When is plt.Show() required to show a plot and when is it not?

When working with Matplotlib plots, understanding when to use plt.show() is crucial. The requirement depends on your environment ? whether you're in an interactive Python session, a Jupyter notebook, or running a script.

Interactive vs Non-Interactive Environments

In interactive environments like Jupyter notebooks or IPython, plots often display automatically without calling plt.show(). In non-interactive environments like regular Python scripts, you must call plt.show() to display the plot.

Basic Example Without plt.show()

In Jupyter notebooks, this code displays the plot automatically:

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(-5, 5, 100)
y = np.sin(x)

plt.plot(x, y)
plt.title("Sine Wave")

[Displays plot automatically in Jupyter]

Using plt.show() Explicitly

For Python scripts or when you want explicit control, use plt.show():

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(-5, 5, 100)
y = np.cos(x)

plt.figure(figsize=(8, 4))
plt.plot(x, y, 'b-', linewidth=2)
plt.title("Cosine Wave")
plt.grid(True)
plt.show()

[Displays plot in a popup window]

Using fig.show() vs plt.show()

The fig.show() method is used with figure objects, while plt.show() works with the current figure:

import matplotlib.pyplot as plt
import numpy as np

# Create figure object
fig, ax = plt.subplots(figsize=(7, 4))

x = np.linspace(0, 10, 50)
ax.plot(x, x**2, 'r-', label='x²')
ax.set_title("Quadratic Function")
ax.legend()

# Using fig.show() - non-blocking
fig.show()

# Using plt.show() - blocks execution until window closed
plt.show()

[Displays plot with both methods]

When Each Method is Required

Conclusion

Use plt.show() in Python scripts to display plots. In interactive environments like Jupyter, it's optional but provides explicit control. Use fig.show() for non-blocking display when working with figure objects.