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How to change the figure size with subplots in Matplotlib in Python

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by Dejaswarooba dot icon Updated: May 8, 2023

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Matplotlib is a popular Python toolkit for creating high-quality visualizations and plots. It depends on the NumPy library and works well with other libraries. Matplotlib offers various customization options. We can do it by allowing users to produce plots ranging from simple lines to scatter plots. Also, you can produce several plots of complicated heat maps, contour plots, and 3D graphs. 


When creating a new figure in Matplotlib, you can use the figsize parameter or attribute. It will change the size of the figure. Matplotlib's figures are 6.4 x 4.8 inches by default. If you need to change the size or width of a plot or many plots in a subplot grid, you can use the figsize option. The figsize argument accepts a tuple of the plot's width and height in inches. It will alter to meet your exact plot size requirements. You can also change the size of a given plot by navigating to its axis object. It will then change the figsize attribute. 


The options available are the aspect ratio, layouts, size, grid lines, tick labels, and width. It will help in altering the size of the figure. Matplotlib also allows many axes and custom axes. It will let you change the scaling of the default axes. Then you can use tight_layout to change the spacing between the axes. You may change the size of a new figure by using the figsize attribute or parameter of the figure object. 

Changing the figure size with subplots in Matplotlib in Python? 

The subplots() function generates a subplot grid and accepts several options. We can use it to alter the arrangement and look of the subplots. To adjust the size of a subplot's figure, use the figsize parameter of the subplots() function. The figsize argument specifies the figure's size. It accepts a tuple of two values reflecting the figure's width and height in inches. 


Preview of the output obtained when the below code is executed

Code

Matplotlib - Plot size, how to adjust the size?

PythondotLines of Code : 23dotLicense : Strong Copyleft (CC BY-SA 4.0)

Dependent Libraries : 
ax1 = plt.subplot2grid((4,3), (0,0),)

ax1 = plt.subplot2grid((2,2), (0,0),)

import numpy as np
import matplotlib.pyplot as plt

data = np.random.randn(25)

fig = plt.figure(figsize=(7,7))

ax1 = plt.subplot2grid((2,2), (0,0),)
ax2 = plt.subplot2grid((2,2), (1,0),)
ax3 = plt.subplot2grid((2,2), (0,1),)
ax4 = plt.subplot2grid((2,2), (1,1),)

ax1.plot(data)
ax2.plot(data)
ax3.plot(data)
ax4.plot(data)

plt.show()

Follow the steps carefully to get the output easily.

  • Install Visual Studio Code in your computer.
  • Install the required library by using the following command -

pip install matplotlib

pip install numpy


  • If your system is not reflecting the installation, try running the above command by opening windows powershell as administrator.
  • Open the folder in the code editor, copy and paste the above kandi code snippet in the python file.
  • Remove the first two lines of the code.
  • Run the code using the run command.


I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.


I found this code snippet by searching for "figsize matplotlib" in kandi. You can try any such use case!

Dependent Libraries

numpyby numpy

Python doticonstar image 23755 doticonVersion:v1.25.0rc1doticon
License: Permissive (BSD-3-Clause)

The fundamental package for scientific computing with Python.

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            numpyby numpy

            Python doticon star image 23755 doticonVersion:v1.25.0rc1doticon License: Permissive (BSD-3-Clause)

            The fundamental package for scientific computing with Python.
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                  License
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                      matplotlibby matplotlib

                      Python doticonstar image 17559 doticonVersion:v3.7.1doticon
                      no licences License: No License (null)

                      matplotlib: plotting with Python

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                                matplotlibby matplotlib

                                Python doticon star image 17559 doticonVersion:v3.7.1doticonno licences License: No License

                                matplotlib: plotting with Python
                                Support
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                                          If you do not have matplotlib that is required to run this code, you can install it by clicking on the above link and copying the pip Install command from the page in kandi.


                                          You can search for any dependent library on kandi like matplotlib.

                                          FAQ

                                          What is the figure size when creating a matplotlib figure with subplots? 

                                          When constructing a figure, we can determine the size by the subplots and their aspect ratio. Matplotlib attempts to fit the subplots into the available area. It will be retaining its aspect ratios by default. If we don't specify the figure size, the generated figure may not have the correct size and aspect ratio. But you can change the figure's size by using the figsize option. It will let you specify the figure width and height in inches. 


                                          How can I use the figsize parameter to control the plot size of a matplotlib subplot grid? 

                                          We can use the figsize parameter to control the entire figure size, like the subplot grid. It accepts a tuple of two values representing the figure's width and height in inches. You can change the size of the figure and the subplot grid by adjusting the figsize option. 


                                          Are there any limitations to what values I can use for the figsize parameter in matplot lib? 

                                          Matplotlib has no restrictions on the values we can use for the figsize parameter. It is critical to ensure a clear and pleasing plot. It is crucial to select appropriate parameters for the size and aspect ratio. The large or small values may be incompatible with the display or print capabilities. Select acceptable values for the use case and the display or print possibilities. 


                                          How does changing the figsize parameter affect axes' scales in a matplotlib graph? 

                                          Changing the figsize parameter does not affect the scaling of the graph's axes. The figsize parameter only affects the size of the figure. It can affect the arrangement and presentation of the graph. But size changes can affect the axes' scales depending on how the figure resizes. For example, if we used the figsize parameter to shrink the figure, the axes would also shrink. This can make the data on the graph more compressed. We can do it by compressing the scales and the appearance. 


                                          What are tips for getting the most out of my figure object when using subplots, figsize? 

                                          To avoid overlapping text or labels, use the tight_layout() function. It will alter the layout of subplots. This is very beneficial when working with many subplots or a complex arrangement. Experiment with several aspect ratios to find the best for your data. You can set the aspect parameter of each subplot to "equal". It will help ensure that all subplots have the same aspect ratio. To ensure that many subplots share the same x or y axis, use the sharex and sharey options. This can help to verify that we can align the data across all subplots. 

                                          Environment tested

                                          1. This code had been tested using python version 3.8.0
                                          2. matplotlib version 3.7.1 has been used.
                                          3. numpy version 1.24.2 has been used.

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