What Are Markers in Matplotlib?

Markers in Matplotlib are symbols used to highlight individual data points on a graph.
They make charts easier to read by clearly showing where each data value lies on the plot.

Markers are mainly used in line plots and scatter plots.

Basic Marker Example

Python 
import matplotlib.pyplot as plt x = [1, 2, 3, 4] y = [10, 15, 20, 25] plt.plot(x, y, marker="o") plt.show() # Output: # Line chart with circular markers on each point

Here, "o" represents a circle marker.

Common Marker Styles

MarkerSymbolDescription
"o"●Circle
"s"■Square
"^"▲Triangle Up
"v"▼Triangle Down
"*"★Star
"+"+Plus
"x"×Cross
"D"◆Diamond

Changing Marker Size

Python 
import matplotlib.pyplot as plt x = [1, 2, 3, 4] y = [10, 15, 20, 25] plt.plot(x, y, marker="o", markersize=10) plt.show() # Output: # Plot with larger circle markers

markersize controls how big the marker appears.

Changing Marker Color

Python 
import matplotlib.pyplot as plt x = [1, 2, 3, 4] y = [10, 15, 20, 25] plt.plot(x, y, marker="o", markerfacecolor="red", markeredgecolor="black") plt.show() # Output: # Red markers with black borders

  • markerfacecolor → inner color

  • markeredgecolor → border color

Using Markers Without Lines

Python 
import matplotlib.pyplot as plt x = [1, 2, 3, 4] y = [10, 15, 20, 25] plt.plot(x, y, linestyle="", marker="s") plt.show() # Output: # Only square markers displayed without connecting lines

This is useful when you want a scatter-style look.

Markers in Scatter Plot

Python 
import matplotlib.pyplot as plt x = [1, 2, 3, 4] y = [10, 15, 20, 25] plt.scatter(x, y, marker="^") plt.show() # Output: # Scatter plot with triangle markers

Scatter plots often use markers to represent each data point.

Combining Marker with Line Style

Python 
import matplotlib.pyplot as plt x = [1, 2, 3, 4] y = [10, 15, 20, 25] plt.plot(x, y, marker="*", linestyle="--", color="blue") plt.show() # Output: # Dashed blue line with star markers

Key Points to Remember

  • Markers improve data visibility.

  • Use marker parameter inside plot() or scatter().

  • Customize size using markersize.

  • Change colors using markerfacecolor and markeredgecolor.

  • Combine with line styles for better visualization.