Plot customization (title, labels, figsize) in Pandas - Step-by-Step Execution

Concept Flow - Plot customization (title, labels, figsize)

Create DataFrame

↓

Call plot() method

↓

Set figsize parameter

↓

Add title with set_title()

↓

Add x-label and y-label with set_xlabel(), set_ylabel()

↓

Show customized plot

Start with data, call plot, customize size, add title and labels, then display the plot.

Execution Sample

Pandas

import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame({'A': [1, 3, 2, 4]})
ax = df.plot(figsize=(6,4))
ax.set_title('My Plot')
ax.set_xlabel('X Axis')
ax.set_ylabel('Y Axis')
plt.show()

This code creates a simple line plot with a custom size, title, and axis labels.

Execution Table

Step	Action	Parameter/Method	Effect/Result
1	Create DataFrame	pd.DataFrame({'A': [1,3,2,4]})	DataFrame with column A and 4 rows
2	Call plot()	df.plot(figsize=(6,4))	Plot object created with size 6x4 inches
3	Set title	ax.set_title('My Plot')	Plot title set to 'My Plot'
4	Set x-label	ax.set_xlabel('X Axis')	X-axis label set to 'X Axis'
5	Set y-label	ax.set_ylabel('Y Axis')	Y-axis label set to 'Y Axis'
6	Show plot	plt.show()	Plot window opens showing customized plot

💡 Plot displayed with specified size, title, and axis labels

Variable Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	After Step 4	After Step 5	Final
df	None	DataFrame with data	DataFrame unchanged	DataFrame unchanged	DataFrame unchanged	DataFrame unchanged	DataFrame unchanged
ax	None	None	AxesSubplot object with figsize (6,4)	AxesSubplot with title set	AxesSubplot with x-label set	AxesSubplot with y-label set	AxesSubplot fully customized

Key Moments - 3 Insights

Why do we use ax.set_title() instead of passing title directly to df.plot()?

Because df.plot() accepts figsize as a parameter but to customize title and labels after plot creation, we use ax methods like set_title(), as shown in steps 3-5 of the execution_table.

What does figsize=(6,4) mean in the plot() method?

It sets the plot size to 6 inches wide and 4 inches tall, controlling how big the plot appears, as seen in step 2 of the execution_table.

Can we set axis labels before calling plt.show()?

Yes, axis labels must be set before plt.show() to appear on the plot, as shown in steps 4 and 5 before step 6 in the execution_table.

Visual Quiz - 3 Questions

Look at the variable_tracker table, what is the value of 'ax' after step 2?

A None

B DataFrame object

C AxesSubplot object with figsize (6,4)

D String 'My Plot'

💡 Hint

Check the 'ax' row under 'After Step 2' column in variable_tracker.

According to the execution_table, which step sets the x-axis label?

A Step 2

B Step 4

C Step 3

D Step 5

💡 Hint

Look for the row where 'Action' is 'Set x-label' in execution_table.

If figsize was changed to (8,6), what would change in the execution_table?

A Step 2 effect would say 'Plot object created with size 8x6 inches'

B Step 3 would set a different title

C Step 4 would set a different x-label

D No change in any step

💡 Hint

Focus on the 'Effect/Result' column of step 2 in execution_table.

Concept Snapshot

Plot customization in pandas:
- Use df.plot(figsize=(w,h)) to set plot size
- Use ax.set_title('title') to add a title
- Use ax.set_xlabel('label') and ax.set_ylabel('label') for axis labels
- Call plt.show() to display the plot
- Customize after plot creation using ax methods

Full Transcript

This visual execution shows how to customize a pandas plot by setting the figure size, adding a title, and labeling the axes. First, a DataFrame is created with sample data. Then, the plot() method is called with the figsize parameter to control the plot size. After the plot object is created, the title and axis labels are set using ax.set_title(), ax.set_xlabel(), and ax.set_ylabel(). Finally, plt.show() displays the customized plot. Variables like 'df' and 'ax' change state step-by-step, helping beginners understand how plot customization works in pandas.

Practice

1. What does the figsize parameter control when creating a plot with pandas?

easy

A. The type of plot (line, bar, scatter).

B. The color of the plot background.

C. The font size of the plot title.

D. The size of the plot figure in inches (width, height).

Solution

1. Step 1: Understand the role of figsize

   The figsize parameter sets the width and height of the plot in inches.

2. Step 2: Differentiate from other parameters

   Color, font size, and plot type are controlled by other parameters, not figsize.

3. Final Answer:

   The size of the plot figure in inches (width, height). -> Option D

4. Quick Check:

   Figsize = plot size in inches [OK]

Hint: Figsize sets plot width and height in inches [OK]

Common Mistakes:

• Confusing figsize with color or font size
• Thinking figsize changes plot type
• Using figsize as a string instead of tuple

2. Which of the following is the correct way to set the plot title and axis labels in pandas?

easy

A. df.plot().set_title('Sales').set_xlabel('Month').set_ylabel('Revenue')

B. df.plot().set(title='Sales', xlabel='Month', ylabel='Revenue')

C. df.plot(title='Sales', x_label='Month', y_label='Revenue')

D. df.plot().title('Sales').xlabel('Month').ylabel('Revenue')

Solution

1. Step 1: Recall pandas plot method chaining

   After plotting, you can chain set_title(), set_xlabel(), and set_ylabel() to set title and labels.

2. Step 2: Check syntax correctness

   df.plot().set_title('Sales').set_xlabel('Month').set_ylabel('Revenue') uses correct method names and chaining syntax. df.plot(title='Sales', x_label='Month', y_label='Revenue') tries to pass labels directly to plot() which is invalid. df.plot().set(title='Sales', xlabel='Month', ylabel='Revenue') uses set() with wrong keys. df.plot().title('Sales').xlabel('Month').ylabel('Revenue') uses non-existent methods.

