Scatter plots in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a scatter plot using matplotlib.

Data Analysis Python

import matplotlib.pyplot as plt
x = [1, 2, 3, 4]
y = [10, 20, 25, 30]
plt.[1](x, y)
plt.show()

Drag options to blanks, or click blank then click option'

Ascatter

Bplot

Cbar

Dhist

Attempts:

3 left

💡 Hint

Common Mistakes

Using plt.plot() which creates a line plot instead of scatter plot.

Using plt.bar() which creates bar charts, not scatter plots.

The scatter function creates a scatter plot by plotting points at the given x and y coordinates.

2fill in blank

medium

Complete the code to add labels to the x and y axes in the scatter plot.

Data Analysis Python

import matplotlib.pyplot as plt
x = [5, 7, 8, 7, 2]
y = [99, 86, 87, 88, 100]
plt.scatter(x, y)
plt.xlabel([1])
plt.ylabel('Scores')
plt.show()

Drag options to blanks, or click blank then click option'

A'Weight'

B'Height'

C'Age'

D'Temperature'

Attempts:

3 left

💡 Hint

Common Mistakes

Forgetting to put the label text inside quotes.

Using the wrong label that does not match the data.

The x-axis label should describe the data on the x-axis. Here, it is 'Age'.

3fill in blank

hard

Fix the error in the code to correctly plot a scatter plot with red points.

Data Analysis Python

import matplotlib.pyplot as plt
x = [1, 2, 3, 4]
y = [10, 20, 25, 30]
plt.scatter(x, y, color=[1])
plt.show()

Drag options to blanks, or click blank then click option'

Ared

B'r'

Cr

D'red'

Attempts:

3 left

💡 Hint

Common Mistakes

Passing color without quotes causing a NameError.

Using full color name without quotes.

The color argument requires a string, so it must be in quotes. 'r' is a shorthand for red color.

4fill in blank

hard

Fill both blanks to create a scatter plot with blue points and size 100.

Data Analysis Python

import matplotlib.pyplot as plt
x = [2, 4, 6, 8]
y = [5, 15, 25, 35]
plt.scatter(x, y, color=[1], s=[2])
plt.show()

Drag options to blanks, or click blank then click option'

A'blue'

B50

C100

D'green'

Attempts:

3 left

💡 Hint

Common Mistakes

Using color without quotes.

Setting size too small to notice.

The color is set to 'blue' as a string, and the size s is set to 100 for larger points.

5fill in blank

hard

Fill all three blanks to create a scatter plot with green points, size 80, and alpha transparency 0.5.

Data Analysis Python

import matplotlib.pyplot as plt
x = [1, 3, 5, 7]
y = [2, 4, 6, 8]
plt.scatter(x, y, color=[1], s=[2], alpha=[3])
plt.show()

Drag options to blanks, or click blank then click option'

A'green'

B80

C0.5

D'yellow'

Attempts:

3 left

💡 Hint

Common Mistakes

Passing color without quotes.

Using alpha values outside 0 to 1 range.

Setting size too small or too large.

The color is 'green' as a string, size s is 80 for medium points, and alpha 0.5 makes points semi-transparent.

Practice

1. What does a scatter plot primarily show in data analysis?

easy

A. The relationship between two numerical variables

B. The total count of categories

C. The average value of a dataset

D. The sum of all data points

Solution

1. Step 1: Understand scatter plot purpose

   A scatter plot is used to display how two numerical variables relate to each other by plotting points on a graph.

2. Step 2: Compare options to definition

   Options B, C, and D describe other chart types or calculations, not relationships between two variables.

3. Final Answer:

   The relationship between two numerical variables -> Option A

4. Quick Check:

   Scatter plot = relationship between two numbers [OK]

Hint: Scatter plots always compare two numeric sets [OK]

Common Mistakes:

• Confusing scatter plots with bar charts
• Thinking scatter plots show totals or averages
• Ignoring that scatter plots need two numeric variables

2. Which of the following is the correct way to create a scatter plot using matplotlib in Python?

easy

A. plt.bar(x, y)

B. plt.plot(x, y, kind='scatter')

C. plt.scatterplot(x, y)

D. plt.scatter(x, y)

Solution

1. Step 1: Recall matplotlib scatter syntax

   Matplotlib uses plt.scatter(x, y) to create scatter plots.

