Scatter plots in Pandas - Step-by-Step Execution

Concept Flow - Scatter plots

Start with DataFrame

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Select two columns

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Call plot.scatter(x, y)

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Matplotlib creates scatter plot

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Display plot to user

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End

Scatter plots show how two variables relate by plotting points for each pair of values.

Execution Sample

Pandas

import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame({'x': [1, 2, 3], 'y': [4, 5, 6]})
df.plot.scatter(x='x', y='y')
plt.show()

This code creates a scatter plot of 'x' vs 'y' from a simple DataFrame.

Execution Table

Step	Action	DataFrame State	Plot State	Output
1	Create DataFrame with columns 'x' and 'y'	{'x': [1,2,3], 'y': [4,5,6]}	No plot yet	DataFrame ready
2	Call df.plot.scatter(x='x', y='y')	DataFrame unchanged	Scatter plot object created	Plot object ready
3	Matplotlib prepares plot	DataFrame unchanged	Points plotted at (1,4), (2,5), (3,6)	Plot ready to display
4	Call plt.show()	DataFrame unchanged	Plot displayed on screen	Scatter plot visible
5	End of code	DataFrame unchanged	Plot displayed	Execution complete

💡 Plot displayed and code execution finished

Variable Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	After Step 4	Final
df	None	{'x': [1,2,3], 'y': [4,5,6]}	{'x': [1,2,3], 'y': [4,5,6]}	{'x': [1,2,3], 'y': [4,5,6]}	{'x': [1,2,3], 'y': [4,5,6]}	{'x': [1,2,3], 'y': [4,5,6]}
plot	None	None	Scatter plot object	Scatter plot with points	Displayed plot	Displayed plot

Key Moments - 3 Insights

Why do we need to specify x and y columns explicitly in df.plot.scatter?

Because scatter plots need two variables to plot points on x and y axes. The execution_table step 2 shows the call with x='x' and y='y' to tell pandas which columns to use.

Does the DataFrame change after plotting?

No, the DataFrame stays the same throughout. The variable_tracker shows 'df' remains unchanged after each step.

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

The plot object is created but not displayed. Step 4 in execution_table shows plt.show() triggers the plot to appear.

Visual Quiz - 3 Questions

Look at the execution_table at step 3, what points are plotted on the scatter plot?

A (1,2), (3,4), (5,6)

B (4,1), (5,2), (6,3)

C (1,4), (2,5), (3,6)

D (None, None)

💡 Hint

Check the 'Plot State' column at step 3 in execution_table

According to variable_tracker, what is the state of 'plot' after step 2?

A Scatter plot object created

B No plot created

C Plot displayed

D DataFrame changed

💡 Hint

Look at the 'plot' row under 'After Step 2' in variable_tracker

If we omit plt.show(), what will happen according to execution_table?

A Plot will be displayed anyway

B Plot object created but not displayed

C DataFrame will change

D Code will error out

💡 Hint

Refer to step 4 in execution_table where plt.show() triggers display

Concept Snapshot

Scatter plots show points for two variables on x and y axes.
Use df.plot.scatter(x='col1', y='col2') to create.
Matplotlib draws points for each row.
Call plt.show() to display the plot.
DataFrame stays unchanged during plotting.

Full Transcript

This visual execution shows how to create a scatter plot using pandas. First, a DataFrame with two columns is created. Then, df.plot.scatter is called with x and y column names to make a scatter plot object. Matplotlib plots points for each pair of values. Finally, plt.show() displays the plot on screen. The DataFrame does not change during this process. Key moments include specifying x and y columns, understanding DataFrame immutability, and the role of plt.show(). The quizzes test understanding of plotted points, plot object state, and plot display behavior.