Plot customization (title, labels, figsize) in Pandas

Introduction

We add titles, labels, and size to plots to make them easier to understand and look better.

When you want to explain what the plot shows with a clear title.

When you want to name the x-axis and y-axis so people know what data they represent.

When the default plot size is too small or too big for your presentation or report.

When you want your plot to fit nicely in a document or slide.

When you want to make your plot look professional and clear.

Syntax

Pandas

df.plot(figsize=(width, height), title='Your Title', xlabel='X-axis Label', ylabel='Y-axis Label')

figsize takes a tuple with width and height in inches.

title, xlabel, and ylabel are strings to name parts of the plot.

Examples

Adds a title to the plot.

Pandas

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

Adds labels to the x-axis and y-axis.

Pandas

df.plot(xlabel='Month', ylabel='Sales')

Changes the plot size to 10 inches wide and 5 inches tall.

Pandas

df.plot(figsize=(10, 5))

Combines size, title, and axis labels in one plot.

Pandas

df.plot(figsize=(8, 4), title='Monthly Sales', xlabel='Month', ylabel='Sales')

Sample Program

This code creates a simple sales data table, then plots it with a title, axis labels, and a custom size.

Pandas

import pandas as pd
import matplotlib.pyplot as plt

# Create sample data
data = {'Month': ['Jan', 'Feb', 'Mar', 'Apr'], 'Sales': [250, 300, 400, 350]}
df = pd.DataFrame(data)
df.set_index('Month', inplace=True)

# Plot with customization
plot = df.plot(
    figsize=(8, 4),
    title='Monthly Sales',
    xlabel='Month',
    ylabel='Sales'
)
plt.show()

Important Notes

You need to import matplotlib.pyplot to show the plot when running outside notebooks.

Setting the index to the x-axis values (like 'Month') helps pandas plot the data correctly.

You can customize many other parts of the plot using matplotlib if needed.

Summary

Use title to add a clear heading to your plot.

Use xlabel and ylabel to name the axes.

Use figsize to control the size of your plot for better visibility.

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