Pyplot interface overview in Matplotlib - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the main purpose of the pyplot interface in matplotlib?

The pyplot interface provides a simple way to create and customize plots by using functions that work like MATLAB commands. It helps you make graphs step-by-step easily.

beginner

Which function in pyplot is used to create a new figure window?

The function plt.figure() creates a new figure window where you can draw your plots.

beginner

How do you add a title to a plot using pyplot?

Use plt.title('Your Title') to add a title to the current plot.

beginner

What does plt.show() do in the pyplot interface?

plt.show() displays all the figures and plots you have created. It opens the plot window so you can see your graph.

intermediate

Explain the difference between plt.plot() and plt.scatter().

plt.plot() draws lines connecting points, useful for continuous data. plt.scatter() draws individual points without connecting lines, useful for showing data distribution.

Which pyplot function starts a new plot figure?

A plt.figure()

B plt.plot()

C plt.show()

D plt.title()

plt.figure() creates a new figure window for plotting.

What does plt.show() do?

A Displays the plot window

B Saves the plot to a file

C Adds a title to the plot

D Creates a new plot

plt.show() opens the window to display your plot.

Which function adds a title to your plot?

A plt.ylabel()

B plt.xlabel()

C plt.title()

D plt.legend()

plt.title() sets the title text on the plot.

If you want to plot points without connecting lines, which pyplot function should you use?

A plt.hist()

B plt.plot()

C plt.bar()

D plt.scatter()

plt.scatter() plots individual points without lines.

What is the typical order of commands to create and display a simple line plot?

A plt.show(), plt.plot(), plt.figure()

B plt.figure(), plt.plot(), plt.show()

C plt.plot(), plt.figure(), plt.show()

D plt.plot(), plt.show(), plt.figure()

First create a figure with plt.figure(), then plot with plt.plot(), and finally display with plt.show().

Describe the basic workflow of creating a plot using the pyplot interface.

Think about the steps from starting a plot to seeing it on screen.

Explain when you would use plt.plot() versus plt.scatter() in pyplot.

Consider the visual difference between lines and points.

Practice

1. What is the main purpose of the plt.show() function in matplotlib's Pyplot interface?

easy

A. To create a new figure object

B. To save the plot as an image file

C. To clear the current plot

D. To display the created plot on the screen

Solution

1. Step 1: Understand the role of plt.show()

   This function is used to display all the figures and plots that have been created so far.

2. Step 2: Differentiate from other functions

   Functions like plt.savefig() save images, and plt.clf() clears plots, but plt.show() actually opens the window to view the plot.

3. Final Answer:

   To display the created plot on the screen -> Option D

4. Quick Check:

   Display plot = plt.show() [OK]

Hint: Remember: plt.show() always displays your plot [OK]

Common Mistakes:

• Confusing plt.show() with plt.savefig()
• Thinking plt.show() clears the plot
• Assuming plt.show() creates a new plot

2. Which of the following is the correct way to import the Pyplot interface from matplotlib?

easy

A. import matplotlib.pyplot as plt

B. import pyplot.matplotlib as plt

C. from matplotlib import plot as plt

D. import matplotlib.pyplot

Solution

1. Step 1: Recall the standard import syntax

   The common and recommended way is to import pyplot from matplotlib and alias it as plt for easy use.

2. Step 2: Check each option

   Only import matplotlib.pyplot as plt is syntactically correct and widely used.

3. Final Answer:

   import matplotlib.pyplot as plt -> Option A

4. Quick Check:

   Standard import = import matplotlib.pyplot as plt [OK]

Hint: Always import pyplot as plt for convenience [OK]

Common Mistakes:

• Swapping module and submodule names
• Using incorrect alias names
• Missing 'as plt' alias

3. What will be the output of the following code?

import matplotlib.pyplot as plt
plt.plot([1, 2, 3], [4, 5, 6])
plt.title('Sample Plot')
plt.show()

medium

A. A line plot with points (1,4), (2,5), (3,6) and title 'Sample Plot' displayed

B. A scatter plot with points (1,4), (2,5), (3,6) without any title

C. No plot will be shown because plt.show() is missing

D. An error because plt.title() is not a valid function

Solution

1. Step 1: Analyze the plot function

   plt.plot() with two lists creates a line plot connecting points (1,4), (2,5), and (3,6).

2. Step 2: Check the title and show functions

   plt.title('Sample Plot') adds the title, and plt.show() displays the plot window.

3. Final Answer:

   A line plot with points (1,4), (2,5), (3,6) and title 'Sample Plot' displayed -> Option A

4. Quick Check:

   plt.plot + plt.title + plt.show = line plot with title [OK]

Hint: plt.plot draws lines; plt.show displays them [OK]

Common Mistakes:

• Confusing plt.plot with scatter plot
• Forgetting plt.show() to display plot
• Assuming plt.title() is invalid

4. Identify the error in the following code snippet:

import matplotlib.pyplot as plt
plt.plot([1, 2, 3], [4, 5])
plt.show()

medium

A. plt.show() is missing, so plot won't display

B. plt.plot() requires only one list, so two lists cause a syntax error

C. The x and y data lists have different lengths causing a ValueError

D. No error; the plot will display correctly

Solution

1. Step 1: Check the lengths of x and y data

   The x list has 3 elements, but the y list has only 2 elements, which is invalid for plotting.

2. Step 2: Understand the error raised

   This mismatch causes a ValueError because each x must have a corresponding y value.

3. Final Answer:

   The x and y data lists have different lengths causing a ValueError -> Option C

4. Quick Check:

   Length mismatch in plt.plot = ValueError [OK]

Hint: x and y lists must be same length in plt.plot [OK]

Common Mistakes:

• Assuming plt.plot accepts different length lists
• Thinking plt.show() is missing
• Believing two lists cause syntax error

5. You want to create a plot with two lines on the same figure using Pyplot. Which code snippet correctly does this?

hard

A. import matplotlib.pyplot as plt
plt.plot([1, 2, 3], [4, 5, 6])
plt.clear()
plt.plot([1, 2, 3], [6, 5, 4])
plt.show()

B. import matplotlib.pyplot as plt
plt.plot([1, 2, 3], [4, 5, 6])
plt.plot([1, 2, 3], [6, 5, 4])
plt.show()

C. import matplotlib.pyplot as plt
plt.plot([1, 2, 3], [4, 5, 6])
plt.show()
plt.show()

D. import matplotlib.pyplot as plt
plt.plot([1, 2, 3], [4, 5, 6])
plt.show()
plt.plot([1, 2, 3], [6, 5, 4])

Solution

1. Step 1: Understand how to plot multiple lines

   Calling plt.plot() multiple times before plt.show() adds multiple lines to the same figure.

2. Step 2: Check each option for correct sequence

   import matplotlib.pyplot as plt plt.plot([1, 2, 3], [4, 5, 6]) plt.plot([1, 2, 3], [6, 5, 4]) plt.show() calls both plot commands before a single show, so both lines appear together. Others either call show too early or clear the plot.

3. Final Answer:

   import matplotlib.pyplot as plt plt.plot([1, 2, 3], [4, 5, 6]) plt.plot([1, 2, 3], [6, 5, 4]) plt.show() -> Option B

4. Quick Check:

   Multiple plt.plot calls before plt.show = multiple lines [OK]

Hint: Plot all lines before plt.show() to display together [OK]

Common Mistakes:

• Calling plt.show() too early clears previous plots
• Using plt.clear() removes existing plots
• Expecting multiple plt.show() calls to overlay plots