When using this in a script (not IPython), nothing happens, i.e. the plot window doesn't appear :
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()
Even when adding time.sleep(5)
, there is still nothing. Why?
Is there a way to do it, without having to manually call matplotlib ?
It means if we are not using the show() function, it wouldn't show any plot. When we use the show() function in the non-interactive mode. That means when we write the code in the file it will show all the figures or plots and blocks until the plots have been closed.
Why matplotlib inline is used. You can use the magic function %matplotlib inline to enable the inline plotting, where the plots/graphs will be displayed just below the cell where your plotting commands are written. It provides interactivity with the backend in the frontends like the jupyter notebook.
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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