Using reticulate with Jupyter

Is it possible to use reticulate with Jupyter Lab and produce charts using the python packages matplotlib/seaborn?

When I tried to replicate this: https://datascienceplus.com/how-to-make-seaborn-pairplot-and-heatmap-in-r-write-python-in-r/ (code submitted is below)

I got this message, but no chart: AxesSubplot(0.125,0.11;0.62x0.77)

library(reticulate)
use_python("/opt/rh/rh-python36/root/usr/bin", required = TRUE)
use_virtualenv("/opt/pmaqa/pydev/py36-venv", required = TRUE)

#py_config()
#py_discover_config()
 
plt <- import('matplotlib.pyplot')
sns <- import('seaborn')
pd <- import('pandas')

#using R's inbuilt AirPassengers dataset
df <- datasets::AirPassengers

#converting Time-Series object into an R Dataframe
#Thx: https://stackoverflow.com/questions/5331901/transforming-a-time-series-into-a-data-frame-and-back
df1 <- data.frame(tapply(df, list(year = floor(time(df)), month = month.abb[cycle(df)]), c))
df1 <- df1[month.abb]

#building a heatmap using seaborn
#please note the function r_to_py() that converts R object into a python
sns$heatmap(r_to_py(df1), fmt="g", cmap ='viridis')

#display the plot
plt$show()

Start by reproducing the provided reticulate code in Jupyter Lab with the specified Python and virtualenv settings, focusing on the seaborn heatmap and matplotlib display calls. Done means determining why the plot is not rendered, establishing whether this combination is supported, and documenting the result or a reproducible fix.