Basic scatter plot with plt.scatter in Matplotlib - Step-by-Step Execution

Concept Flow - Basic scatter plot with plt.scatter

Prepare data points

↓

Call plt.scatter(x, y)

↓

Plot points on graph

↓

Show or save plot

First, we prepare the x and y data points. Then we call plt.scatter to plot these points. Finally, we display the scatter plot.

Execution Sample

Matplotlib

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

This code plots four points on a scatter plot and shows the graph.

Execution Table

Step	Action	Input/Parameters	Result/Output
1	Prepare x data	[1, 2, 3, 4]	x list created
2	Prepare y data	[10, 20, 25, 30]	y list created
3	Call plt.scatter	x=[1, 2, 3, 4], y=[10, 20, 25, 30]	Scatter plot points placed on graph
4	Call plt.show	None	Graph window opens showing scatter plot

💡 Plot displayed and program waits for user to close graph window

Variable Tracker

Variable	Start	After Step 1	After Step 2	Final
x	undefined	[1, 2, 3, 4]	[1, 2, 3, 4]	[1, 2, 3, 4]
y	undefined	undefined	[10, 20, 25, 30]	[10, 20, 25, 30]

Key Moments - 2 Insights

Why do we need both x and y lists for plt.scatter?

Because plt.scatter plots points by pairing each x value with a y value, as shown in execution_table step 3.

What happens if plt.show() is not called?

The plot will not appear on screen because plt.show() triggers the display, as seen in execution_table step 4.

Visual Quiz - 3 Questions

Look at the execution_table, what is the value of y after Step 2?

A undefined

B [10, 20, 25, 30]

C [1, 2, 3, 4]

D None

💡 Hint

Check the variable_tracker table under 'y' after Step 2 column

At which step does the scatter plot points get placed on the graph?

A Step 3

B Step 2

C Step 1

D Step 4

💡 Hint

Look at the 'Result/Output' column in execution_table for Step 3

If we skip plt.show(), what will happen according to the execution flow?

A Plot will still display automatically

B Plot window will open but be empty

C Plot will not display on screen

D Code will error out

💡 Hint

Refer to key_moments explanation about plt.show() and execution_table Step 4

Concept Snapshot

plt.scatter(x, y) plots points with x and y coordinates.
Both x and y must be lists or arrays of same length.
Call plt.show() to display the plot window.
Useful for visualizing relationships between two variables.

Full Transcript

This visual execution shows how to create a basic scatter plot using matplotlib's plt.scatter function. First, we prepare two lists: x and y, which hold the horizontal and vertical coordinates of points. Then, plt.scatter is called with these lists to place points on the graph. Finally, plt.show() displays the plot window so we can see the scatter plot. Variables x and y remain unchanged after creation. Key points include needing both x and y lists and calling plt.show() to see the plot. The execution table traces each step from data preparation to plot display. The quiz tests understanding of variable values and function effects.

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