Grid and Axis¶

Configure grid lines and axis behavior for clearer visualizations.

Basic Grid¶

Enable grid lines:

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.grid()
plt.show()

Disable grid:

ax.grid(visible=False)

Grid Styling¶

Customize grid appearance:

ax.grid(True, linestyle='--', alpha=0.7)

Full customization:

ax.grid(
    visible=True,
    which='major',      # 'major', 'minor', or 'both'
    axis='both',        # 'x', 'y', or 'both'
    color='gray',
    linestyle='-',
    linewidth=0.5,
    alpha=0.7
)

Major and Minor Grids¶

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)

# Enable minor ticks
ax.minorticks_on()

# Style grids separately
ax.grid(which='major', color='gray', linestyle='-')
ax.grid(which='minor', color='lightgray', linestyle=':')

plt.show()

Axis Scaling¶

Set axis scale type:

import matplotlib.pyplot as plt
import numpy as np

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

fig, ax = plt.subplots()
ax.plot(x, y)
ax.set_xscale('log')
ax.set_yscale('linear')  # Options: 'linear', 'log', 'symlog', 'logit'
plt.show()

Or use plt.axes() with scale:

fig = plt.figure()
ax = plt.axes(yscale='log')
ax.plot(x, y)

axis() Method¶

Control multiple axis properties:

Tight bounds:

import matplotlib.pyplot as plt
import numpy as np

i = complex(0, 1)
theta = np.linspace(0, 2*np.pi, 100)
z = np.exp(i * theta)
x = np.real(z)
y = np.imag(z)

fig, ax = plt.subplots(figsize=(3, 3))
ax.plot(x, y)
ax.axis('tight')  # Tight bounds around data
plt.show()

Equal aspect ratio:

fig, ax = plt.subplots(figsize=(3, 3))
ax.plot(x, y)
ax.axis('equal')  # Equal scaling for x and y
plt.show()

Turn off axis:

fig, ax = plt.subplots(figsize=(3, 3))
ax.plot(x, y)
ax.axis('equal')
ax.axis('off')  # Hide all axis elements
plt.show()

axis() Options Summary¶

Option	Description
`'on'`	Turn axis lines and labels on
`'off'`	Turn axis lines and labels off
`'equal'`	Equal scaling on both axes
`'scaled'`	Equal scaling, adjust limits
`'tight'`	Tight limits around data
`'auto'`	Automatic limits
`'square'`	Square aspect ratio
`'image'`	Equal with tight limits

You can also set limits directly:

ax.axis([xmin, xmax, ymin, ymax])

Aspect Ratio¶

Control the aspect ratio directly:

ax.set_aspect('equal')    # Equal scaling
ax.set_aspect(2.0)        # y-axis is 2x scale of x-axis
ax.set_aspect('auto')     # Automatic (default)

Box Aspect¶

Set the physical box aspect ratio:

ax.set_box_aspect(1)      # Square box
ax.set_box_aspect(0.5)    # Wide box

Complete Example¶

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(-2*np.pi, 2*np.pi, 100)
y = np.sin(x)

fig, ax = plt.subplots(figsize=(12, 4))
ax.plot(x, y)

# Grid
ax.minorticks_on()
ax.grid(which='major', color='#666666', linestyle='-', linewidth=0.8)
ax.grid(which='minor', color='#999999', linestyle=':', linewidth=0.5, alpha=0.5)

# Set limits
ax.set_xlim(-2.5*np.pi, 2.5*np.pi)
ax.set_ylim(-1.5, 1.5)

# Labels
ax.set_xlabel('x')
ax.set_ylabel('sin(x)')
ax.set_title('Sine Wave with Grid')

plt.show()

Key Takeaways¶

ax.grid() enables/disables grid lines
Use which='major' or which='minor' for different grid levels
ax.minorticks_on() enables minor ticks
ax.set_xscale() and ax.set_yscale() set axis scaling
ax.axis() provides quick access to common configurations
ax.set_aspect() controls the aspect ratio