This issue is a follow up on this SO answer as per @philippjfr request. Please keep in mind it's the first time I'm using holoplot (which seems to be awesome!)

I tried to use holoplot from within a Jupyter notebook. Once importing the package using

import holoplot.pandas

all .plot are going through holoplot. This is not always a convenient behavior. Sometimes, it is easy to think of a use case where some cells should be using holoplot while others will be rendered using the standard matplotlib. I hope this issue is good enough as a starting point for an interesting discussion.

ALL software version info

hvplot: 0.7.3

Description of expected behavior and the observed behavior

The following import fails, despite the all-catching except in the code?? (Honestly stumped)

from hvplot.sample_data import us_crime, airline_flights

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
/tmp/ipykernel_3185062/1788543639.py in <module>
----> 1 from hvplot.sample_data import us_crime, airline_flights

~/miniconda3/envs/py39/lib/python3.9/site-packages/hvplot/sample_data.py in <module>
     23 # Add catalogue entries to namespace
     24 for _c in catalogue:
---> 25     globals()[_c] = catalogue[_c]

~/miniconda3/envs/py39/lib/python3.9/site-packages/intake/catalog/base.py in __getitem__(self, key)
    398             if e.container == 'catalog':
    399                 return e(name=key)
--> 400             return e()
    401         if isinstance(key, str) and '.' in key:
    402             key = key.split('.')

~/miniconda3/envs/py39/lib/python3.9/site-packages/intake/catalog/entry.py in __call__(self, persist, **kwargs)
     75             raise ValueError('Persist value (%s) not understood' % persist)
     76         persist = persist or self._pmode
---> 77         s = self.get(**kwargs)
     78         if persist != 'never' and isinstance(s, PersistMixin) and s.has_been_persisted:
     79             from ..container.persist import store

~/miniconda3/envs/py39/lib/python3.9/site-packages/intake/catalog/local.py in get(self, **user_parameters)
    287             return self._default_source
    288 
--> 289         plugin, open_args = self._create_open_args(user_parameters)
    290         data_source = plugin(**open_args)
    291         data_source.catalog_object = self._catalog

~/miniconda3/envs/py39/lib/python3.9/site-packages/intake/catalog/local.py in _create_open_args(self, user_parameters)
    261 
    262         if len(self._plugin) == 0:
--> 263             raise ValueError('No plugins loaded for this entry: %s\n'
    264                              'A listing of installable plugins can be found '
    265                              'at https://intake.readthedocs.io/en/latest/plugin'

ValueError: No plugins loaded for this entry: parquet
A listing of installable plugins can be found at https://intake.readthedocs.io/en/latest/plugin-directory.html .

For reference, this is the code in 0.7.3:

import os

try:
    from intake import open_catalog
except:
    raise ImportError('Loading hvPlot sample data requires intake '
                      'and intake-parquet. Install it using conda or '
                      'pip before loading data.')

How can intake throw a ValueError??

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

• Have only the package intake installed, no other intake-subpackages.
• Execute : from hvplot.sample_data import us_crime, airline_flights

# code goes here between backticks
from hvplot.sample_data import us_crime, airline_flights

Stack traceback and/or browser JavaScript console output

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
/tmp/ipykernel_3185062/1788543639.py in <module>
----> 1 from hvplot.sample_data import us_crime, airline_flights

~/miniconda3/envs/py39/lib/python3.9/site-packages/hvplot/sample_data.py in <module>
     23 # Add catalogue entries to namespace
     24 for _c in catalogue:
---> 25     globals()[_c] = catalogue[_c]

~/miniconda3/envs/py39/lib/python3.9/site-packages/intake/catalog/base.py in __getitem__(self, key)
    398             if e.container == 'catalog':
    399                 return e(name=key)
--> 400             return e()
    401         if isinstance(key, str) and '.' in key:
    402             key = key.split('.')

