Pass color and linestyle as keyword arguments to set a Matplotlib date plot’s line appearance. For new code, use plot() rather than plot_date(): Matplotlib 3.10.9 marks plot_date() deprecated since 3.9 and scheduled for removal in 3.11.
Set a line’s color and style
Use color for the line color and linestyle for its stroke pattern. For example:
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ax.plot(dates, values, color="tab:blue", linestyle="--")This draws a dashed blue line. The same styling keywords were accepted by the older date-specific method:
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| Value | Pattern |
|---|---|
- |
Solid |
-- |
Dashed |
-. |
Dash-dot |
: |
Dotted |
Choose colors and patterns with enough contrast to distinguish series, especially when multiple lines appear together.
Use the current date-plotting API
Matplotlib 3.10.9 documents plot_date() as deprecated since version 3.9 and scheduled for removal in version 3.11. For datetime-like x or y values, pass them directly to plot() with the desired style keywords. See the pyplot plot_date reference and Axes plot_date reference.
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If the values are numeric Matplotlib date numbers, or you need to configure a timezone, set the relevant axis to date mode before plotting:
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ax.plot(date_numbers, values, color="tab:blue", linestyle="--")Use ax.yaxis.axis_date() instead when the date values are on the y-axis. Date-axis handling and line styling are separate: configure the axis as needed, then specify color and linestyle on the plot call.
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Keep date ticks readable
Date locators and formatters control the tick positions and labels, not the line’s color or dash pattern. The plot_date() API may set automatic date defaults, so if you use custom date tickers or formatters with legacy code, apply them after plotting. The 3.10.9 references describe the deprecation and replacement guidance; earlier documentation records the transition in context: Matplotlib 3.9.1 deprecated the method, while Matplotlib 3.7.0 discouraged it for datetime-like values.
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