How do I change the figure size with subplots?

I came across this example in the Matplotlib website. I was wondering if it was possible to increase the figure size.

I tried with

f.figsize(15,15)

but it does nothing.

If you already have the figure object use:

f.set_figheight(15)
f.set_figwidth(15)

But if you use the .subplots() command (as in the examples you're showing) to create a new figure you can also use:

f, axs = plt.subplots(2,2,figsize=(15,15))

Alternatively, create a figure() object using the figsize argument and then use add_subplot to add your subplots. E.g.

import matplotlib.pyplot as plt
import numpy as np

f = plt.figure(figsize=(10,3))
ax = f.add_subplot(121)
ax2 = f.add_subplot(122)
x = np.linspace(0,4,1000)
ax.plot(x, np.sin(x))
ax2.plot(x, np.cos(x), 'r:')

Benefits of this method are that the syntax is closer to calls of subplot() instead of subplots(). E.g. subplots doesn't seem to support using a GridSpec for controlling the spacing of the subplots, but both subplot() and add_subplot() do.

In addition to the previous answers, here is an option to set the size of the figure and the size of the subplots within the figure individually by means of gridspec_kw:

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

#generate random data
x,y=range(100), range(10)
z=np.random.random((len(x),len(y)))
Y=[z[i].sum() for i in range(len(x))]
z=pd.DataFrame(z).unstack().reset_index()

#Plot data
fig, axs = plt.subplots(2,1,figsize=(16,9), gridspec_kw={'height_ratios': [1, 2]})
axs[0].plot(Y)
axs[1].scatter(z['level_1'], z['level_0'],c=z[0])

with this figure as result:

You can use plt.figure(figsize = (16,8)) to change figure size of a single plot and with up to two subplots. (arguments inside figsize lets to modify the figure size)

To change figure size of more subplots you can use plt.subplots(2,2,figsize=(10,10)) when creating subplots.

For plotting subplots in a for loop which is useful sometimes: Sample code to for a matplotlib plot of multiple subplots of histograms from a multivariate numpy array (2 dimensional).

plt.figure(figsize=(16, 8)) 
for i in range(1, 7):
    plt.subplot(2, 3, i)
    plt.title('Histogram of {}'.format(str(i)))
    plt.hist(x[:,i-1], bins=60)

   from matplotlib import pyplot as plt
   lis=[img,gaussian_img,gaussian_img_8bit]
   f,axs=plt.subplots(3,1,figsize=(25,25)) #ROW,COLUMN
   axs[0].imshow(lis[0])
   axs[1].imshow(lis[1])
   axs[2].imshow(lis[2])