax = plt.subplots(figsize=(12, 3)) ax.plot(x, y, color='g') ax.set_title('\(y = x + x^2\)', fontsize=20) ax.set_xlabel('\(x\)', fontsize=20) ax.set_ylabel('\(y\)', fontsize=20) plt.show() ```

Get current labels:

python print(ax.get_xlabel()) print(ax.get_ylabel())

LaTeX Support¶

Matplotlib supports LaTeX math notation using $...$:

```python import matplotlib.pyplot as plt import numpy as np

x = np.linspace(-3, 3, 100) y = np.sin(x)

fig, ax = plt.subplots() ax.plot(x, y) ax.set_title(r'\(y = \sin(x)\)') ax.set_xlabel('\(x\)') ax.set_ylabel('\(y\)') plt.show() ```

Complex equations:

python ax.set_title(r'$y = \frac{1}{\sqrt{2\pi}} e^{-\frac{x^2}{2}}$')

Using set() for Multiple Properties¶

Set multiple properties at once:

```python import matplotlib.pyplot as plt import numpy as np

x = np.linspace(0, 1, 100) y = x + x**2

fig, ax = plt.subplots() ax.plot(x, y, color='g') ax.set( title='\(y = x + x^2\)', xlabel='\(x\)', ylabel='\(y\)', xlim=[0, 1], ylim=(0, 2) ) plt.show() ```

Label Padding and Rotation¶

python ax.set_xlabel('Time (seconds)', labelpad=10) # Add padding ax.set_ylabel('Value', rotation=0, labelpad=15) # Horizontal label

Figure Super Title¶

For multi-subplot figures, use suptitle:

```python import matplotlib.pyplot as plt import numpy as np

fig, (ax0, ax1) = plt.subplots(1, 2, figsize=(12, 3)) fig.suptitle("Figure Title", fontsize=20)

ax0.hist(np.random.normal(size=1000), bins=30) ax0.set_title("Histogram")

ax1.boxplot(np.random.normal(size=1000)) ax1.set_title("Box Plot")

plt.tight_layout() plt.show() ```

Key Takeaways¶

• ax.set_title() sets the axes title
• ax.set_xlabel() and ax.set_ylabel() set axis labels
• Use $...$ for LaTeX math notation
• Use ax.set() to set multiple properties at once
• fig.suptitle() adds a title above all subplots
• Get current values with get_title(), get_xlabel(), get_ylabel()

Exercises¶

Exercise 1. Create a plot of y = cos(x) and add a title, x-label, and y-label with the following customizations: title in bold 16pt font, x-label in italic 12pt with color blue, y-label in 12pt with color red. Use fontdict parameter for styling.

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(0, 2 * np.pi, 200)

fig, ax = plt.subplots(figsize=(8, 5))
ax.plot(x, np.cos(x))

ax.set_title('Cosine Function', fontdict={'fontsize': 16, 'fontweight': 'bold'})
ax.set_xlabel('x (radians)', fontdict={'fontsize': 12, 'fontstyle': 'italic', 'color': 'blue'})
ax.set_ylabel('cos(x)', fontdict={'fontsize': 12, 'color': 'red'})

plt.tight_layout()
plt.show()

Exercise 2. Create a 2x2 subplot grid. Add individual titles to each subplot and a super title for the entire figure using fig.suptitle(). Also add a shared x-label with fig.supxlabel() and shared y-label with fig.supylabel().

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(0, 2 * np.pi, 200)

fig, axes = plt.subplots(2, 2, figsize=(10, 8))

axes[0, 0].plot(x, np.sin(x))
axes[0, 0].set_title('sin(x)')

axes[0, 1].plot(x, np.cos(x))
axes[0, 1].set_title('cos(x)')

axes[1, 0].plot(x, np.sin(2*x))
axes[1, 0].set_title('sin(2x)')

axes[1, 1].plot(x, np.cos(2*x))
axes[1, 1].set_title('cos(2x)')

fig.suptitle('Trigonometric Functions', fontsize=16, fontweight='bold')
fig.supxlabel('x (radians)')
fig.supylabel('y')

plt.tight_layout()
plt.show()

Exercise 3. Create a plot where the title includes LaTeX math: display the formula being plotted as part of the title. Plot \(y = \frac{\sin(x)}{x}\) and title it with the rendered equation. Also add an xlabel with units in parentheses and a ylabel with a LaTeX symbol.

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(-10, 10, 1000)
y = np.sinc(x / np.pi)  # sinc(x/pi) = sin(x)/x

fig, ax = plt.subplots(figsize=(10, 5))
ax.plot(x, y, color='darkblue', linewidth=2)
ax.set_title(r'$y = \frac{\sin(x)}{x}$', fontsize=16)
ax.set_xlabel(r'$x$ (radians)', fontsize=12)
ax.set_ylabel(r'$\mathrm{sinc}(x)$', fontsize=12)
ax.grid(True, alpha=0.3)
plt.tight_layout()
plt.show()

Exercise 4. Demonstrate weak vs strong titles. Plot the same data (y = e^{-x} \sin(5x) for x in [0, 3]) twice: once with a weak title ("Plot of Data") and once with a strong title that communicates the insight ("Exponentially Decaying Oscillation"). Add proper axis labels with units to both. Explain why the strong title is better.

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(0, 3, 200)
y = np.exp(-x) * np.sin(5 * x)

fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 4))

ax1.plot(x, y, 'b-')
ax1.set_title('Plot of Data')  # WEAK: says nothing
ax1.set_xlabel('x')
ax1.set_ylabel('y')

ax2.plot(x, y, 'b-')
ax2.set_title(r'Exponentially Decaying Oscillation ($e^{-x}\sin(5x)$)')
ax2.set_xlabel('Time (seconds)')
ax2.set_ylabel('Amplitude (volts)')

plt.tight_layout()
plt.show()

# The strong title tells the reader what to observe (decay + oscillation)
# The axis labels with units place it in a physical context
# The weak title adds no information beyond "this is a plot"