~/miniconda3/envs/py39/lib/python3.9/site-packages/intake/catalog/entry.py in __call__(self, persist, **kwargs)
     75             raise ValueError('Persist value (%s) not understood' % persist)
     76         persist = persist or self._pmode
---> 77         s = self.get(**kwargs)
     78         if persist != 'never' and isinstance(s, PersistMixin) and s.has_been_persisted:
     79             from ..container.persist import store

~/miniconda3/envs/py39/lib/python3.9/site-packages/intake/catalog/local.py in get(self, **user_parameters)
    287             return self._default_source
    288 
--> 289         plugin, open_args = self._create_open_args(user_parameters)
    290         data_source = plugin(**open_args)
    291         data_source.catalog_object = self._catalog

~/miniconda3/envs/py39/lib/python3.9/site-packages/intake/catalog/local.py in _create_open_args(self, user_parameters)
    261 
    262         if len(self._plugin) == 0:
--> 263             raise ValueError('No plugins loaded for this entry: %s\n'
    264                              'A listing of installable plugins can be found '
    265                              'at https://intake.readthedocs.io/en/latest/plugin'

ValueError: No plugins loaded for this entry: parquet
A listing of installable plugins can be found at https://intake.readthedocs.io/en/latest/plugin-directory.html .

Additional info

The list of required package is now this:

• intake-parquet
• intake-xarray
• s3fs

ALL software version info

xr.__version__
'0.21.1'
hvplot.__version__
'0.7.3'
holoviews.__version__
'1.14.7'

Description of expected behavior and the observed behavior

When I visualize zarr-backed xarray datasets with hvplot, I expect the loading to be lazy. I don't want to load the entire array into memory. I expect this to happen even without dask being involved.

Instead, I am noticing that hvplot is loading data eagerly.

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

import xarray as xr
import hvplot.xarray

url = "https://ncsa.osn.xsede.org/Pangeo/pangeo-forge/swot_adac/FESOM/surf/fma.zarr"
ds = xr.open_dataset(url, engine='zarr') # note that ds is not chunked but still uses lazy loading

# this will trigger loading the whole array into memory
ds.sst.hvplot(x='lon', y='lat', dynamic=True, rasterize=True)

Note that lazyness can be achieved by chunking the xarray dataset. But I don't want to have to do that. Dask introduces additional latency that I would like to avoid here.

Fixes #114

@tonyfast, @jlstevens and I worked through a solution to add a datashade option for a hvplot scatter_matrix. @jlstevens pointed out datashade options (aggregator, rasterize, etc) may need to be considered when implementing this. This PR, so far, only includes an argument to set datashade = True in the call to scatter_matrix, which will then use grid.apply(datashade, per_element=True), as @philippjfr suggested as a solution in the issue.

This PR aims to add better docstring for users. It does this by providing more descriptive text, examples and reference links similar to the docstrings recently added to Panel.

I will try to stick to the reference example below.

As a user I would like to understand

• what the plot is
• be guided when to use it
• How this can be used
  • understand the available options and parameters and how to find out more about them
• Quickly be able to learn more about the type of plot in general (wikipedia) and in particular for the selected backend.

As a developer or supporter on Discourse working on the specific plot it is very helpful to be able to find the Pandas .plot and backend references quickly.

For beginners the docstring should contain just enough information to get a general idea of what this is and if it is the right plot to use. For more info they can head of to the reference documentation.

For super users the docstring should have just enough information to refresh your memory and be able to work. And we should be able to navigate without to much context switching. When you have to leave your editor or IDE there is a cost.

Many users (my self included) have not been educated abstractly (we might have concretely) in data visualization. I.e. we might not know the right terms, the right plot to use for the kind of data, not understand why we cannot make a bar plot from non-categorical data when that is normal for other frameworks to support etc. So the docs should help guide and share knowledge.

Describe the bug

I have a collection of holoviews and hvplot plots that I'd like to pickle and store for later retrieval, ideally including all styles/customizations.

With holoviews, this can easily be done with using either pickle or hv.Store - where the first stores the core holoviews obj and the latter includes the holoviews options to persist style/customizations.

However, neither pickle or hv.Store seem to work with hvplot plots.

Steps/Code to reproduce bug

Create a hvplot:

import numpy as np
import pandas as pd
import hvplot.pandas

df = pd.DataFrame(np.random.randn(1000, 4), columns=list('ABCD')).cumsum()
hv_plot_example = df.hvplot()
hv_plot_example

Try to pickle the plot:

import pickle

plot_bytes = pickle.dumps(hv_plot_example)

or

import holoviews as hv

plot_bytes = hv.Store.dumps(hv_plot_example)

Both throw the following AttributeError:

AttributeError: Can't pickle local object Redim._create_expression_transform.<locals>._transform_expression

Expected behavior

I would like to be able to pickle the hvplot directly so that I can persist in for retrieval later. Without this functionality, I'm limited to writing plots to temporary .png files and storing those rather than the pickled object.

