Basic scatter plot with plt.scatter in Matplotlib - Mini Project: Build & Apply

Basic scatter plot with plt.scatter

📖 Scenario: You are a data analyst working with a small dataset of students' study hours and their exam scores. You want to visualize the relationship between study hours and exam scores using a scatter plot.

🎯 Goal: Create a scatter plot using plt.scatter to show how study hours relate to exam scores.

📋 What You'll Learn

Create two lists: study_hours and exam_scores with exact values.

Create a variable point_color to set the color of the scatter points.

Use plt.scatter with the lists and point_color to plot the points.

Display the scatter plot using plt.show().

💡 Why This Matters

🌍 Real World

Scatter plots help visualize relationships between two sets of numbers, like hours studied and exam scores, to find patterns.

💼 Career

Data analysts and scientists use scatter plots to explore data and communicate findings clearly.

1

Create the data lists

Create a list called study_hours with these exact values: [2, 3, 5, 7, 8]. Also create a list called exam_scores with these exact values: [50, 60, 70, 80, 90].

Matplotlib

# Create the lists study_hours and exam_scores with the given values
# Your code here

Hint

Use square brackets [] to create lists with the exact numbers given.

2

Set the color for scatter points

Create a variable called point_color and set it to the string 'blue' to use as the color for the scatter plot points.

Matplotlib

study_hours = [2, 3, 5, 7, 8]
exam_scores = [50, 60, 70, 80, 90]
# Create the variable point_color and set it to 'blue'
# Your code here

Hint

Assign the string 'blue' to the variable point_color.

3

Create the scatter plot

Import matplotlib.pyplot as plt. Then use plt.scatter with study_hours, exam_scores, and the color set by point_color to create the scatter plot.

Matplotlib

study_hours = [2, 3, 5, 7, 8]
exam_scores = [50, 60, 70, 80, 90]
point_color = 'blue'
# Import matplotlib.pyplot as plt
# Use plt.scatter with study_hours, exam_scores, and color=point_color
# Your code here

Hint

Use import matplotlib.pyplot as plt at the top. Then call plt.scatter() with the two lists and color=point_color.

4

Display the scatter plot

Use plt.show() to display the scatter plot you created.

Matplotlib

import matplotlib.pyplot as plt

study_hours = [2, 3, 5, 7, 8]
exam_scores = [50, 60, 70, 80, 90]
point_color = 'blue'

plt.scatter(study_hours, exam_scores, color=point_color)
# Use plt.show() to display the plot
# Your code here

Hint

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

Practice

1. What does the plt.scatter(x, y) function do in matplotlib?

easy

A. It creates a line plot connecting x and y points.

B. It creates a scatter plot showing points for x and y data.

C. It creates a bar chart for x and y values.

D. It creates a histogram of x values only.

Solution

1. Step 1: Understand the purpose of plt.scatter

   The function plt.scatter is designed to plot individual points based on two lists or arrays, x and y, showing their relationship.

2. Step 2: Compare with other plot types

   Unlike line plots or bar charts, scatter plots show points without connecting lines or bars.

3. Final Answer:

   It creates a scatter plot showing points for x and y data. -> Option B

4. Quick Check:

   Scatter plot = points for x and y [OK]

Hint: Scatter plots show points, not lines or bars [OK]

Common Mistakes:

• Confusing scatter plot with line plot
• Thinking it creates bars or histograms
• Assuming it only plots x values

2. Which of the following is the correct syntax to create a scatter plot with x and y lists (x horizontal, y vertical) using matplotlib?

easy

A. plt.scatter(x, y)

B. plt.scatter(y, x)

C. plt.plot.scatter(x, y)

D. scatter.plot(x, y)

Solution

1. Step 1: Recall the correct function call

   The correct function to create a scatter plot in matplotlib is plt.scatter(x, y), where x and y are data lists.