2. Step 2: Check other options for correctness

   plt.plot(x, y, kind='scatter') is incorrect syntax; plt.plot does not take kind='scatter'. plt.bar(x, y) creates bar charts. plt.scatterplot(x, y) is not a valid matplotlib function.

3. Final Answer:

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

4. Quick Check:

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

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

Common Mistakes:

• Using plt.plot with kind='scatter' (wrong syntax)
• Confusing scatter with bar plot functions
• Trying to use plt.scatterplot which doesn't exist

3. What will the following code output?

import matplotlib.pyplot as plt
x = [1, 2, 3, 4]
y = [10, 20, 25, 30]
plt.scatter(x, y)
plt.title('Test Plot')
plt.xlabel('X axis')
plt.ylabel('Y axis')
plt.show()

medium

A. An error because plt.scatter requires more arguments

B. A scatter plot with points at (1,10), (2,20), (3,25), (4,30) and labeled axes

C. A bar chart with bars at x positions 1 to 4

D. A line plot connecting points (1,10), (2,20), (3,25), (4,30)

Solution

1. Step 1: Analyze the code commands

   The code uses plt.scatter(x, y) which plots points at given x and y coordinates. Titles and labels are added correctly.

2. Step 2: Understand the plot output

   The plot will show points at (1,10), (2,20), (3,25), (4,30) with axis labels and a title. No lines or bars are drawn.

3. Final Answer:

   A scatter plot with points at (1,10), (2,20), (3,25), (4,30) and labeled axes -> Option B

4. Quick Check:

   plt.scatter plots points, not lines or bars [OK]

Hint: plt.scatter plots points, not lines or bars [OK]

Common Mistakes:

• Thinking plt.scatter draws lines between points
• Confusing scatter plot with bar chart
• Assuming plt.scatter needs extra arguments

4. Identify the error in this code snippet that tries to create a scatter plot:

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

medium

A. plt.scatter requires a third argument for color

B. plt.show() is missing parentheses

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

D. No error, code runs fine

Solution

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

   x has 3 elements, y has 2 elements. Scatter plot requires equal length for x and y.

2. Step 2: Understand matplotlib error behavior

   Matplotlib will raise a ValueError because x and y lengths differ. Options A and C are incorrect because color is optional and plt.show() is correctly called.

3. Final Answer:

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

4. Quick Check:

   Equal length x and y needed for scatter [OK]

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

Common Mistakes:

• Ignoring length mismatch between x and y
• Thinking color argument is mandatory
• Assuming plt.show() can be called without parentheses

5. You have a dataset with columns 'Age' and 'Income'. You want to create a scatter plot to find if older people tend to earn more. Which steps should you follow to create a clear scatter plot in Python using pandas and matplotlib?

hard

A. Import pandas and matplotlib, extract 'Age' and 'Income' columns as x and y, use plt.scatter(x, y), add title and axis labels, then plt.show()

B. Use plt.bar with 'Age' as x and 'Income' as height, then add labels

C. Plot a line graph with 'Age' on x-axis and 'Income' on y-axis without labels

D. Create a pie chart showing distribution of 'Income' grouped by 'Age' categories

Solution

1. Step 1: Extract relevant columns for scatter plot

   Use pandas to get 'Age' and 'Income' columns as x and y arrays for plotting.

2. Step 2: Plot scatter and add labels

   Use plt.scatter(x, y) to plot points, add a title and axis labels for clarity, then display with plt.show().

3. Final Answer:

   Import pandas and matplotlib, extract 'Age' and 'Income' columns as x and y, use plt.scatter(x, y), add title and axis labels, then plt.show() -> Option A

4. Quick Check:

   Scatter plot with labels = Import pandas and matplotlib, extract 'Age' and 'Income' columns as x and y, use plt.scatter(x, y), add title and axis labels, then plt.show() [OK]

Hint: Extract columns, use plt.scatter, add labels, then show plot [OK]

Common Mistakes:

• Using bar or pie charts instead of scatter for relationships
• Skipping axis labels and titles
• Plotting line graph which implies continuous trend