Dates on x-axis in Matplotlib - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of this matplotlib date plot code?

Consider the following Python code that plots dates on the x-axis using matplotlib. What will be the format of the x-axis labels shown in the plot?

Matplotlib

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

dates = [datetime(2024, 1, 1), datetime(2024, 1, 2), datetime(2024, 1, 3)]
values = [10, 20, 15]

fig, ax = plt.subplots()
ax.plot(dates, values)
ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
plt.show()

A Dates formatted as 'YYYY-MM-DD', e.g., '2024-01-01', '2024-01-02', '2024-01-03'

B Dates formatted as 'MM/DD/YYYY', e.g., '01/01/2024', '01/02/2024', '01/03/2024'

C Dates formatted as 'Day Month Year', e.g., '1 Jan 2024', '2 Jan 2024', '3 Jan 2024'

D Dates shown as integers representing days since 1970-01-01

💡 Hint

Look at the format string passed to DateFormatter.

The DateFormatter is set with the format '%Y-%m-%d', which means year-month-day with four-digit year, two-digit month, and two-digit day separated by dashes.

❓ data_output

intermediate

How many major ticks appear on the x-axis?

Given this code that plots data with dates on the x-axis, how many major ticks will appear on the x-axis?

Matplotlib

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

dates = [datetime(2024, 5, 1), datetime(2024, 5, 2), datetime(2024, 5, 3), datetime(2024, 5, 4), datetime(2024, 5, 5)]
values = [5, 3, 6, 2, 7]

fig, ax = plt.subplots()
ax.plot(dates, values)
ax.xaxis.set_major_locator(mdates.DayLocator(interval=2))
plt.show()

A 3 major ticks

B 5 major ticks

C 2 major ticks

D 1 major tick

💡 Hint

Check the interval set in DayLocator and the date range.

DayLocator with interval=2 places a major tick every 2 days starting from the first date. For 5 days, ticks appear on day 1, 3, and 5, totaling 3 ticks.

❓ visualization

advanced

Which plot shows correctly formatted monthly ticks on the x-axis?

You want to plot data with monthly ticks labeled as abbreviated month names (e.g., Jan, Feb). Which code snippet produces this correctly formatted x-axis?

A

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

B

ax.xaxis.set_major_locator(mdates.WeekdayLocator())
ax.xaxis.set_major_formatter(mdates.DateFormatter('%b'))

C

ax.xaxis.set_major_locator(mdates.DayLocator())
ax.xaxis.set_major_formatter(mdates.DateFormatter('%b'))

D

ax.xaxis.set_major_locator(mdates.MonthLocator())
ax.xaxis.set_major_formatter(mdates.DateFormatter('%b'))

💡 Hint

MonthLocator controls tick positions by month, DateFormatter controls label format.

MonthLocator places ticks at the start of each month. DateFormatter with '%b' formats labels as abbreviated month names like 'Jan', 'Feb'.

🔧 Debug

advanced

What error does this code raise when plotting dates?

This code attempts to plot dates on the x-axis but raises an error. What is the error type?

Matplotlib

import matplotlib.pyplot as plt
from datetime import datetime

dates = ['2024-01-01', '2024-01-02', '2024-01-03']
values = [1, 2, 3]

plt.plot(dates, values)
plt.show()

A TypeError: float() argument must be a string or a number, not 'datetime.date'

B No error, plot displays correctly

C ValueError: could not convert string to float: '2024-01-01'

D AttributeError: 'str' object has no attribute 'toordinal'

💡 Hint

Matplotlib expects datetime objects or numbers, not date strings.

Matplotlib cannot convert date strings directly to floats for plotting, causing a ValueError.

🚀 Application

expert

What is the value of 'num_ticks' after running this code?

This code sets up a plot with dates on the x-axis and custom tick intervals. What is the number of major ticks on the x-axis after running?

Matplotlib

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

start = datetime(2024, 1, 1)
end = datetime(2024, 3, 1)

fig, ax = plt.subplots()
ax.set_xlim(start, end)
ax.xaxis.set_major_locator(mdates.MonthLocator(bymonthday=15))

# Count major ticks
num_ticks = len(ax.get_xticks())
plt.close(fig)

A 1

B 2

C 3

D 0

💡 Hint

MonthLocator with bymonthday=15 places ticks on the 15th of each month within limits.

Between 2024-01-01 and 2024-03-01, the 15th of January and 15th of February fall inside the range, so 2 ticks appear.

Practice

1. What is the main reason to use datetime objects on the x-axis in matplotlib plots?

easy

A. To display dates properly and allow date-specific formatting

B. To speed up the plotting process

C. To change the color of the plot lines

D. To add grid lines automatically

Solution

1. Step 1: Understand the role of datetime objects

   Datetime objects represent dates and times in Python, allowing matplotlib to recognize and format them correctly on the x-axis.

2. Step 2: Identify the benefit for plotting

   Using datetime objects enables proper date formatting, such as showing months, days, or years, and helps in handling date ticks automatically.

