How to Show Multiple Charts In Matplotlib

8 minutes read

To show multiple charts in Matplotlib, you can use the subplot() function to create a grid of subplots within a single figure. This function takes three arguments: the number of rows, the number of columns, and the index of the subplot you want to create.


For example, if you want to create a 2x2 grid of subplots, you can use the following code:

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plt.subplot(2, 2, 1)
plt.plot(x1, y1)

plt.subplot(2, 2, 2)
plt.plot(x2, y2)

plt.subplot(2, 2, 3)
plt.plot(x3, y3)

plt.subplot(2, 2, 4)
plt.plot(x4, y4)

plt.show()


This code will create a 2x2 grid of subplots with a different chart in each subplot. You can customize the size and layout of the subplots by adjusting the arguments passed to the subplot() function.

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How to share axes between multiple charts in matplotlib?

To share axes between multiple charts in matplotlib, you can use the sharex and sharey parameters when creating the subplots. Here's an example:

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import matplotlib.pyplot as plt

# Create the first subplot
fig, axs = plt.subplots(2, 1, sharex=True, sharey=True)
ax1 = axs[0]
ax2 = axs[1]

# Plot on the first subplot
ax1.plot([1, 2, 3], [4, 5, 6])

# Plot on the second subplot
ax2.plot([1, 2, 3], [6, 5, 4])

plt.show()


In this example, we create two subplots with the sharex=True and sharey=True parameters, which makes the x-axis and y-axis shared between the two subplots. This ensures that the axes of the two subplots are synchronized and have the same scale.


How to plot multiple charts with shared x-axis in matplotlib?

You can plot multiple charts with a shared x-axis in matplotlib by using the subplots() function to create a figure with multiple axes, and then specifying sharex=True when creating the axes. This will ensure that all the subplots share the same x-axis.


Here is an example code snippet:

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import matplotlib.pyplot as plt

# Create a figure and a set of subplots
fig, axs = plt.subplots(2, 1, sharex=True)

# Plot data on the first subplot
axs[0].plot([1, 2, 3, 4], [10, 20, 15, 25])
axs[0].set_title('First Subplot')

# Plot data on the second subplot
axs[1].plot([1, 2, 3, 4], [5, 10, 15, 20])
axs[1].set_title('Second Subplot')

# Set common x-axis label
fig.text(0.5, 0.04, 'X-axis', ha='center')

plt.show()


In this code, plt.subplots(2, 1, sharex=True) creates a figure with 2 subplots stacked vertically, and the sharex=True parameter ensures that both subplots share the same x-axis. You can then plot your data on each subplot as needed and customize the appearance of the plots.


What is the function of the subplot() method in matplotlib?

The subplot() method in matplotlib allows you to create multiple plots in a single figure. It takes in three arguments - the number of rows, the number of columns, and the plot number. By specifying these arguments, you can create subplots within a single figure, allowing you to compare different plots or data visualizations side by side. This method is particularly useful for creating complex and informative data visualizations.

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