Plot customization (title, labels, figsize) in Pandas - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the figsize parameter control in a pandas plot?

The figsize parameter controls the size of the plot figure in inches, given as a tuple (width, height). It helps make the plot bigger or smaller to fit your needs.

beginner

How do you add a title to a pandas plot?

You add a title by using the title parameter inside the plot function, like df.plot(title='My Title'). This shows a heading on top of the plot.

beginner

How can you label the x-axis and y-axis in a pandas plot?

You can label axes by using xlabel and ylabel parameters inside the plot function, for example: df.plot(xlabel='Time', ylabel='Value').

beginner

True or False: You can customize the plot size, title, and axis labels all in one pandas plot command.

True. You can set figsize, title, xlabel, and ylabel all together in one call to df.plot().

beginner

Why is it helpful to customize the title and labels of a plot?

Customizing the title and labels makes the plot easier to understand. It tells the viewer what the plot shows and what the axes represent, just like a clear signpost.

Which parameter changes the size of a pandas plot?

A figsize

B title

C xlabel

D ylabel

The figsize parameter sets the width and height of the plot figure.

How do you add a title 'Sales Over Time' to a pandas plot?

A df.plot(figsize='Sales Over Time')

B df.plot(title='Sales Over Time')

C df.plot(label='Sales Over Time')

D df.plot(xlabel='Sales Over Time')

Use the title parameter inside the plot function to add a title.

Which parameters label the axes in a pandas plot?

A xlabel and ylabel

B title and figsize

C label and legend

D color and style

Use xlabel for the x-axis and ylabel for the y-axis labels.

What is the correct way to set a plot size of 8 inches wide and 4 inches tall?

A df.plot(size=(8,4))

B df.plot(dimensions=[8,4])

C df.plot(figsize=(8,4))

D df.plot(scale=(8,4))

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

True or False: You must call separate functions to add title and labels after plotting in pandas.

A True

B Only for labels

C Only for title

D False

You can add title and labels directly inside the df.plot() call.

Explain how to customize a pandas plot with a title, axis labels, and figure size in one command.

Think about the parameters you pass inside df.plot()

Why is it important to add titles and labels to your plots when sharing data?

Imagine showing a plot to a friend who doesn't know the data

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