Additional Context

holoviews supports this functionality as the following example works perfectly:

import holoviews as hv
hv.extension('bokeh')

holo_plot_example = hv.Overlay()
for column in list(df):
    ys = df[column].values
    holo_plot_example *= hv.Curve(ys).opts(title="Test")
    
holo_plot_example

which can be pickled with either:

import pickle

holo_plot_pickle = pickle.dumps(holo_plot_example)
pickle.loads(holo_plot_pickle)

or

holo_plot_store_pickle = hv.Store.dumps(holo_plot_example)
hv.Store.loads(holo_plot_store_pickle)

Thanks for contacting us! Please read and follow these instructions carefully, then delete this introductory text to keep your issue easy to read. Note that the issue tracker is NOT the place for usage questions and technical assistance; post those at Discourse instead. Issues without the required information below may be closed immediately.

ALL software version info

hvplot 0.5.2 bokeh 2.0.1

Description of expected behavior and the observed behavior

Plotting image results in axes and colorbar limits jumping around. A zoom box draw partially outside valid pixels of image causes further jumping around of axes limits.

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

https://gist.github.com/scottyhq/0e245fcd62d8a46b82a4186fcd8945e6#file-hvplot-zoom-ipynb

# Lots of window and colorbar rescaling happening when first plot, and upon zooming
band1.hvplot.image(x='x',y='y',
                   crs='epsg:32645', 
                   tiles='OSM', 
                   rasterize=True,
                   width=700, height=500, 
                   cmap='plasma', 
                   logz=True,
                   alpha=0.7)

Stack traceback and/or browser JavaScript console output

No error or traceback, but the behavior is buggy. See gif:

Screenshots or screencasts of the bug in action

Using python 3.6 on Linux with

• holoviews 1.13.2
• hvplot 0.5.2
• bokeh 2.0.2
• IPython 7.1.1

When I do something simple like:

df.hvplot(kind="scatter")

A red "Out[nn]" is shown and nothing else. This frequently happens in notebooks where the same plot showed fine earlier. At some point it stopped working.

Under my imports:

import holoviews as hv
hv.extension("bokeh")
import hvplot
import hvplot.pandas

The following messages are shown:

Javascript error adding output!
TypeError: Bokeh.set_log_level is not a function
See your browser Javascript console for more details

On the Chrome javascript console there are many warnings and the following errors:

Uncaught TypeError: Cannot read property 'embed_items_notebook' of undefined 
    at embed_document (<anonymous>:5:20)
    at <anonymous>:8:5
    at <anonymous>:24:3
    at eval (eval at append_javascript (outputarea.js:763), <anonymous>:97:28)
    at Array.forEach (<anonymous>)
    at window._Events.handle_add_output (eval at append_javascript (outputarea.js:763), <anonymous>:86:13)
    at window._Events.dispatch (jquery.min.js:5237)
    at window._Events.elemData.handle (jquery.min.js:5044)
    at Object.trigger (jquery.min.js:8471)
    at window._Events.<anonymous> (jquery.min.js:8549)
events.js:33 Exception in event handler for output_added.OutputArea TypeError: Cannot use 'in' operator to search for '1754' in undefined
    at window._Events.handle_add_output (eval at append_javascript (outputarea.js:763), <anonymous>:103:45)
    at window._Events.dispatch (jquery.min.js:5237)
    at window._Events.elemData.handle (jquery.min.js:5044)
    at Object.trigger (jquery.min.js:8471)
    at window._Events.<anonymous> (jquery.min.js:8549)
    at Function.each (jquery.min.js:367)
    at jQuery.fn.init.each (jquery.min.js:202)
    at jQuery.fn.init.trigger (jquery.min.js:8548)
    at jQuery.fn.init.events.trigger (events.js:31)
    at OutputArea.append_output (outputarea.js:355) Arguments(2)

In the Firefox console I see the following errors:

Comm promise not found for comm id hv-extension-comm comm.js:127
    comm_msg comm.js:127
    proxy jQuery
    _handle_iopub_message kernel.js:1224
    _finish_ws_message kernel.js:1016
    _msg_queue kernel.js:1007
TypeError: root.Bokeh.embed is undefinedplotting-libs.ipynb line 97 > scriptElement:5:3
    embed_document plotting-libs.ipynb line 97 > scriptElement:5
    <anonymous> plotting-libs.ipynb line 97 > scriptElement:8
    <anonymous> plotting-libs.ipynb line 97 > scriptElement:24
    handle_add_output main.min.js:97
    forEach self-hosted:225
    handle_add_output main.min.js:86
    jQuery 7
    trigger events.js:31
    append_output outputarea.js:355
    fromJSON outputarea.js:1046
    fromJSON codecell.js:564
    fromJSON notebook.js:2660
    load_notebook_success notebook.js:3146
    proxy jQuery
Exception in event handler for output_added.OutputArea TypeError: "right-hand side of 'in' should be an object, got undefined"
    handle_add_output main.min.js:103
    jQuery 7
    trigger events.js:31
    append_output outputarea.js:355
    fromJSON outputarea.js:1046
    fromJSON codecell.js:564
    fromJSON notebook.js:2660
    load_notebook_success notebook.js:3146
    proxy jQuery

What I find frustrating is that the same notebook worked fine a bit earlier and there is nothing obvious that has been changed to explain why it suddenly does not work and no helpful error message as to what might be going wrong.

ALL software version info

I am using the latest released versions of all the relevant libraries.

Hvplot 0.5.2 Datshader 0.10.0 Numba 0.48.0

Description of expected behavior and the observed behavior

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

I am trying to plot an xarray dataset backed by dask using hvplot. Here is how I load the data. (Should be reproducible with intake installed.)

from intake import open_catalog
cat = open_catalog("https://raw.githubusercontent.com/pangeo-data/pangeo-datastore/master/intake-catalogs/ocean.yaml")
ds  = cat["sea_surface_height"].to_dask()

The following code works fine:

ds.sla.hvplot.image('longitude', 'latitude', rasterize=True, dynamic=True)

However, if I try to do quadmesh instead

ds.sla.hvplot.quadmesh('longitude', 'latitude', rasterize=True, dynamic=True)

I get a big long error.

Stack traceback and/or browser JavaScript console output

WARNING:param.dynamic_operation: Callable raised "TypingError('Failed in nopython mode pipeline (step: nopython frontend)\nnon-precise type pyobject\n[1] During: typing of argument at <extend_cpu> (4)\n\nFile "<extend_cpu>", line 4:\n<source missing, REPL/exec in use?>\n\nThis error may have been caused by the following argument(s):\n- argument 4: cannot determine Numba type of <class \'dask.array.core.Array\'>\n')".
Invoked as dynamic_operation(numpy.datetime64('1993-01-01T00:00:00.000000000'), height=300, scale=1.0, width=700, x_range=None, y_range=None)
WARNING:param.dynamic_operation: Callable raised "TypingError('Failed in nopython mode pipeline (step: nopython frontend)\nnon-precise type pyobject\n[1] During: typing of argument at <extend_cpu> (4)\n\nFile "<extend_cpu>", line 4:\n<source missing, REPL/exec in use?>\n\nThis error may have been caused by the following argument(s):\n- argument 4: cannot determine Numba type of <class \'dask.array.core.Array\'>\n')".
Invoked as dynamic_operation(numpy.datetime64('1993-01-01T00:00:00.000000000'), height=300, scale=1.0, width=700, x_range=None, y_range=None)
---------------------------------------------------------------------------
TypingError                               Traceback (most recent call last)
/srv/conda/envs/pangeo/lib/python3.7/site-packages/IPython/core/formatters.py in __call__(self, obj, include, exclude)
    968 
    969             if method is not None:
--> 970                 return method(include=include, exclude=exclude)
    971             return None
    972         else:

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/core/dimension.py in _repr_mimebundle_(self, include, exclude)
   1302         combined and returned.
   1303         """
-> 1304         return Store.render(self)
   1305 
   1306 

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/core/options.py in render(cls, obj)
   1393         data, metadata = {}, {}
   1394         for hook in hooks:
-> 1395             ret = hook(obj)
   1396             if ret is None:
   1397                 continue

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/ipython/display_hooks.py in pprint_display(obj)
    280     if not ip.display_formatter.formatters['text/plain'].pprint:
    281         return None
--> 282     return display(obj, raw_output=True)
    283 
    284 

