Closed patrickm663 closed 4 months ago
Forgot to add:
Hi @patrickm663 Sorry for the errors. I noticed that with pandas 2.0 and numpy >1.24 and newer python versions, the entire python ecosystem has gone for a toss. I am sorry to say but it is hitting open source developers like me hard. We now have to have different versions for different python versions. I have tried my best to maintain support for AutoViz in these trying times for python ecosystem. So please try to install directly from the github if possible to get the latest updates.
pip install git+https://github.com/AutoViML/AutoViz.git --user
For now, I have fixed your error 👍
You can check it by upgrading to autoviz version 0.1.901 as follows
pip install autoviz==0.1.901
or
pip install autoviz --upgrade
Thanks AutoVimal
Hi @patrickm663 Sorry for the errors. I noticed that with pandas 2.0 and numpy >1.24 and newer python versions, the entire python ecosystem has gone for a toss. I am sorry to say but it is hitting open source developers like me hard. We now have to have different versions for different python versions. I have tried my best to maintain support for AutoViz in these trying times for python ecosystem. So please try to install directly from the github if possible to get the latest updates.
pip install git+https://github.com/AutoViML/AutoViz.git --user
For now, I have fixed your error 👍
You can check it by upgrading to autoviz version 0.1.901 as follows
pip install autoviz==0.1.901
or
pip install autoviz --upgrade
Thanks AutoVimal
Hi
Sorry for the delayed response but thanks very much for looking into this!
Interestingly, I came across it when cleaning up the 'mess' caused by Pandas updating and breaking some old code. This prompted a further look at some notebooks that hadn't run in a while (to see if they still worked correctly with updated dependencies) and noted the edge-case here that had previously worked.
Many thanks again!
Best wishes Patrick
Hi
I am getting a strange error when using Bokeh as the backend, whereas SVG works. Part of the visualisation gets produced before throwing an error.
After testing Iris and Penguins data from Seaborn, the issue likely stems from the structure of the Planets dataset that is not being handled correctly. In fact, all of these datasets from Seaborn seem to fail:
What they all have in common is that they contain a date of sorts, however, datasets like "glue" have an
int64
for its Year column so this may just be coincidence.Below is a MWE (Classic Jupyter Notebook view):
Below is the stacktrace: