Scatter plots in Data Analysis Python - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a scatter plot?

A scatter plot is a graph that shows points representing values for two different variables. It helps us see if there is a relationship or pattern between them.

beginner

Which Python library is commonly used to create scatter plots?

Matplotlib is a popular Python library used to create scatter plots easily with the function plt.scatter().

beginner

How do you add labels to the axes in a scatter plot using Matplotlib?

Use plt.xlabel('X label') and plt.ylabel('Y label') to add labels to the x-axis and y-axis respectively.

beginner

What does it mean if points in a scatter plot form a clear upward trend?

It means there is a positive correlation: as one variable increases, the other tends to increase too.

intermediate

How can you change the color and size of points in a scatter plot in Matplotlib?

Use the c parameter to set colors and s parameter to set sizes in plt.scatter(). For example, plt.scatter(x, y, c='red', s=50).

What does each point in a scatter plot represent?

A A pair of values from two variables

B A single value from one variable

C The average of all data points

D A summary statistic

Each point shows one value from each of the two variables, plotted on x and y axes.

Which function creates a scatter plot in Matplotlib?

A plt.plot()

B plt.hist()

C plt.scatter()

D plt.bar()

plt.scatter() is used specifically for scatter plots.

If points in a scatter plot are randomly spread with no pattern, what does it suggest?

A Strong positive correlation

B No clear relationship

C Strong negative correlation

D Data error

Random spread means no clear relationship between variables.

How can you add a title to a scatter plot in Matplotlib?

A plt.title('My Title')

B plt.label('My Title')

C plt.name('My Title')

D plt.header('My Title')

Use plt.title() to add a title to your plot.

Which parameter controls the size of points in plt.scatter()?

A marker

B c

C size

D s

The s parameter sets the size of points.

Explain how to create a basic scatter plot in Python using Matplotlib.

Think about the steps from importing the library to displaying the plot.

Describe what a scatter plot can tell you about the relationship between two variables.

Focus on what the pattern of points means.

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