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Call ax.plot() once for each series on the same Matplotlib Axes. Matplotlib assigns colors automatically from its style cycle; use color= when you need specific colors, and add a legend to identify the lines.
Plot multiple lines with automatic colors
This is the simplest pattern when Matplotlib’s current color cycle is suitable:
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.plot(x, y1, label="Series 1")
ax.plot(x, y2, label="Series 2")
ax.legend()
plt.show()Each call adds a line to the same Axes. With no color specified, Matplotlib uses the next style in that Axes’ property cycle. If you plot more lines than the cycle contains, its styles repeat. See the Matplotlib plot API reference.
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Pass a color specification to each call when a particular series should always use a particular color:
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fig, ax = plt.subplots()
ax.plot(x, y1, color="tab:blue", label="Series 1")
ax.plot(x, y2, color="#ff7f0e", label="Series 2")
ax.legend()Matplotlib accepts short color codes such as "r", named colors such as "green", hex strings such as "#008000", Tableau colors such as "tab:blue", and cycle references such as "C0" and "C1". A plot format string can also combine a line or marker style with a color. Consult the plot API reference and color guide for supported specifications.
Use one palette across the lines in an Axes
Set an Axes-local property cycle before plotting to apply a chosen sequence of colors automatically:
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from cycler import cycler
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.set_prop_cycle(color=["#4c78a8", "#f58518", "#54a24b"])
ax.plot(x, y1, label="Series 1")
ax.plot(x, y2, label="Series 2")
ax.plot(x, y3, label="Series 3")
ax.legend()The cycle is scoped to that Axes, making it useful when one chart needs a consistent palette without changing other charts. The styling guide explains property cycles.
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To configure a palette for Axes created later in the session, set axes.prop_cycle:
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import matplotlib as mpl
from cycler import cycler
mpl.rcParams["axes.prop_cycle"] = cycler(
color=["#4c78a8", "#f58518", "#54a24b"]
)Apply this before creating the Axes you want to affect. Changing this rcParam does not update Axes that already exist. The property-cycle guide and customization guide document the behavior. Do not use lines.color to set the usual colors for plot(); the rcParams reference says it has no effect on that function. Use axes.prop_cycle instead: Matplotlib rcParams reference.
Plot several datasets in one call
You can pass multiple [x], y, [fmt] groups to plot(), or pass 2D data so that each column is plotted as a dataset. Repeated calls are often easier to read when each line needs its own label or color. With one 2D argument, the one-dimensional sequence is reused for each dataset; when both x and y are 2D, they must have the same shape. Keyword arguments in a call with several datasets apply to all of them. See the API reference for the supported forms and shape details.
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Make lines easier to distinguish
For overlapping lines or charts with many series, include a legend and consider adding markers or varying line styles as well as colors. Colors alone do not ensure that every reader can distinguish the series; Matplotlib’s styling options let you provide additional visual cues. Assign clear labels in the plotting calls so the legend identifies each line.
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Check the documentation for your installed version
The stable Matplotlib API documentation identified here is for version 3.11.2, and its stable URL may change as releases advance. If your project pins an older Matplotlib version, verify the relevant call and color behavior in the documentation for that installed version.
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