Multiple time series comparison in Matplotlib

Introduction

We compare multiple time series to see how different things change over time together. This helps us find patterns or differences easily.

Comparing sales of different products over months to see which sells better.

Tracking temperature changes in different cities over days to find weather trends.

Monitoring stock prices of several companies to spot market movements.

Observing website visits from different sources over weeks to understand traffic.

Syntax

Matplotlib

import matplotlib.pyplot as plt

plt.plot(time1, series1, label='Series 1')
plt.plot(time2, series2, label='Series 2')
plt.xlabel('Time')
plt.ylabel('Value')
plt.title('Multiple Time Series Comparison')
plt.legend()
plt.show()

Use plt.plot() multiple times to add each time series to the same chart.

Add label to each series for the legend to identify them.

Examples

Two simple series with the same time points are plotted and labeled.

Matplotlib

plt.plot([1, 2, 3], [10, 20, 30], label='Series A')
plt.plot([1, 2, 3], [15, 25, 35], label='Series B')
plt.legend()
plt.show()

Plotting sales data for two products over the same dates with axis labels and title.

Matplotlib

plt.plot(dates, sales_product1, label='Product 1')
plt.plot(dates, sales_product2, label='Product 2')
plt.xlabel('Date')
plt.ylabel('Sales')
plt.title('Sales Comparison')
plt.legend()
plt.show()

Sample Program

This code plots two time series with dates on the x-axis and values on the y-axis. Markers help distinguish points. The legend shows which line is which.

Matplotlib

import matplotlib.pyplot as plt
import pandas as pd

# Create sample dates
dates = pd.date_range(start='2024-01-01', periods=5, freq='D')

# Sample data for two time series
series1 = [100, 120, 130, 115, 140]
series2 = [90, 110, 125, 130, 135]

# Plot both series
plt.plot(dates, series1, marker='o', label='Series 1')
plt.plot(dates, series2, marker='s', label='Series 2')

# Add labels and title
plt.xlabel('Date')
plt.ylabel('Value')
plt.title('Multiple Time Series Comparison')
plt.legend()
plt.grid(True)
plt.tight_layout()
plt.show()

Important Notes

Make sure time points align or are comparable for meaningful comparison.

Use different colors or markers to clearly see each series.

Adding grid lines helps read values better.

Summary

Plot multiple time series on the same chart using plt.plot() repeatedly.

Label each series for clarity with label and show legend.

Use axis labels and titles to explain what the chart shows.

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