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/ipython/display_hooks.py in display(obj, raw_output, **kwargs)
    256     elif isinstance(obj, (HoloMap, DynamicMap)):
    257         with option_state(obj):
--> 258             output = map_display(obj)
    259     elif isinstance(obj, Plot):
    260         output = render(obj)

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/ipython/display_hooks.py in wrapped(element)
    144         try:
    145             max_frames = OutputSettings.options['max_frames']
--> 146             mimebundle = fn(element, max_frames=max_frames)
    147             if mimebundle is None:
    148                 return {}, {}

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/ipython/display_hooks.py in map_display(vmap, max_frames)
    204         return None
    205 
--> 206     return render(vmap)
    207 
    208 

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/ipython/display_hooks.py in render(obj, **kwargs)
     66         renderer = renderer.instance(fig='png')
     67 
---> 68     return renderer.components(obj, **kwargs)
     69 
     70 

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/plotting/renderer.py in components(self, obj, fmt, comm, **kwargs)
    363             doc = Document()
    364             with config.set(embed=embed):
--> 365                 model = plot.layout._render_model(doc, comm)
    366             return render_model(model, comm) if embed else render_mimebundle(model, doc, comm)
    367         else:

/srv/conda/envs/pangeo/lib/python3.7/site-packages/panel/viewable.py in _render_model(self, doc, comm)
    363         if comm is None:
    364             comm = state._comm_manager.get_server_comm()
--> 365         model = self.get_root(doc, comm)
    366 
    367         if config.embed:

/srv/conda/envs/pangeo/lib/python3.7/site-packages/panel/viewable.py in get_root(self, doc, comm)
    534         """
    535         doc = doc or _curdoc()
--> 536         root = self._get_model(doc, comm=comm)
    537         self._preprocess(root)
    538         ref = root.ref['id']

/srv/conda/envs/pangeo/lib/python3.7/site-packages/panel/layout.py in _get_model(self, doc, root, parent, comm)
    134         if root is None:
    135             root = model
--> 136         objects = self._get_objects(model, [], doc, root, comm)
    137         props = dict(self._init_properties(), objects=objects)
    138         model.update(**self._process_param_change(props))

/srv/conda/envs/pangeo/lib/python3.7/site-packages/panel/layout.py in _get_objects(self, model, old_objects, doc, root, comm)
    124             else:
    125                 try:
--> 126                     child = pane._get_model(doc, root, model, comm)
    127                 except RerenderError:
    128                     return self._get_objects(model, current_objects[:i], doc, root, comm)

/srv/conda/envs/pangeo/lib/python3.7/site-packages/panel/pane/holoviews.py in _get_model(self, doc, root, parent, comm)
    225             plot = self.object
    226         else:
--> 227             plot = self._render(doc, comm, root)
    228 
    229         plot.pane = self

/srv/conda/envs/pangeo/lib/python3.7/site-packages/panel/pane/holoviews.py in _render(self, doc, comm, root)
    284             kwargs = {}
    285 
--> 286         return renderer.get_plot(self.object, **kwargs)
    287 
    288     def _cleanup(self, root):

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/plotting/bokeh/renderer.py in get_plot(self_or_cls, obj, doc, renderer, **kwargs)
     71         combining the bokeh model with another plot.
     72         """
---> 73         plot = super(BokehRenderer, self_or_cls).get_plot(obj, doc, renderer, **kwargs)
     74         if plot.document is None:
     75             plot.document = Document() if self_or_cls.notebook_context else curdoc()

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/plotting/renderer.py in get_plot(self_or_cls, obj, doc, renderer, comm, **kwargs)
    200 
    201         # Initialize DynamicMaps with first data item
--> 202         initialize_dynamic(obj)
    203 
    204         if not renderer:

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/plotting/util.py in initialize_dynamic(obj)
    249             continue
    250         if not len(dmap):
--> 251             dmap[dmap._initial_key()]
    252 
    253 

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/core/spaces.py in __getitem__(self, key)
   1278         # Not a cross product and nothing cached so compute element.
   1279         if cache is not None: return cache
-> 1280         val = self._execute_callback(*tuple_key)
   1281         if data_slice:
   1282             val = self._dataslice(val, data_slice)