3. Final Answer:

   To display dates properly and allow date-specific formatting -> Option A

4. Quick Check:

   Datetime objects = Proper date display [OK]

Hint: Use datetime objects to get correct date formatting on x-axis [OK]

Common Mistakes:

• Using strings instead of datetime objects for dates
• Expecting automatic color changes from datetime
• Confusing grid lines with date formatting

2. Which of the following is the correct way to import the module used for date formatting in matplotlib?

easy

A. import matplotlib.date as mdate

B. import matplotlib.dates as mdates

C. import matplotlib.datetime as mdates

D. import matplotlib.dateformatter as mdates

Solution

1. Step 1: Recall the correct module name

   The correct module for date formatting in matplotlib is called dates, not date or datetime.

2. Step 2: Match the import alias

   Common practice is to import it as mdates for convenience.

3. Final Answer:

   import matplotlib.dates as mdates -> Option B

4. Quick Check:

   matplotlib.dates = mdates [OK]

Hint: Remember: 'dates' plural, alias 'mdates' [OK]

Common Mistakes:

• Using singular 'date' instead of 'dates'
• Confusing datetime module with matplotlib.dates
• Using wrong alias causing import errors

3. What will the following code output?

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

dates = [datetime(2024, 1, 1), datetime(2024, 1, 2), datetime(2024, 1, 3)]
values = [10, 20, 15]

plt.plot(dates, values)
plt.gcf().autofmt_xdate()
plt.show()

medium

A. A line plot with dates on x-axis formatted and rotated for readability

B. A line plot with numeric x-axis values instead of dates

C. An error because dates are not converted to strings

D. A scatter plot with dates on y-axis

Solution

1. Step 1: Understand the plot function with datetime

   The plt.plot function accepts datetime objects on the x-axis and plots the corresponding values.

2. Step 2: Effect of autofmt_xdate()

   This function rotates and formats the date labels on the x-axis to prevent overlap and improve readability.

3. Final Answer:

   A line plot with dates on x-axis formatted and rotated for readability -> Option A

4. Quick Check:

   autofmt_xdate() rotates date labels [OK]

Hint: Use autofmt_xdate() to rotate date labels automatically [OK]

Common Mistakes:

• Expecting string conversion of dates automatically
• Confusing plot type with scatter
• Ignoring the effect of autofmt_xdate()

4. Identify the error in this code snippet that tries to plot dates on the x-axis:

import matplotlib.pyplot as plt
from datetime import datetime

dates = ['2024-01-01', '2024-01-02', '2024-01-03']
values = [5, 10, 15]

plt.plot(dates, values)
plt.show()

medium

A. plt.plot cannot plot lists

B. Values list length does not match dates list length

C. Missing import for matplotlib.dates module

D. Dates are strings, not datetime objects, causing incorrect x-axis formatting

Solution

1. Step 1: Check the type of dates list

   The dates are given as strings, which matplotlib does not automatically convert to dates for axis formatting.

2. Step 2: Understand the impact on plotting

   Using strings causes matplotlib to treat them as categorical labels, not dates, so date formatting and scaling won't work properly.

3. Final Answer:

   Dates are strings, not datetime objects, causing incorrect x-axis formatting -> Option D

4. Quick Check:

   Use datetime objects, not strings for dates [OK]

Hint: Convert date strings to datetime objects before plotting [OK]

Common Mistakes:

• Using strings directly for dates
• Assuming matplotlib auto-converts strings to dates
• Ignoring the need for datetime conversion

5. You want to plot daily sales data for January 2024 with dates on the x-axis. You have a list of date strings and sales numbers. Which code snippet correctly converts the dates and formats the x-axis for clear display?

dates = ['2024-01-01', '2024-01-02', '2024-01-03']
sales = [100, 150, 120]

hard

A. from datetime import datetime
plt.plot([datetime(d) for d in dates], sales)
plt.show()

B. import matplotlib.pyplot as plt
plt.plot(dates, sales)
plt.xticks(rotation=45)
plt.show()

C. from datetime import datetime
import matplotlib.pyplot as plt
import matplotlib.dates as mdates

converted_dates = [datetime.strptime(d, '%Y-%m-%d') for d in dates]
plt.plot(converted_dates, sales)
plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%b %d'))
plt.gcf().autofmt_xdate()
plt.show()

D. import matplotlib.dates as mdates
plt.plot(dates, sales)
plt.gca().xaxis.set_major_locator(mdates.DayLocator())
plt.show()

Solution

1. Step 1: Convert date strings to datetime objects

   Use datetime.strptime with the correct format to convert each string to a datetime object.

2. Step 2: Format x-axis dates and rotate labels

   Use mdates.DateFormatter to set a readable date format and autofmt_xdate() to rotate labels for clarity.

3. Final Answer:

   The code snippet that correctly converts dates and formats x-axis -> Option C

4. Quick Check:

   Convert dates + format + rotate labels = from datetime import datetime import matplotlib.pyplot as plt import matplotlib.dates as mdates converted_dates = [datetime.strptime(d, '%Y-%m-%d') for d in dates] plt.plot(converted_dates, sales) plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%b %d')) plt.gcf().autofmt_xdate() plt.show() [OK]

Hint: Convert strings with strptime, format with DateFormatter, rotate labels [OK]

Common Mistakes:

• Plotting strings without conversion
• Using datetime(d) instead of strptime
• Forgetting to rotate date labels