In my Jupyter notebook I am now using %matplotlib notebook
instead of %matplotlib inline
, it's awesome that I can now interact with my plots on Jupyter. However, when I try to make an histogram I get a blank plot:
If I use %matplotlib inline
everything works fine:
What's going on?
The reason your plot is blank is that matplotlib didn't auto-adjust the axis according to the range of your patches. Usually, it will do the auto-adjust jobs with some main plot functions, such as plt. plot(), plt.
In the current versions of the IPython notebook and jupyter notebook, it is not necessary to use the %matplotlib inline function. As, whether you call matplotlib. pyplot. show() function or not, the graph output will be displayed in any case.
The issue actually stems from the matplotlib backend not being properly set, or from a missing dependency when compiling and installing matplotlib.
show() . If you do not want to use inline plotting, just use %matplotlib instead of %matplotlib inline .
Seeing that my comment above has indeed helped someone to solve the problem I will post it as an answer.
The problem occurs if you switch from %matplotlib inline
to %matplotlib notebook
without restarting the kernel.
Switching from %matplotlib notebook
to %matplotlib inline
works fine.
So the solution is to either restart the kernel or start a new notebook.
It seems that in some cases it helps to repeat the setting of the notebook backend, i.e. call it twice like
%matplotlib notebook
%matplotlib notebook
An analysis for why that is can be found in this comment
The answer is not necessarily to restart the entire kernel.
If you reload the matplotlib module, it will work, too. Provided you use Python 3.6 like me, and you have import matplotlib.pyplot as plt
like me:
from importlib import reload
reload(plt)
%matplotlib notebook
It does the trick. Yes it is still a hack. At least this is an independent codecell you can use in the middle of the notebook. Switching back via %matplotlib inline
is not a problem.
You can also remove once imported names from the sys.modules list, then they get imported again when you call the import again.
import sys
sys.modules.pop('matplotlib')
from matplotlib import pyplot as plt
In many cases, that's a less good idea. But it might sometimes be the only straw to hold on.
I was able to fix it by downgrading matplotlib to 3.1.3:
conda install matplotlib=3.1.3
I was running version 3.3.2 and had this same issue. I was not switching between %matplotlib inline
and %matplotlib notebook
, and it did not matter if I placed %matplotlib notebook
before or after importing
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With