# Fix Python – What is the difference between drawing plots using plot, axes or figure in matplotlib?

## Question

I’m kind of confused what is going at the backend when I draw plots in matplotlib, tbh, I’m not clear with the hierarchy of plot, axes and figure. I read the documentation and it was helpful but I’m still confused…

The below code draws the same plot in three different ways –

``````#creating the arrays for testing
x = np.arange(1, 100)
y = np.sqrt(x)
#1st way
plt.plot(x, y)
#2nd way
ax = plt.subplot()
ax.plot(x, y)
#3rd way
figure = plt.figure()
new_plot.plot(x, y)
``````

Now my question is –

1. What is the difference between all the three, I mean what is going under the hood when any of the 3 methods are called?

2. Which method should be used when and what are the pros and cons of using any on those?

Now we will see solution for issue: What is the difference between drawing plots using plot, axes or figure in matplotlib?

Method 1

``````plt.plot(x, y)
``````

This lets you plot just one figure with (x,y) coordinates. If you just want to get one graphic, you can use this way.

Method 2

``````ax = plt.subplot()
ax.plot(x, y)
``````

This lets you plot one or several figure(s) in the same window. As you write it, you will plot just one figure, but you can make something like this:

``````fig1, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2)
``````

You will plot 4 figures which are named ax1, ax2, ax3 and ax4 each one but on the same window. This window will be just divided in 4 parts with my example.

Method 3

``````fig = plt.figure()
new_plot.plot(x, y)
``````

I didn’t use it, but you can find documentation.

Example:

``````import numpy as np
import matplotlib.pyplot as plt

# Method 1 #

x = np.random.rand(10)
y = np.random.rand(10)

figure1 = plt.plot(x,y)

# Method 2 #

x1 = np.random.rand(10)
x2 = np.random.rand(10)
x3 = np.random.rand(10)
x4 = np.random.rand(10)
y1 = np.random.rand(10)
y2 = np.random.rand(10)
y3 = np.random.rand(10)
y4 = np.random.rand(10)

figure2, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2)
ax1.plot(x1,y1)
ax2.plot(x2,y2)
ax3.plot(x3,y3)
ax4.plot(x4,y4)

plt.show()
``````

Other example:

This question is answered By – Essex