`df.my_column.plot(datashade=True)` gives strange graphs when my_column dtype=uint32

ALL software version info

Ubuntu 20.04

name: puma-lab
channels:
  - pyviz
  - conda-forge
  - defaults
dependencies:
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Description of expected behavior and the observed behavior

Expected:

Got:

The original dtype is numpy.uint32 (which gives the second figure). To get the first figure I have to change type: my_df.my_col = my_df.my_col.astype(np.int32)

Complete, minimal, self-contained example code that reproduces the issue

The only thing I noticed is the difference in dtype of data frame’s column. The original is dtype: uint32. When type is changed to e.g. dtype: int32, it works as expected. When trying to reproduce I get an empty figure instead of a half colored plot (see the picture above). So not sure what else the difference could be.

import numpy as np

# works as intended
test = pd.DataFrame([i for i in range(100)], columns=["my_column"])
test.plot(datashade=True)

# creates an empty figure
test.my_column = test.my_column.astype(np.uint32)
test.plot(datashade=True)

Stack traceback and/or browser JavaScript console output

Only a couple of warnings:

/home/toaster/PROGS/miniconda3/envs/puma-lab/lib/python3.7/site-packages/holoviews/operation/datashader.py:428: FutureWarning: casting datetime64[ns] values to int64 with .astype(...) is deprecated and will raise in a future version. Use .view(...) instead.
  df[d.name] = vals.astype('int64')
/home/toaster/PROGS/miniconda3/envs/puma-lab/lib/python3.7/site-packages/holoviews/operation/datashader.py:428: FutureWarning: casting datetime64[ns] values to int64 with .astype(...) is deprecated and will raise in a future version. Use .view(...) instead.
  df[d.name] = vals.astype('int64')

[Hoxbro]

Sorry if I wasn’t clear, the plot I showed was with my fix in it. See the PR above my comment.

[jbednar]

Someone could investigate, but no one has volunteered yet, so it’s an open challenge. I am not sure it’s a datashader issue, and mostly the same people work on both projects, so here is as good a place as any. For now there is a workaround, but if you’d like to investigate, the first step would be to trace though and see if the data is converted to a new type before calling datashader. Wish I had more details than that, but that’s what needs investigating!