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/core/spaces.py in _execute_callback(self, *args)
   1052 
   1053         with dynamicmap_memoization(self.callback, self.streams):
-> 1054             retval = self.callback(*args, **kwargs)
   1055         return self._style(retval)
   1056 

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/core/spaces.py in __call__(self, *args, **kwargs)
    691 
    692         try:
--> 693             ret = self.callable(*args, **kwargs)
    694         except KeyError:
    695             # KeyError is caught separately because it is used to signal

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/util/__init__.py in dynamic_operation(*key, **kwargs)
    983 
    984         def dynamic_operation(*key, **kwargs):
--> 985             key, obj = resolve(key, kwargs)
    986             return apply(obj, *key, **kwargs)
    987 

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/util/__init__.py in resolve(key, kwargs)
    976             elif isinstance(map_obj, DynamicMap) and map_obj._posarg_keys and not key:
    977                 key = tuple(kwargs[k] for k in map_obj._posarg_keys)
--> 978             return key, map_obj[key]
    979 
    980         def apply(element, *key, **kwargs):

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/core/spaces.py in __getitem__(self, key)
   1278         # Not a cross product and nothing cached so compute element.
   1279         if cache is not None: return cache
-> 1280         val = self._execute_callback(*tuple_key)
   1281         if data_slice:
   1282             val = self._dataslice(val, data_slice)

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/core/spaces.py in _execute_callback(self, *args)
   1052 
   1053         with dynamicmap_memoization(self.callback, self.streams):
-> 1054             retval = self.callback(*args, **kwargs)
   1055         return self._style(retval)
   1056 

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/core/spaces.py in __call__(self, *args, **kwargs)
    691 
    692         try:
--> 693             ret = self.callable(*args, **kwargs)
    694         except KeyError:
    695             # KeyError is caught separately because it is used to signal

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/util/__init__.py in dynamic_operation(*key, **kwargs)
    984         def dynamic_operation(*key, **kwargs):
    985             key, obj = resolve(key, kwargs)
--> 986             return apply(obj, *key, **kwargs)
    987 
    988         operation = self.p.operation

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/util/__init__.py in apply(element, *key, **kwargs)
    980         def apply(element, *key, **kwargs):
    981             kwargs = dict(util.resolve_dependent_kwargs(self.p.kwargs), **kwargs)
--> 982             return self._process(element, key, kwargs)
    983 
    984         def dynamic_operation(*key, **kwargs):

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/util/__init__.py in _process(self, element, key, kwargs)
    962         elif isinstance(self.p.operation, Operation):
    963             kwargs = {k: v for k, v in kwargs.items() if k in self.p.operation.param}
--> 964             return self.p.operation.process_element(element, key, **kwargs)
    965         else:
    966             return self.p.operation(element, **kwargs)

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/core/operation.py in process_element(self, element, key, **params)
    170             self.p = param.ParamOverrides(self, params,
    171                                           allow_extra_keywords=self._allow_extra_keywords)
--> 172         return self._apply(element, key)
    173 
    174 

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/core/operation.py in _apply(self, element, key)
    130         element_pipeline = getattr(element, '_pipeline', None)
    131 
--> 132         ret = self._process(element, key)
    133         for hook in self._postprocess_hooks:
    134             ret = hook(self, ret, **kwargs)

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/operation/datashader.py in _process(self, element, key)
   1413                                        if k in transform.param})
   1414             op._precomputed = self._precomputed
-> 1415             element = element.map(op, predicate)
   1416             self._precomputed = op._precomputed
   1417 

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/core/data/__init__.py in pipelined_fn(*args, **kwargs)
    212 
    213             try:
--> 214                 result = method_fn(*args, **kwargs)
    215 
    216                 op = method_op.instance(

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/core/data/__init__.py in map(self, *args, **kwargs)
   1167 
   1168     def map(self, *args, **kwargs):
-> 1169         return super(Dataset, self).map(*args, **kwargs)
   1170     map.__doc__ = LabelledData.map.__doc__
   1171 

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/core/dimension.py in map(self, map_fn, specs, clone)
    703             return deep_mapped
    704         else:
--> 705             return map_fn(self) if applies else self
    706 
    707 

