from matplotlib.pyplot import figure
figure(num=None, figsize=(8, 6), dpi=80, facecolor='w', edgecolor='k')

fig = matplotlib.pyplot.gcf()
fig.set_size_inches(18.5, 10.5)
fig.savefig('test2png.png', dpi=100)

fig.set_size_inches(18.5, 10.5, forward=True)

from pylab import rcParams
rcParams['figure.figsize'] = 5, 10

import matplotlib.pyplot as plt
plt.rcParams["figure.figsize"] = (20,3)

from matplotlib import pyplot as plt
plt.figure(figsize=(1,1))
x = [1,2,3]
plt.plot(x, x)
plt.show()

#!/usr/bin/env python
"""
This is a small demo file that helps teach how to adjust figure sizes
for matplotlib

"""

import matplotlib
print "using MPL version:", matplotlib.__version__
matplotlib.use("WXAgg") # do this before pylab so you don'tget the default back end.

import pylab
import numpy as np

# Generate and plot some simple data:
x = np.arange(0, 2*np.pi, 0.1)
y = np.sin(x)

pylab.plot(x,y)
F = pylab.gcf()

# Now check everything with the defaults:
DPI = F.get_dpi()
print "DPI:", DPI
DefaultSize = F.get_size_inches()
print "Default size in Inches", DefaultSize
print "Which should result in a %i x %i Image"%(DPI*DefaultSize[0], DPI*DefaultSize[1])
# the default is 100dpi for savefig:
F.savefig("test1.png")
# this gives me a 797 x 566 pixel image, which is about 100 DPI

# Now make the image twice as big, while keeping the fonts and all the
# same size
F.set_size_inches( (DefaultSize[0]*2, DefaultSize[1]*2) )
Size = F.get_size_inches()
print "Size in Inches", Size
F.savefig("test2.png")
# this results in a 1595x1132 image

# Now make the image twice as big, making all the fonts and lines
# bigger too.

F.set_size_inches( DefaultSize )# resetthe size
Size = F.get_size_inches()
print "Size in Inches", Size
F.savefig("test3.png", dpi = (200)) # change the dpi
# this also results in a 1595x1132 image, but the fonts are larger.

using MPL version: 0.98.1
DPI: 80
Default size in Inches [ 8.  6.]
Which should result in a 640 x 480 Image
Size in Inches [ 16.  12.]
Size in Inches [ 16.  12.]

df['some_column'].plot(figsize=(10, 5))

df['some_column'].plot(figsize=(10, 5))

fig, ax = plt.subplots(figsize=(10,5))
df['some_column'].plot(ax=ax)

import matplotlib

matplotlib.rc('figure', figsize=(10, 5))

fig.set_size_inches(width,height)

%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt

N = 50
x = np.random.rand(N)
y = np.random.rand(N)
area = np.pi * (15 * np.random.rand(N))**2

fig = plt.figure(figsize=(18, 18))
plt.scatter(x, y, s=area, alpha=0.5)
plt.show()

import matplotlib.pyplot as plt
plt.figure(figsize=(20,10))
plt.plot(x,y) ## This is your plot
plt.show()

fig, ax = plt.subplots(figsize=(20, 10))

N = 2
params = pl.gcf()
plSize = params.get_size_inches()
params.set_size_inches( (plSize[0]*N, plSize[1]*N) )

from matplotlib import pyplot as plt
F = gcf()
Size = F.get_size_inches()
F.set_size_inches(Size[0]*2, Size[1]*2, forward=True)#Set forward to True to resize window along with plot in figure.
plt.show() #or plt.imshow(z_array) if using an animation, where z_array is a matrix or numpy array

def cm2inch(*tupl):
    inch = 2.54
    if isinstance(tupl[0], tuple):
        return tuple(i/inch for i in tupl[0])
    else:
        return tuple(i/inch for i in tupl)

plt.figure(figsize=cm2inch(21, 29.7))

matplotlib.pyplot.get_current_fig_manager().resize(width_px, height_px)

import matplotlib
matplotlib.rc('figure', figsize=[10,5])