How to plot an array in Python using Matplotlib?

To plot an array in Python, we use Matplotlib, a powerful plotting library. This tutorial shows how to create line plots from NumPy arrays with proper formatting and styling.

Basic Array Plotting

Here's how to plot a simple array using Matplotlib ?

import numpy as np
import matplotlib.pyplot as plt

# Create arrays
x = np.array([1, 2, 3, 4, 5])
y = np.array([2, 4, 1, 5, 3])

# Create the plot
plt.figure(figsize=(8, 5))
plt.plot(x, y, color="red", marker='o')
plt.title("Basic Array Plot")
plt.xlabel("X values")
plt.ylabel("Y values")
plt.grid(True, alpha=0.3)
plt.show()

Single Array Plotting

When plotting a single array, Matplotlib uses array indices as x-coordinates ?

import numpy as np
import matplotlib.pyplot as plt

# Single array - indices used as x-coordinates
data = np.array([5, 4, 1, 4, 5])

plt.figure(figsize=(8, 5))
plt.plot(data, color="blue", marker='s', linewidth=2)
plt.title("Single Array Plot")
plt.xlabel("Index")
plt.ylabel("Value")
plt.grid(True, alpha=0.3)
plt.show()

Multiple Plotting Styles

You can customize plots with different line styles, markers, and colors ?

import numpy as np
import matplotlib.pyplot as plt

x = np.array([1, 2, 3, 4, 5])
y1 = np.array([1, 4, 2, 5, 3])
y2 = np.array([2, 1, 4, 3, 5])

plt.figure(figsize=(10, 6))

# Different styles for multiple arrays
plt.plot(x, y1, 'r-o', label='Array 1', linewidth=2)
plt.plot(x, y2, 'g--s', label='Array 2', linewidth=2)

plt.title("Multiple Array Plots")
plt.xlabel("X values")
plt.ylabel("Y values")
plt.legend()
plt.grid(True, alpha=0.3)
plt.show()

Key Plotting Parameters

Advanced Example with Subplots

For comparing multiple arrays side by side ?

import numpy as np
import matplotlib.pyplot as plt

# Create sample data
data1 = np.array([1, 3, 2, 4, 5])
data2 = np.array([2, 1, 4, 3, 5])

fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 5))

# First subplot
ax1.plot(data1, 'ro-', linewidth=2)
ax1.set_title('Array 1')
ax1.set_xlabel('Index')
ax1.set_ylabel('Value')
ax1.grid(True, alpha=0.3)

# Second subplot
ax2.plot(data2, 'bs-', linewidth=2)
ax2.set_title('Array 2')
ax2.set_xlabel('Index')
ax2.set_ylabel('Value')
ax2.grid(True, alpha=0.3)

plt.tight_layout()
plt.show()

Conclusion

Matplotlib makes it easy to plot NumPy arrays using plt.plot(). Use single arrays for index-based plotting or provide both x and y arrays for custom coordinates. Customize with colors, markers, and labels for professional-looking visualizations.