3. Final Answer:

   df.plot().set_title('Sales').set_xlabel('Month').set_ylabel('Revenue') -> Option A

4. Quick Check:

   Use set_title, set_xlabel, set_ylabel methods [OK]

Hint: Use set_title, set_xlabel, set_ylabel after plot() [OK]

Common Mistakes:

• Passing title or labels directly to plot()
• Using wrong method names like title() instead of set_title()
• Trying to set labels with set() method

3. Given the code below, what will be the size of the plot figure?

import pandas as pd
import matplotlib.pyplot as plt

data = {'A': [1, 3, 2, 4]}
df = pd.DataFrame(data)

ax = df.plot(figsize=(8, 4))
plt.show()

medium

A. 8 inches wide and 4 inches tall

B. 4 inches wide and 8 inches tall

C. Default size because figsize is ignored

D. 8 pixels wide and 4 pixels tall

Solution

1. Step 1: Understand figsize parameter

   The figsize argument takes a tuple (width, height) in inches.

2. Step 2: Check the given tuple

   The tuple is (8, 4), so width is 8 inches and height is 4 inches.

3. Final Answer:

   8 inches wide and 4 inches tall -> Option A

4. Quick Check:

   Figsize=(8,4) means width=8, height=4 inches [OK]

Hint: Figsize tuple is (width, height) in inches [OK]

Common Mistakes:

• Swapping width and height values
• Thinking figsize uses pixels
• Assuming figsize is ignored by pandas

4. Identify the error in the following code that tries to set the plot title and labels:

import pandas as pd
data = {'x': [1, 2, 3], 'y': [4, 5, 6]}
df = pd.DataFrame(data)
plot = df.plot()
plot.title('My Plot')
plot.xlabel('X-axis')
plot.ylabel('Y-axis')

medium

A. DataFrame is missing a column for labels.

B. Methods title(), xlabel(), ylabel() do not exist for the plot object.

C. Plotting requires plt.show() to display labels.

D. The DataFrame columns must be strings to set labels.

Solution

1. Step 1: Check method names on plot object

   The plot object returned by pandas uses set_title(), set_xlabel(), and set_ylabel() methods, not title(), xlabel(), or ylabel().

2. Step 2: Identify the error

   Calling plot.title() causes an AttributeError because the method does not exist.

3. Final Answer:

   Methods title(), xlabel(), ylabel() do not exist for the plot object. -> Option B

4. Quick Check:

   Use set_title, set_xlabel, set_ylabel methods [OK]

Hint: Use set_title, set_xlabel, set_ylabel methods [OK]

Common Mistakes:

• Using title() instead of set_title()
• Forgetting to call plt.show() (though not error here)
• Assuming DataFrame columns affect label setting

5. You want to create a bar plot from a DataFrame df with columns 'Year' and 'Sales'. You want the plot to be 10 inches wide and 6 inches tall, with the title 'Annual Sales', x-axis label 'Year', and y-axis label 'Sales'. Which code snippet correctly achieves this?

hard

A. ax = df.plot.bar(x='Year', y='Sales')
plt.title('Annual Sales')
plt.xlabel('Year')
plt.ylabel('Sales')
plt.figure(figsize=(10,6))

B. df.plot.bar(x='Year', y='Sales', title='Annual Sales', x_label='Year', y_label='Sales', figsize=(10,6))

C. ax = df.plot.bar(x='Year', y='Sales', figsize=(10,6))
ax.set_title('Annual Sales')
ax.set_xlabel('Year')
ax.set_ylabel('Sales')

D. df.plot.bar(x='Year', y='Sales')
ax.set_title('Annual Sales')
ax.set_xlabel('Year')
ax.set_ylabel('Sales')
plt.figure(figsize=(10,6))

Solution

1. Step 1: Set figure size correctly

   Figure size must be set in the plot.bar() call using figsize=(10,6). ax = df.plot.bar(x='Year', y='Sales', figsize=(10,6)) ax.set_title('Annual Sales') ax.set_xlabel('Year') ax.set_ylabel('Sales') does this correctly.

2. Step 2: Set title and axis labels on the Axes object

   ax = df.plot.bar(x='Year', y='Sales', figsize=(10,6)) ax.set_title('Annual Sales') ax.set_xlabel('Year') ax.set_ylabel('Sales') uses ax.set_title(), ax.set_xlabel(), and ax.set_ylabel() which is the correct way to set labels after plotting.

3. Step 3: Check other options

   df.plot.bar(x='Year', y='Sales', title='Annual Sales', x_label='Year', y_label='Sales', figsize=(10,6)) tries to pass title and labels directly to plot.bar(), which is not supported. ax = df.plot.bar(x='Year', y='Sales') plt.title('Annual Sales') plt.xlabel('Year') plt.ylabel('Sales') plt.figure(figsize=(10,6)) sets figure size after plotting, which has no effect. df.plot.bar(x='Year', y='Sales') ax.set_title('Annual Sales') ax.set_xlabel('Year') ax.set_ylabel('Sales') plt.figure(figsize=(10,6)) uses ax without defining it and sets figure size after plotting, which is incorrect.

4. Final Answer:

   ax = df.plot.bar(x='Year', y='Sales', figsize=(10,6)) ax.set_title('Annual Sales') ax.set_xlabel('Year') ax.set_ylabel('Sales') -> Option C

5. Quick Check:

   Set figsize in plot call; use set_title and set_xlabel on Axes [OK]

Hint: Set figsize in plot call; use set_title and set_xlabel on Axes [OK]

Common Mistakes:

• Passing title and labels directly to plot.bar()
• Setting figure size after plotting
• Using undefined Axes object