# Change Size of Figures in Matplotlib

Matplotlib is a handy visualization library in python that offers a number of plotting options and customizations. It may happen that at times you’d want to change the size of the plots as per your needs. In this tutorial, we’ll look at how to change the size of figures plotted with matplotlib.

To have the plots of a specific size in matplotlib, you can pass the figure size to the `figsize` parameter of matplotlib pyplot’s `figure()` function or specify the default figure size via `rcParams`. The following is the syntax:

``````import matplotlib.pyplot as plt
plt.figure(figsize=(width,height))``````

Here, we pass the desired dimensions of the plot as a `(width,height)` tuple to `figsize`. Note that the width and height should be in inches. So if you want your plot to be 8 inches wide and 6 inches high, pass (8,6) to `figsize`. The default size of a plot in matplotlib is `(6.4,4.8)`

Let’s look at some examples of changing the figure size in maplotlib:

First, let’s plot a simple line chart with maplotlib without explicitly setting the figure size. Here’s a line chart showing the employee count growth at a company over the last few years:

Highlighted programs for you

Flatiron School

Flatiron School

Data Science Bootcamp
Product Design UX/UI Bootcamp

University of Maryland Global Campus

University of Maryland Global Campus

Cloud Computing Systems Master's
Digital Forensics & Cyber Investigation Master's

Creighton University

Creighton University

Health Informatics Master's

``````import matplotlib.pyplot as plt

# number of employees of ABC
emp_count = [3, 20, 50, 200, 350, 400]
year = [2014, 2015, 2016, 2017, 2018, 2019]

# plot a line chart
plt.plot(year, emp_count)
plt.xlabel("Year")
plt.ylabel("Count")
plt.title("Employee count at ABC")
plt.show()``````

Output:

This is the default figure size we get on plotting with matplotlib. Now let’s make this plot bigger.

``````# change the figure size
plt.figure(figsize=(8,6))

# plot a line chart
plt.plot(year, emp_count)
plt.xlabel("Year")
plt.ylabel("Count")
plt.title("Employee count at ABC")
plt.show()``````

Output:

For the above plot, we first set the `figsize` to `(8,6)` and then proceeded to plot the line chart. You can see that this figure is indeed larger than the previous one. Let’s see what happens if we attempt to plot the same figure without setting the figsize again.

``````# plot a line chart
plt.plot(year, emp_count)
plt.xlabel("Year")
plt.ylabel("Count")
plt.title("Employee count at ABC")
plt.show()``````

Output:

Here we get the plot with the default figure size, smaller than the one we got in the above example where we specified the size. This means that you’ll have to specify the figsize each time you want a plot (with a size other than default) using this method.

Let’s say your working in a Jupyter Notebook and want to set a default figsize without having to specify it each time you plot. For this, use `rcParams` which is used for handling default Matplotlib values.

``````plt.rcParams['figure.figsize'] = [10, 8]

# plot a line chart
plt.plot(year, emp_count)
plt.xlabel("Year")
plt.ylabel("Count")
plt.title("Employee count at ABC")
plt.show()``````

Output:

The size configuration set with `rcParams` remains consistent for other plots as well. For instance, if you plot a bar chart of the same values without setting the figure size:

``````# plot a bar chart
plt.bar(year, emp_count)
plt.xlabel("Year")
plt.ylabel("Employees")
plt.title("Employee count at ABC")
plt.show()``````

Output:

The resulting bar chart retains the figure size settings specified with `rcParams` in the previous example.

With this, we come to the end of this tutorial. The code examples and results presented in this tutorial have been implemented in a Jupyter Notebook with a python (version 3.8.3) kernel having matplotlib version 3.2.2

• 