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Outbyte Driver Updater FREEFix the driver behind crashes, sound loss and screen glitchesFind Drivers →Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →Use fill_between(x, y1, y2) to shade between horizontal curves, and fill_betweenx(y, x1, x2) to shade between vertical curves. The key is which coordinate varies: x for fill_between, y for fill_betweenx.
Choose the function by the direction of the lines
Matplotlib’s fill_between fills the area between two horizontal curves; fill_betweenx fills between two vertical curves. In each case, one coordinate supplies the sequence of nodes and the other coordinate supplies the boundaries.
| Goal | Node sequence | Boundaries | Call |
|---|---|---|---|
| Fill between horizontal curves | x values | Two y values or curves | ax.fill_between(x, y1, y2) |
| Fill between vertical curves | y values | Two x values or curves | ax.fill_betweenx(y, x1, x2) |
The same operations are available through pyplot and an Axes object. The examples below use an Axes object, typically obtained with fig, ax = plt.subplots().
Fill between horizontal lines or curves
Pass x coordinates first, then the two y boundaries. Either boundary can be a scalar, which represents a constant horizontal line:
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ax.fill_between(x, y1, y2) # between two y curves
ax.fill_between(x, y, 0) # between y(x) and the horizontal line y=0For example, the following shades between a curve and the x-axis:
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(0, 2 * np.pi, 200)
y = np.sin(x)
fig, ax = plt.subplots()
ax.plot(x, y)
ax.fill_between(x, y, 0, facecolor="tab:blue", alpha=0.3)
plt.show()In the pyplot API, the call returns a FillBetweenPolyCollection. Styling can be set with collection keyword arguments such as facecolor, alpha, and linewidth. See the Matplotlib pyplot.fill_between API.
Fill between vertical lines or curves
Pass y coordinates first, followed by the two x boundaries. A scalar boundary represents a constant vertical line:
ax.fill_betweenx(y, x1, x2) # between two x curves
ax.fill_betweenx(y, x, 0) # between x(y) and the vertical line x=0To shade between two vertical boundaries, use fill_betweenx rather than swapping arguments to fill_between. The official example demonstrates shading between x=0 and a curve, then between that curve and x=1:
ax.fill_betweenx(y, 0, x1)
ax.fill_betweenx(y, x1, 1)See the Matplotlib 3.11.2 Axes.fill_betweenx API and its vertical-fill example.
Limit the fill with a condition
Use where with a boolean mask aligned to the node sequence. For horizontal fills, the mask aligns with x; for vertical fills, it aligns with y. An interval is filled only when the mask is true at both of its neighboring nodes.
# Fill only where y1 is above y2
ax.fill_between(x, y1, y2, where=(y1 > y2))
# For vertical curves, the condition is evaluated along y
ax.fill_betweenx(y, x1, x2, where=(x1 > x2))This neighboring-node rule matters: one isolated True surrounded by False values does not mark either adjacent interval for filling. If a mask changes at a point where the two curves cross, set interpolate=True so Matplotlib calculates the intersection and extends the fill to it instead of stopping at the sampled node:
ax.fill_between(x, y1, y2, where=(y1 > y2), interpolate=True)The same option applies to fill_betweenx. The behavior of where and interpolation is documented in the fill-between API reference.
Use step alignment for stepped data
For step-like curves, the step argument controls where each value extends relative to its coordinate. The same alignments apply to fill_betweenx, read along y instead of x.
step='pre': a value extends to the left of its x coordinate (or toward lower y for a vertical fill).step='post': a value extends to the right of its x coordinate (or toward higher y for a vertical fill).step='mid': the transition is placed halfway between neighboring coordinates.
Diagnose unexpected gaps and triangles
Check the mask and sample spacing as separate issues. A gap can follow directly from the rule that both nodes bounding an interval must pass the mask. At crossings, consider whether interpolate=True is needed. Separately, Matplotlib’s vertical-fill gallery example notes that coarse data gridding can leave unfilled triangles around crossover points; interpolating onto a finer grid is described there as a brute-force remedy. That note concerns sampling resolution and does not mean every visible gap has the same cause.
If a version-specific behavior is unexpected, compare it with the documentation for the installed Matplotlib release. The API details here reflect Matplotlib 3.11.2 documentation as of October 4, 2026.
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