Jupyter Notebook kernel dies when I increase the number of samples

Question

I am trying to execute the following python code:

plt.figure(figsize=(9,6))  
plt.title("Dendrograms for number of clusters")  
dend = sch.dendrogram(sch.linkage(scaled, method='ward'))

When I execute the above code with 12000 samples it works fine. However, when I increase the samples to 24000 it shows that Kernel appears to be dead in Jupyter notebook. KernelRestarter: restarting kernel (1/5), keep random ports Any help is really appreciated

Answer 1

This was an issue with scipy package. I downgraded the package scipy from 1.7.3 to 1.7.1 and it is working. However, the downgraded version of scipy has an issue of maximum recursion depth exceeded while getting str of an object . The second issue can be resolved by expanding the limit.