I am having trouble displaying plots inside of Jupyter tab widgets. Consider the following snippet:
import matplotlib.pyplot as plt
import pandas as pd
import ipywidgets as widgets
import numpy as np
out1 = widgets.Output()
out2 = widgets.Output()
data1 = pd.DataFrame(np.random.normal(size = 50))
data2 = pd.DataFrame(np.random.normal(size = 100))
with out1:
fig1, axes1 = plt.subplots()
data1.hist(ax = axes1)
display(fig1)
with out2:
fig2, axes2 = plt.subplots()
data2.hist(ax = axes2)
display(fig2)
tab = widgets.Tab(children = [out1, out2])
tab.set_title(0, 'First')
tab.set_title(1, 'Second')
display(tab)
(I am running Python 3.5.2, Jupyter 4.4.0, ipywidgets 7.2.1 on Ubuntu 16.04 inside a virtual environment.)
If I put this code on the first row of the notebook and run it, I see a tab widget with two tabs, each one of which displays a string, but not the plot:
If I run it for a second time, or if I rerun it putting everything after the import of matplotlib
in a second cell, I see a tab widget with one plot on each tab, but I get the two plots displayed a second time outside of the tabs.
I can get rid of the additional displays by wrapping my code inside calls to plt.ioff
and plt.ion
, but it has been suggested to me that this is a hack. And in any case, it does not make matplotlib display the plots in the first cell.
Question: What is the proper way of displaying plots inside tabs?
I added a couple of things to make your code work as you would like
%matplotlib inline
at the top of the celldisplay(fig)
calls with plt.show(fig)
calls.%matplotlib inline
import matplotlib.pyplot as plt
import pandas as pd
import ipywidgets as widgets
import numpy as np
out1 = widgets.Output()
out2 = widgets.Output()
data1 = pd.DataFrame(np.random.normal(size = 50))
data2 = pd.DataFrame(np.random.normal(size = 100))
tab = widgets.Tab(children = [out1, out2])
tab.set_title(0, 'First')
tab.set_title(1, 'Second')
display(tab)
with out1:
fig1, axes1 = plt.subplots()
data1.hist(ax = axes1)
plt.show(fig1)
with out2:
fig2, axes2 = plt.subplots()
data2.hist(ax = axes2)
plt.show(fig2)