Save plot to image file instead of displaying it using Matplotlib (so it can be used in batch scripts for example)

The solution is:

pylab.savefig('foo.png')

As others have said, plt.savefig() or fig1.savefig() is indeed the way to save an image.

However I've found that in certain cases (eg. with Spyder having plt.ion(): interactive mode = On) the figure is always shown. I work around this by forcing the closing of the figure window in my giant loop, so I don't have a million open figures during the loop:

import matplotlib.pyplot as plt
fig, ax = plt.subplots( nrows=1, ncols=1 )  # create figure & 1 axis
ax.plot([0,1,2], [10,20,3])
fig.savefig('path/to/save/image/to.png')   # save the figure to file
plt.close(fig)    # close the figure

If you don't like the concept of the "current" figure, do:

import matplotlib.image as mpimg

img = mpimg.imread("src.png")
mpimg.imsave("out.png", img)

import datetime
import numpy as np
from matplotlib.backends.backend_pdf import PdfPages
import matplotlib.pyplot as plt

# Create the PdfPages object to which we will save the pages:
# The with statement makes sure that the PdfPages object is closed properly at
# the end of the block, even if an Exception occurs.
with PdfPages('multipage_pdf.pdf') as pdf:
    plt.figure(figsize=(3, 3))
    plt.plot(range(7), [3, 1, 4, 1, 5, 9, 2], 'r-o')
    plt.title('Page One')
    pdf.savefig()  # saves the current figure into a pdf page
    plt.close()

    plt.rc('text', usetex=True)
    plt.figure(figsize=(8, 6))
    x = np.arange(0, 5, 0.1)
    plt.plot(x, np.sin(x), 'b-')
    plt.title('Page Two')
    pdf.savefig()
    plt.close()

    plt.rc('text', usetex=False)
    fig = plt.figure(figsize=(4, 5))
    plt.plot(x, x*x, 'ko')
    plt.title('Page Three')
    pdf.savefig(fig)  # or you can pass a Figure object to pdf.savefig
    plt.close()

    # We can also set the file's metadata via the PdfPages object:
    d = pdf.infodict()
    d['Title'] = 'Multipage PDF Example'
    d['Author'] = u'Jouni K. Sepp\xe4nen'
    d['Subject'] = 'How to create a multipage pdf file and set its metadata'
    d['Keywords'] = 'PdfPages multipage keywords author title subject'
    d['CreationDate'] = datetime.datetime(2009, 11, 13)
    d['ModDate'] = datetime.datetime.today()

Just found this link on the MatPlotLib documentation addressing exactly this issue: http://matplotlib.org/faq/howto_faq.html#generate-images-without-having-a-window-appear

They say that the easiest way to prevent the figure from popping up is to use a non-interactive backend (eg. Agg), via matplotib.use(<backend>), eg:

import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
plt.plot([1,2,3])
plt.savefig('myfig')

I still personally prefer using plt.close( fig ), since then you have the option to hide certain figures (during a loop), but still display figures for post-loop data processing. It is probably slower than choosing a non-interactive backend though - would be interesting if someone tested that.

I used the following:

import matplotlib.pyplot as plt

p1 = plt.plot(dates, temp, 'r-', label="Temperature (celsius)")  
p2 = plt.plot(dates, psal, 'b-', label="Salinity (psu)")  
plt.legend(loc='upper center', numpoints=1, bbox_to_anchor=(0.5, -0.05),        ncol=2, fancybox=True, shadow=True)

plt.savefig('data.png')  
plt.show()  
f.close()
plt.close()

I found very important to use plt.show after saving the figure, otherwise it won't work.figure exported in png

If, like me, you use Spyder IDE, you have to disable the interactive mode with :

plt.ioff()

(this command is automatically launched with the scientific startup)

If you want to enable it again, use :

plt.ion()

The Solution :

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
matplotlib.style.use('ggplot')
ts = pd.Series(np.random.randn(1000), index=pd.date_range('1/1/2000', periods=1000))
ts = ts.cumsum()
plt.figure()
ts.plot()
plt.savefig("foo.png", bbox_inches='tight')

If you do want to display the image as well as saving the image use:

%matplotlib inline

after import matplotlib