Multiple time series comparison in Matplotlib - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the main purpose of comparing multiple time series in data science?

To observe and analyze how different variables change over time relative to each other, helping identify patterns, correlations, or differences.

beginner

Which matplotlib function is commonly used to plot multiple time series on the same graph?

The plt.plot() function can be called multiple times or with multiple series to plot several time series on the same axes.

beginner

Why is it important to use a legend when plotting multiple time series?

A legend helps identify which line corresponds to which time series, making the graph easier to understand.

intermediate

How can you improve readability when multiple time series have very different scales?

You can use separate y-axes (twin axes) or normalize the data so all series fit well on the same scale.

beginner

What does overlapping multiple time series on one plot help you discover?

It helps discover relationships like trends, seasonal patterns, or anomalies that occur at the same time across series.

Which matplotlib function is used to add a legend to a plot?

A plt.grid()

B plt.title()

C plt.xlabel()

D plt.legend()

The plt.legend() function adds a legend to the plot, showing labels for each line.

What is a good way to handle multiple time series with very different value ranges?

A Normalize or use separate y-axes

B Plot them all on the same y-axis without changes

C Use different colors but same scale

D Plot only one series

Normalizing or using separate y-axes helps visualize series with different scales clearly.

What does overlapping multiple time series on one plot help identify?

A Only the maximum value of each series

B Relationships and patterns across series

C The average of all series combined

D The number of data points

Overlapping time series helps identify relationships, trends, and patterns across the series.

Which of these is NOT a good practice when plotting multiple time series?

A Using different colors for each series

B Adding a legend to identify series

C Plotting all series without labels

D Labeling axes clearly

Plotting without labels makes it hard to understand which line represents which series.

In matplotlib, how do you plot two time series stored in lists x and y1, y2 on the same graph?

A plt.plot(x, y1); plt.plot(x, y2)

B plt.plot(y1, y2)

C plt.scatter(x, y1, y2)

D plt.bar(x, y1, y2)

Calling plt.plot() twice with the same x and different y values plots both series on the same graph.

Explain how you would plot and compare two time series using matplotlib. Include how to make the plot clear and easy to understand.

Think about how to show both series clearly on one graph.

Describe methods to handle multiple time series with very different scales when plotting them together.

Consider how to make all series visible and comparable.

Practice

1. What is the main purpose of plotting multiple time series on the same graph using matplotlib?

easy

A. To make the graph load faster

B. To create separate graphs for each time series

C. To hide the data labels for clarity

D. To visually compare trends and differences between series over time

Solution

1. Step 1: Understand the purpose of multiple time series plots

   Plotting multiple lines on one graph helps us see how different series change over time side by side.

2. Step 2: Compare options with this purpose

   Only To visually compare trends and differences between series over time describes this visual comparison goal correctly.

3. Final Answer:

   To visually compare trends and differences between series over time -> Option D

4. Quick Check:

   Multiple time series comparison = Visual comparison [OK]

Hint: Multiple lines on one plot show trends side by side [OK]

Common Mistakes:

• Thinking multiple plots are created instead of one combined plot
• Ignoring the importance of labels and legends
• Believing it speeds up graph loading

2. Which of the following matplotlib code snippets correctly plots two time series series1 and series2 on the same graph with labels?

easy

A. plt.plot(series1, label='Series 1')
plt.legend()
plt.show()

B. plt.plot(series1)
plt.plot(series2)
plt.show()

C. plt.plot(series1, label='Series 1')
plt.plot(series2, label='Series 2')
plt.legend()
plt.show()

D. plt.plot(series1, label='Series 1')
plt.plot(series2, label='Series 2')
plt.show()

Solution

1. Step 1: Check for plotting both series with labels

   plt.plot(series1, label='Series 1') plt.plot(series2, label='Series 2') plt.legend() plt.show() plots both series and adds labels for each.

