[python] How do I get multiple subplots in matplotlib?

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)

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()

Go with the following if you really want to use a loop. Nobody has actually answered how to feed data in 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()

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.

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()

• 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()

Iterating through all subplots sequentially:

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

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

Accessing a specific index:

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