Why axis formatting matters in Matplotlib - Challenge Your Understanding

Challenge - 5 Problems

❓ visualization

intermediate

Identify the effect of axis formatting on a plot

Look at the following code that plots a simple line chart. Which option shows the plot with the x-axis labels formatted as dates?

Matplotlib

import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from datetime import datetime, timedelta

dates = [datetime(2024, 1, 1) + timedelta(days=i) for i in range(5)]
values = [10, 15, 7, 12, 9]

fig, ax = plt.subplots()
ax.plot(dates, values)

# Axis formatting missing here

plt.show()

A ax.yaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))

B ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))

C ax.xaxis.set_major_formatter(plt.FuncFormatter(lambda x, _: f'{x:.2f}'))

D ax.xaxis.set_major_locator(plt.MaxNLocator(integer=True))

💡 Hint

Think about which axis shows dates and how to format them properly.

Option B correctly formats the x-axis labels as dates using mdates.DateFormatter. Option B formats numbers with decimals, not dates. Option B tries to format the y-axis as dates, which is incorrect. Option B changes tick locations but does not format dates.

❓ Predict Output

intermediate

What is the output of this axis formatting code?

What will be the output of the following code snippet?

Matplotlib

import matplotlib.pyplot as plt
import numpy as np

fig, ax = plt.subplots()
ax.plot(np.arange(5), np.arange(5)**2)
ax.set_xticks([0, 1, 2, 3, 4])
ax.set_xticklabels(['zero', 'one', 'two', 'three', 'four'])
labels = [label.get_text() for label in ax.get_xticklabels()]
print(labels)

A ['zero', 'one', 'two', 'three', 'four']

B ['0', '1', '2', '3', '4']

C ['zero', 'one', 'two', 'three', 'four', '']

D ['zero', 'one', 'two', 'three']

💡 Hint

Check how many labels are set and what get_xticklabels() returns.

The code sets 5 custom labels for the x-axis ticks. The get_xticklabels() method returns all labels including the empty last one by default, but since we set exactly 5 labels, the printed list matches those labels exactly.

❓ data_output

advanced

How many ticks are shown after axis formatting?

Given this code, how many ticks will be visible on the y-axis?

Matplotlib

import matplotlib.pyplot as plt
import numpy as np

fig, ax = plt.subplots()
ax.plot(np.arange(10), np.random.rand(10))
ax.yaxis.set_major_locator(plt.MaxNLocator(4))
ticks = ax.get_yticks()
print(len(ticks))

A 5

B 10

C Cannot determine without plotting

D 4

💡 Hint

Remember that MaxNLocator(4) tries to show up to 4 intervals, which means 5 ticks.

The MaxNLocator(4) sets a maximum of 4 intervals between ticks, so the number of ticks is intervals + 1, which is 5.

🔧 Debug

advanced

Why does this axis formatting code raise an error?

Consider this code snippet:

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.plot([1, 2, 3], [4, 5, 6])
ax.xaxis.set_major_formatter('%Y-%m-%d')
plt.show()

Why does it raise an error?

A Because plt.show() is missing parentheses

B Because the plot data is not dates

C Because set_major_formatter expects a Formatter object, not a string

D Because the x-axis has no ticks

💡 Hint

Check the type of argument set_major_formatter requires.

The method set_major_formatter requires a Formatter object like DateFormatter, not a plain string. Passing a string causes a TypeError.

🚀 Application

expert

Choose the correct axis formatting to display large numbers in millions

You have a plot with y-axis values in the millions (e.g., 1,000,000). Which axis formatter will display the y-axis labels as '1M', '2M', etc.?

Matplotlib

import matplotlib.pyplot as plt
import matplotlib.ticker as ticker

fig, ax = plt.subplots()
ax.plot([1, 2, 3], [1000000, 2000000, 3000000])

# Apply correct formatter here

plt.show()

A ax.yaxis.set_major_formatter(ticker.FormatStrFormatter('%.2f'))

B ax.yaxis.set_major_formatter(ticker.PercentFormatter())

C ax.yaxis.set_major_formatter(ticker.ScalarFormatter())

D ax.yaxis.set_major_formatter(ticker.FuncFormatter(lambda x, _: f'{int(x/1e6)}M'))

💡 Hint

Think about how to convert large numbers to a shorter string with 'M' suffix.

Option D uses a custom function to divide the number by 1 million and add 'M' suffix, which correctly formats large numbers. Option D formats as percentages, which is incorrect. Option D shows raw numbers without suffix. Option D formats as float numbers without suffix.