python - How to plot in multiple subplots

Question

I am a little confused about how this code works:

fig, axes = plt.subplots(nrows=2, ncols=2)
plt.show()

How does the fig, axes work in this case? What does it do?

Also why wouldn't this work to do the same thing:

fig = plt.figure()
axes = fig.subplots(nrows=2, ncols=2)

Answer 1

There are several ways to do it. The subplots method creates the figure along with the subplots that are then stored in the ax array. For example:

import matplotlib.pyplot as plt

x = range(10)
y = range(10)

fig, ax = plt.subplots(nrows=2, ncols=2)

for row in ax:
    for col in row:
        col.plot(x, y)

plt.show()

However, something like this will also work, it's not so "clean" though since you are creating a figure with subplots and then add on top of them:

fig = plt.figure()

plt.subplot(2, 2, 1)
plt.plot(x, y)

plt.subplot(2, 2, 2)
plt.plot(x, y)

plt.subplot(2, 2, 3)
plt.plot(x, y)

plt.subplot(2, 2, 4)
plt.plot(x, y)

plt.show()

Answer 2

import matplotlib.pyplot as plt

fig, ax = plt.subplots(2, 2)

ax[0, 0].plot(range(10), 'r') #row=0, col=0
ax[1, 0].plot(range(10), 'b') #row=1, col=0
ax[0, 1].plot(range(10), 'g') #row=0, col=1
ax[1, 1].plot(range(10), 'k') #row=1, col=1
plt.show()

Answer 3

• You can also unpack the axes in the subplots call

• And set whether you want to share the x and y axes between the subplots

Like this:

import matplotlib.pyplot as plt
fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(nrows=2, ncols=2, sharex=True, sharey=True)
ax1.plot(range(10), 'r')
ax2.plot(range(10), 'b')
ax3.plot(range(10), 'g')
ax4.plot(range(10), 'k')
plt.show()

Answer 4

You might be interested in the fact that as of matplotlib version 2.1 the second code from the question works fine as well.

From the change log:

Figure class now has subplots method The Figure class now has a subplots() method which behaves the same as pyplot.subplots() but on an existing figure.

Example:

import matplotlib.pyplot as plt

fig = plt.figure()
axes = fig.subplots(nrows=2, ncols=2)

plt.show()

Answer 5

Read the documentation: matplotlib.pyplot.subplots

pyplot.subplots() returns a tuple fig, ax which is unpacked in two variables using the notation

fig, axes = plt.subplots(nrows=2, ncols=2)

The code:

fig = plt.figure()
axes = fig.subplots(nrows=2, ncols=2)

does not work because subplots() is a function in pyplot not a member of the object Figure.

Answer 6

# Generate figure and its subplots
fig, axes = plt.subplots(nrows, ncols)

Iterating through all subplots sequentially:

for ax in axes.flatten():
    ax.plot(x,y)

Accessing a specific subplot via its index:

for row in range(nrows):
    for col in range(ncols):
        axes[row,col].plot(x[row], y[col])

Answer 7

Go with the following if you really want to use a loop:

def plot(data):
    fig = plt.figure(figsize=(100, 100))
    for idx, k in enumerate(data.keys(), 1):
        x, y = data[k].keys(), data[k].values
        plt.subplot(63, 10, idx)
        plt.bar(x, y)  
    plt.show()

Answer 8

The other answers are great, this answer is a combination which might be useful.

import numpy as np
import matplotlib.pyplot as plt

# Optional: define x for all the sub-plots
x = np.linspace(0,2*np.pi,100)

# (1) Prepare the figure infrastructure 
fig, ax_array = plt.subplots(nrows=2, ncols=2)

# flatten the array of axes, which makes them easier to iterate through and assign
ax_array = ax_array.flatten()

# (2) Plot loop
for i, ax in enumerate(ax_array):
  ax.plot(x , np.sin(x + np.pi/2*i))
  #ax.set_title(f'plot {i}')

# Optional: main title
plt.suptitle('Plots')

Summary

1. Prepare the figure infrastructure

   • Get ax_array, an array of the subplots
   • Flatten the array in order to use it in one 'for loop'

2. Plot loop

   • Loop over the flattened ax_array to update the subplots
   • optional: use enumeration to track subplot number