Plt.Figure.Figure.Show() Does Nothing When Not Executing Interactively

plt.figure.Figure.show() does nothing when not executing interactively

plt.show starts an event loop, creates interactive windows and shows all current figures in them. If you have more figures than you actually want to show in your current pyplot state, you may close all unneeded figures prior to calling plt.show().

fig1 = plt.figure()
ax1 = fig1.add_subplot(1, 1, 1)
ax1.plot([1,3,4])

fig2 = plt.figure()
ax2 = fig2.add_subplot(1, 1, 1)
ax2.plot([1,2,5])

# close first figure
plt.close(fig1)
# show all active figures (which is now only fig2)
plt.show()

In contrast fig.show() will not start an event loop. It will hence only make sense in case an event loop already has been started, e.g. after plt.show() has been called. In non-interactive mode that may happen upon events in the event loop. To give an example, the following would show fig2 once a key on the keyboard is pressed when fig1 is active.

import matplotlib.pyplot as plt

fig1 = plt.figure()
ax1 = fig1.add_subplot(1, 1, 1)
ax1.plot([1,3,4])

def show_new_figure(evt=None):
    fig2 = plt.figure()
    ax2 = fig2.add_subplot(1, 1, 1)
    ax2.plot([1,2,5])
    fig2.show()

# Upon pressing any key in fig1, show fig2.
fig1.canvas.mpl_connect("key_press_event", show_new_figure)

plt.show()

Matplotlib `figure.show()` does not show anything on Mac OSX

figure.show() makes sense in interactive mode, not for permanently showing a figure. So you need to use plt.show(). In order not to show the second figure, you may close it beforehands,

plt.close(figure2)
plt.show()

Matplotlib plots aren't shown when running file from bash terminal

You need to add matplotlib.pyplot.show() in your code to show plots in non-interactive mode. See docs at http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.show

EDIT:

After further info from OP, blocking had to be enabled explicitly using plt.show(block=True).

How can I show figures separately in matplotlib?

Sure. Add an Axes using add_subplot. (Edited import.) (Edited show.)

import matplotlib.pyplot as plt
f1 = plt.figure()
f2 = plt.figure()
ax1 = f1.add_subplot(111)
ax1.plot(range(0,10))
ax2 = f2.add_subplot(111)
ax2.plot(range(10,20))
plt.show()

Alternatively, use add_axes.

ax1 = f1.add_axes([0.1,0.1,0.8,0.8])
ax1.plot(range(0,10))
ax2 = f2.add_axes([0.1,0.1,0.8,0.8])
ax2.plot(range(10,20))

Plots not showing in Jupyter notebook

If you are working with a Jupyter Notebook then you can add the following line to the top cell where you call all your imports. The following command will render your graph

%matplotlib inline

Is there a way to detach matplotlib plots so that the computation can continue?

Use matplotlib's calls that won't block:

Using draw():

from matplotlib.pyplot import plot, draw, show
plot([1,2,3])
draw()
print('continue computation')

# at the end call show to ensure window won't close.
show()

Using interactive mode:

from matplotlib.pyplot import plot, ion, show
ion() # enables interactive mode
plot([1,2,3]) # result shows immediatelly (implicit draw())

print('continue computation')

# at the end call show to ensure window won't close.
show()

Pandas plot doesn't show

Once you have made your plot, you need to tell matplotlib to show it. The usual way to do things is to import matplotlib.pyplot and call show from there:

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
ts = pd.Series(np.random.randn(1000), index=pd.date_range('1/1/2000', periods=1000))
ts.plot()
plt.show()

In older versions of pandas, you were able to find a backdoor to matplotlib, as in the example below. NOTE: This no longer works in modern versions of pandas, and I still recommend importing matplotlib separately, as in the example above.

import numpy as np
import pandas as pd
ts = pd.Series(np.random.randn(1000), index=pd.date_range('1/1/2000', periods=1000))
ts.plot()
pd.tseries.plotting.pylab.show()

But all you are doing there is finding somewhere that matplotlib has been imported in pandas, and calling the same show function from there.

Are you trying to avoid calling matplotlib in an effort to speed things up? If so then you are really not speeding anything up, since pandas already imports pyplot:

python -mtimeit -s 'import pandas as pd'
100000000 loops, best of 3: 0.0122 usec per loop

python -mtimeit -s 'import pandas as pd; import matplotlib.pyplot as plt'
100000000 loops, best of 3: 0.0125 usec per loop

Finally, the reason the example you linked in comments doesn't need the call to matplotlib is because it is being run interactively in an iPython notebook, not in a script.

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