2. Step 2: Verify legend call to show labels

   plt.plot(series1, label='Series 1') plt.plot(series2, label='Series 2') plt.legend() plt.show() calls plt.legend() to display labels on the graph.

3. Final Answer:

   Code that plots both series with labels and shows legend -> Option C

4. Quick Check:

   Plot both + labels + legend = plt.plot(series1, label='Series 1') plt.plot(series2, label='Series 2') plt.legend() plt.show() [OK]

Hint: Always add labels and call plt.legend() to show them [OK]

Common Mistakes:

• Forgetting to call plt.legend() so labels don't appear
• Plotting only one series instead of both
• Not adding labels to each series

3. What will be the output of this code snippet?

import matplotlib.pyplot as plt
series1 = [1, 3, 2, 4]
series2 = [2, 1, 3, 5]
plt.plot(series1, label='A')
plt.plot(series2, label='B')
plt.legend()
plt.show()

medium

A. A graph with two lines labeled 'A' and 'B' showing series1 and series2

B. A graph with one line showing the sum of series1 and series2

C. A graph with two lines but no labels

D. SyntaxError due to missing import

Solution

1. Step 1: Analyze the plotting commands

   Two lines are plotted: series1 with label 'A' and series2 with label 'B'.

2. Step 2: Check legend and show calls

   Calling plt.legend() displays the labels on the graph.

3. Final Answer:

   A graph with two lines labeled 'A' and 'B' showing series1 and series2 -> Option A

4. Quick Check:

   Two labeled lines plotted = A graph with two lines labeled 'A' and 'B' showing series1 and series2 [OK]

Hint: Labels appear only if plt.legend() is called [OK]

Common Mistakes:

• Thinking lines are summed instead of plotted separately
• Forgetting plt.legend() hides labels
• Assuming syntax error without import

4. The following code is intended to plot two time series with labels, but the legend does not appear. What is the error?

import matplotlib.pyplot as plt
series1 = [1, 2, 3]
series2 = [3, 2, 1]
plt.plot(series1, label='First')
plt.plot(series2, label='Second')
plt.show()

medium

A. Missing plt.legend() call to display the legend

B. Labels are incorrectly assigned inside plt.plot()

C. plt.show() should be called before plotting

D. series2 should be plotted before series1

Solution

1. Step 1: Check for legend display code

   The code does not call plt.legend(), so labels won't show.

2. Step 2: Confirm label usage is correct

   Labels are correctly passed in plt.plot(), so no issue there.

3. Final Answer:

   Missing plt.legend() call to display the legend -> Option A

4. Quick Check:

   Legend missing without plt.legend() [OK]

Hint: Always add plt.legend() to show labels on plot [OK]

Common Mistakes:

• Assuming labels show automatically without legend call
• Thinking order of plotting affects legend display
• Calling plt.show() too early

5. You have three time series with different lengths:
series1 = [1, 2, 3, 4], series2 = [2, 3, 4], series3 = [1, 3, 5, 7, 9].
How can you correctly plot all three on the same graph to compare them over time?

hard

A. Plot all series using the length of the longest series only

B. Plot each series with its own x-axis range matching its length, then add labels and legend

C. Pad shorter series with zeros to match the longest series length before plotting

D. Plot only the shortest series to avoid errors

Solution

1. Step 1: Understand different lengths require matching x-axis

   Each series must be plotted with x values matching its length to avoid misalignment.

2. Step 2: Plot each series with its own x range and add labels

   Use range(len(series)) for x-axis, plot all, then add labels and legend.

3. Final Answer:

   Plot each series with its own x-axis range matching its length, then add labels and legend -> Option B

4. Quick Check:

   Match x-axis length per series + labels = Plot each series with its own x-axis range matching its length, then add labels and legend [OK]

Hint: Use range(len(series)) for x-axis of each series [OK]

Common Mistakes:

• Plotting all series without adjusting x-axis causes misaligned lines
• Padding with zeros changes data meaning
• Ignoring series length differences