How can I plot a single point in Matplotlib Python?

To plot a single data point in matplotlib, you can use the plot() method with specific marker parameters. This is useful for highlighting specific coordinates or creating scatter-like visualizations with individual points.

Basic Single Point Plot

Here's how to plot a single point with customized appearance ?

import matplotlib.pyplot as plt

# Define single point coordinates
x = [4]
y = [3]

# Set axis limits and add grid
plt.xlim(0, 5)
plt.ylim(0, 5)
plt.grid(True)

# Plot the single point
plt.plot(x, y, marker="o", markersize=15, 
         markeredgecolor="red", markerfacecolor="green")

plt.title("Single Point Plot")
plt.xlabel("X-axis")
plt.ylabel("Y-axis")
plt.show()

Using scatter() Method

Alternatively, you can use scatter() which is designed specifically for plotting individual points ?

import matplotlib.pyplot as plt

# Single point coordinates
x = 4
y = 3

# Create scatter plot
plt.scatter(x, y, s=200, c='blue', marker='*', edgecolors='black', linewidth=2)

plt.xlim(0, 5)
plt.ylim(0, 5)
plt.grid(True)
plt.title("Single Point using scatter()")
plt.xlabel("X-axis")
plt.ylabel("Y-axis")
plt.show()

Multiple Styling Options

You can customize the point appearance with various markers and colors ?

import matplotlib.pyplot as plt

# Create subplots for different styles
fig, axes = plt.subplots(1, 3, figsize=(12, 4))

# Style 1: Circle marker
axes[0].plot(2, 2, marker='o', markersize=20, color='red')
axes[0].set_title("Circle Marker")
axes[0].grid(True)
axes[0].set_xlim(0, 4)
axes[0].set_ylim(0, 4)

# Style 2: Square marker
axes[1].plot(2, 2, marker='s', markersize=20, color='blue')
axes[1].set_title("Square Marker")
axes[1].grid(True)
axes[1].set_xlim(0, 4)
axes[1].set_ylim(0, 4)

# Style 3: Star marker
axes[2].plot(2, 2, marker='*', markersize=25, color='green')
axes[2].set_title("Star Marker")
axes[2].grid(True)
axes[2].set_xlim(0, 4)
axes[2].set_ylim(0, 4)

plt.tight_layout()
plt.show()

Key Parameters

Conclusion

Use plot() with marker parameters for single points within line plots, or scatter() for dedicated point visualization. Both methods allow extensive customization of point appearance and styling.