Pyplot interface overview in Matplotlib - Mini Project: Build & Apply

Pyplot Interface Overview

📖 Scenario: You are working as a data analyst and want to create a simple line chart to visualize sales data over a week. You will use the matplotlib.pyplot interface to plot the data.

🎯 Goal: Build a simple line plot using matplotlib.pyplot to show sales numbers for each day of the week.

📋 What You'll Learn

Create a list of sales numbers for 7 days

Create a list of day names for the x-axis

Use matplotlib.pyplot to plot the sales data

Add labels for x-axis and y-axis

Display the plot

💡 Why This Matters

🌍 Real World

Line charts are common in business to track sales, website visits, or any data changing over time.

💼 Career

Data analysts and scientists use matplotlib.pyplot to quickly visualize data and communicate insights.

1

Create sales data and days list

Create a list called sales with these exact values: [150, 200, 170, 220, 180, 190, 210]. Also create a list called days with these exact values: ["Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"].

Matplotlib

# Create the sales and days lists
# Your code here

Hint

Use square brackets to create lists. Put the exact numbers and day names as shown.

2

Import pyplot and set up plot

Import matplotlib.pyplot as plt. This will allow you to use plotting functions easily.

Matplotlib

sales = [150, 200, 170, 220, 180, 190, 210]
days = ["Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"]
# Import matplotlib.pyplot as plt
# Your code here

Hint

Use the syntax import matplotlib.pyplot as plt to import pyplot.

3

Plot sales data with labels

Use plt.plot(days, sales) to create a line plot. Then add x-axis label "Days" using plt.xlabel("Days") and y-axis label "Sales" using plt.ylabel("Sales").

Matplotlib

import matplotlib.pyplot as plt

sales = [150, 200, 170, 220, 180, 190, 210]
days = ["Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"]
# Plot the sales data and add axis labels
# Your code here

Hint

Use plt.plot() to draw the line. Use plt.xlabel() and plt.ylabel() to add labels.

4

Display the plot

Use plt.show() to display the plot window with your line chart.

Matplotlib

import matplotlib.pyplot as plt

sales = [150, 200, 170, 220, 180, 190, 210]
days = ["Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"]

plt.plot(days, sales)
plt.xlabel("Days")
plt.ylabel("Sales")
# Display the plot
# Your code here

Hint

Call plt.show() to open the plot window.

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