How to Draw a Rectangle in a Matplotlib Plot?

In this tutorial, we’ll try to understand how to draw a rectangle in matplotlib with the help of some examples.

We can directly use matplotlib.patches.Rectangle class to draw a rectangle in matplotlib.

Basic Syntax:

matplotlib.patches.Rectangle(xy, width, height, *, angle=0.0, rotation_point='xy', **kwargs)

Parameters:

• xy: Lower left point to start the rectangle plotting
• width: width of the rectangle
• height: Height of the rectangle
• angle: Angle of rotation of the rectangle

For more parameters, refer to this.

Examples

Now, let us try to understand the above method using worked-out examples.

Example 1 – Drawing a simple Rectangle in Matplotlib

import matplotlib
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111)
rect = matplotlib.patches.Rectangle((0, 50),50, 100)
ax.add_patch(rect)
plt.xlim(-10,75)
plt.ylim(-10,175)
plt.show()

Output:

In the above example, we –

1. First, imported the required modules.
2. Then, generated a pyplot figure and added a subplot.
3. Then, we created a rectangle with the bottom left coordinate of the rectangle to be (0,50), with width as 50 and height as 100.
4. Then, we added the created rectangle to the axes using the add_patch method.
5. Then, we adjusted the x and y limits of the axes and plotted the figure.

Example 2 – Drawing a rotated Rectangle in Matplotlib

import matplotlib
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111)
rect = matplotlib.patches.Rectangle((0, 50),50, 100,angle=30)
ax.add_patch(rect)
plt.xlim(-100,100)
plt.ylim(-100,200)
plt.show()

Output:

In the above example, we –

1. First, imported the required modules.
2. Then, generated a pyplot figure and added a subplot.
3. Then, we created a rectangle with the bottom left coordinate of the rectangle to be (0,50), with width as 50 and height as 100, and rotated by an angle of 30 degrees.
4. Then, we added the created rectangle to the axes using the add_patch method.
5. Then, we adjusted the x and y limits of the axes and plotted the figure.

Example 3 – Styling a Rectangle in Matplotlib

import matplotlib
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111)
rect = matplotlib.patches.Rectangle((0, 50),50, 100,facecolor='blue',edgecolor='pink', lw = 10)
ax.add_patch(rect)
plt.xlim(-100,100)
plt.ylim(-100,200)
plt.show()

Output:

In the above example, we –

1. First, imported the required modules.
2. Then, generated a pyplot figure and added a subplot.
3. Then, we created a rectangle with the bottom left coordinate of the rectangle to be (0,50), with width as 50 and height as 100, and changed the color of the rectangle to blue and edge color to pink, and the edge width to 10.
4. Then, we added the created rectangle to the axes using the add_patch method.
5. Then, we adjusted the x and y limits of the axes and plotted the figure.

Example 4 – Styling a Rectangle By adjusting transparency

import matplotlib
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111)
rect = matplotlib.patches.Rectangle((0, 50),50, 100,facecolor='red',alpha = 0.1)
ax.add_patch(rect)
plt.xlim(-100,100)
plt.ylim(-100,200)
plt.show()

Output:

In the above example, we –

1. First, imported the required modules.
2. Then, generated a pyplot figure and added a subplot.
3. Then, we created a rectangle with the bottom left coordinate of the rectangle to be (0,50), with width as 50 and height as 100, and adjusted the transparency as 10% using the alpha parameter.
4. Then, we added the created rectangle to the axes using the add_patch method.
5. Then, we adjusted the x and y limits of the axes and plotted the figure.

Example 5 – Drawing multiple rectangles in Matplotlib

import matplotlib
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111)
rect1 = matplotlib.patches.Rectangle((0, 50),50, 100)
rect2 = matplotlib.patches.Rectangle((100, 50),10, 100)
ax.add_patch(rect1)
ax.add_patch(rect2)
plt.xlim(-400,400)
plt.ylim(-400,400)
plt.show()

Output:

In the above example, we –

1. First, imported the required modules.
2. Then, generated a pyplot figure and added a subplot.
3. Then, we created a rectangle with the bottom left coordinate of the rectangle to be (0,50), with width as 50 and height as 100.
4. Then, we created another rectangle with the bottom left coordinate of the rectangle to be (100,50), with width as 10, and height as 100.
5. Then, we added the created rectangles to the axes using the add_patch method.
6. Then, we adjusted the x and y limits of the axes and plotted the figure.

Example 6 – Drawing a Rectangle on a scatter plot

import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
fig, ax = plt.subplots()
ax.scatter([5, 7, 8, 7, 2, 17, 2, 9,
     4, 11, 12, 9, 6],[99, 86, 87, 88, 100, 86,
     103, 87, 94, 78, 77, 85, 86])
ax.add_patch( Rectangle((5, 82.5),
                        5, 7.5,
                        fc='none',
                        color ='yellow',
                        linewidth = 5,
                        linestyle="dotted") )
plt.show()

Output:

In the above example, we –

1. First, imported the required modules.
2. Then, generated a subplot.
3. Then we created a scatter plot of the data points using the pyplot.scatter() method (refer here).
4. Then we created a rectangle with the bottom left coordinate of the rectangle to be (5,82.5), with width as 5, and height as 7.5 with a dotted linestyle.
5. Then, we added the created rectangle to the axes using the add_patch method.
6. And finally, we plotted the figure.

Example 7 – Drawing a Rectangle on a scatter plot -2

import matplotlib.pyplot as plt
import pandas as pd
import matplotlib.patches as mpatches

penguins_data="https://raw.githubusercontent.com/datavizpyr/data/master/palmer_penguin_species.tsv"
# load penguns data with Pandas read_csv
df = pd.read_csv(penguins_data, sep="t")
plt.scatter(x=df.culmen_length_mm,
            y=df.culmen_depth_mm)
rect=mpatches.Rectangle((31,15),14,7, 
                        color = "purple",
                        linewidth = 2,
                        alpha=0.2)
plt.gca().add_patch(rect)
plt.show()

Output:

In the above example, we –

1. First, imported the required modules.
2. Then, import the data from an online resource and read the csv using pandas.read_csv() method (refer this) into a pandas data frame (refer this).
3. Then, plot the scatter points which are in the dataframe.
4. Then, draw the rectangle over the scatter plot.
5. Then, we added the created rectangle to the axes using the add_patch method.
6. And finally, we plotted the figure.

Example 8 – Drawing a rectangle over an Image

import matplotlib.pyplot as plt
import matplotlib.patches as patches
from PIL import Image
import numpy as np
import urllib.request  
urllib.request.urlretrieve(
  'https://picsum.photos/200',
   "temp.png")
x = np.array(Image.open('temp.png'))
fig, ax = plt.subplots(1)
ax.imshow(x)
rect = patches.Rectangle((10, 100), 100, 30, linewidth=1, edgecolor='r')
ax.add_patch(rect)
plt.show()

Output:

In the above example, we –

1. First, imported the required modules and methods.
2. Then, we get the image from a url and store it in our local storage using the urllib.request.urlretrieve method (refer this).
3. Then, we open the image (refer this) and convert it into its respective pixels using np.array (refer this).
4. Then, we create a subplot and add the image to the subplot.
5. Then, we create a rectangle and add it to the axes using the add_path method.
6. And finally, we plotted the figure.

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