2. Step 2: Identify incorrect syntax

   Options with reversed arguments or wrong method chaining like plt.plot.scatter or scatter.plot are invalid.

3. Final Answer:

   plt.scatter(x, y) -> Option A

4. Quick Check:

   Correct syntax = plt.scatter(x, y) [OK]

Hint: Use plt.scatter(x, y) exactly for scatter plots [OK]

Common Mistakes:

• Swapping x and y arguments
• Using plt.plot.scatter instead of plt.scatter
• Calling scatter on wrong object

3. What will be the output of this code?

import matplotlib.pyplot as plt
x = [1, 2, 3]
y = [4, 5, 6]
plt.scatter(x, y)
plt.show()

medium

A. An error because plt.show() is missing.

B. A line plot connecting points (1,4), (2,5), and (3,6).

C. A scatter plot with points at (1,4), (2,5), and (3,6).

D. A bar chart with bars at x positions 1, 2, 3.

Solution

1. Step 1: Understand plt.scatter with given data

   The code plots points at coordinates from lists x and y: (1,4), (2,5), and (3,6).

2. Step 2: Confirm plt.show() displays the plot

   The plt.show() command displays the scatter plot window with these points.

3. Final Answer:

   A scatter plot with points at (1,4), (2,5), and (3,6). -> Option C

4. Quick Check:

   Scatter plot points = (1,4), (2,5), (3,6) [OK]

Hint: Scatter plots show points at (x[i], y[i]) pairs [OK]

Common Mistakes:

• Thinking plt.scatter creates line plots
• Assuming plt.show() is optional and causes error
• Confusing scatter with bar chart

4. Identify the error in this code snippet:

import matplotlib.pyplot as plt
x = [1, 2, 3]
y = [4, 5]
plt.scatter(x, y)
plt.show()

medium

A. plt.scatter requires numpy arrays, not lists.

B. The code is correct and runs without error.

C. plt.show() is missing to display the plot.

D. x and y lists have different lengths causing an error.

Solution

1. Step 1: Check lengths of x and y lists

   The x list has 3 elements, but y has only 2 elements. This mismatch causes plt.scatter to raise a ValueError.

2. Step 2: Understand plt.scatter input requirements

   Both x and y must have the same number of points to plot pairs correctly.

3. Final Answer:

   x and y lists have different lengths causing an error. -> Option D

4. Quick Check:

   Equal length x and y needed [OK]

Hint: x and y must be same length for scatter plot [OK]

Common Mistakes:

• Ignoring length mismatch of x and y
• Thinking plt.scatter needs numpy arrays only
• Assuming plt.show() missing causes error

5. You want to plot points with x = [1, 2, 3, 4] and y = [10, 20, 30, 40], but color points red if y > 25 and blue otherwise. Which code correctly does this?

hard

A. colors = ['red' if val > 25 else 'blue' for val in y]
plt.scatter(x, y, c=colors)
plt.show()

B. plt.scatter(x, y, color=['red' if y > 25 else 'blue'])
plt.show()

C. plt.scatter(x, y, c='red' if y > 25 else 'blue')
plt.show()

D. colors = ['red' if x > 25 else 'blue' for x in x]
plt.scatter(x, y, c=colors)
plt.show()

Solution

1. Step 1: Create color list based on y values

   We use a list comprehension to assign 'red' if y value is greater than 25, else 'blue'. This creates a color list matching each point.

2. Step 2: Pass color list to plt.scatter with c parameter

   Using c=colors applies the color list to points correctly. Then plt.show() displays the plot.

3. Final Answer:

   colors = ['red' if val > 25 else 'blue' for val in y] plt.scatter(x, y, c=colors) plt.show() -> Option A

4. Quick Check:

   Use list comprehension for colors, pass as c=colors [OK]

Hint: Use list comprehension for colors, pass with c=colors [OK]

Common Mistakes:

• Using 'color' instead of 'c' parameter
• Passing single color string instead of list
• Checking condition on x instead of y