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/core/operation.py in __call__(self, element, **kwargs)
    190             elif ((self._per_element and isinstance(element, Element)) or
    191                   (not self._per_element and isinstance(element, ViewableElement))):
--> 192                 return self._apply(element)
    193         elif 'streams' not in kwargs:
    194             kwargs['streams'] = self.p.streams

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/core/operation.py in _apply(self, element, key)
    130         element_pipeline = getattr(element, '_pipeline', None)
    131 
--> 132         ret = self._process(element, key)
    133         for hook in self._postprocess_hooks:
    134             ret = hook(self, ret, **kwargs)

/srv/conda/envs/pangeo/lib/python3.7/site-packages/holoviews/operation/datashader.py in _process(self, element, key)
   1081 
   1082         vdim = getattr(agg_fn, 'column', element.vdims[0].name)
-> 1083         agg = cvs.quadmesh(data[vdim], x.name, y.name, agg_fn)
   1084         xdim, ydim = list(agg.dims)[:2][::-1]
   1085         if xtype == "datetime":

/srv/conda/envs/pangeo/lib/python3.7/site-packages/datashader/core.py in quadmesh(self, source, x, y, agg)
    770                 dims=list(xarr.dims)))
    771 
--> 772         return bypixel(source, self, glyph, agg)
    773 
    774     # TODO re 'untested', below: Consider replacing with e.g. a 3x3

/srv/conda/envs/pangeo/lib/python3.7/site-packages/datashader/core.py in bypixel(source, canvas, glyph, agg)
   1159     with np.warnings.catch_warnings():
   1160         np.warnings.filterwarnings('ignore', r'All-NaN (slice|axis) encountered')
-> 1161         return bypixel.pipeline(source, schema, canvas, glyph, agg)
   1162 
   1163 

/srv/conda/envs/pangeo/lib/python3.7/site-packages/datashader/utils.py in __call__(self, head, *rest, **kwargs)
     91         typ = type(head)
     92         if typ in lk:
---> 93             return lk[typ](head, *rest, **kwargs)
     94         for cls in getmro(typ)[1:]:
     95             if cls in lk:

/srv/conda/envs/pangeo/lib/python3.7/site-packages/datashader/data_libraries/xarray.py in xarray_pipeline(df, schema, canvas, glyph, summary)
     17 def xarray_pipeline(df, schema, canvas, glyph, summary):
     18     cuda = cupy and isinstance(df[glyph.name].data, cupy.ndarray)
---> 19     return glyph_dispatch(glyph, df, schema, canvas, summary, cuda)
     20 
     21 

/srv/conda/envs/pangeo/lib/python3.7/site-packages/datashader/utils.py in __call__(self, head, *rest, **kwargs)
     94         for cls in getmro(typ)[1:]:
     95             if cls in lk:
---> 96                 return lk[cls](head, *rest, **kwargs)
     97         raise TypeError("No dispatch for {0} type".format(typ))
     98 

/srv/conda/envs/pangeo/lib/python3.7/site-packages/datashader/data_libraries/pandas.py in default(glyph, source, schema, canvas, summary, cuda)
     43 
     44     bases = create((height, width))
---> 45     extend(bases, source, x_st + y_st, x_range + y_range)
     46 
     47     return finalize(bases,

/srv/conda/envs/pangeo/lib/python3.7/site-packages/datashader/glyphs/quadmesh.py in extend(aggs, xr_ds, vt, bounds)
    186                 do_extend = extend_cpu
    187 
--> 188             do_extend(xs, ys, *aggs_and_cols)
    189 
    190         return extend

/srv/conda/envs/pangeo/lib/python3.7/site-packages/numba/dispatcher.py in _compile_for_args(self, *args, **kws)
    399                 e.patch_message(msg)
    400 
--> 401             error_rewrite(e, 'typing')
    402         except errors.UnsupportedError as e:
    403             # Something unsupported is present in the user code, add help info

/srv/conda/envs/pangeo/lib/python3.7/site-packages/numba/dispatcher.py in error_rewrite(e, issue_type)
    342                 raise e
    343             else:
--> 344                 reraise(type(e), e, None)
    345 
    346         argtypes = []

/srv/conda/envs/pangeo/lib/python3.7/site-packages/numba/six.py in reraise(tp, value, tb)
    666             value = tp()
    667         if value.__traceback__ is not tb:
--> 668             raise value.with_traceback(tb)
    669         raise value
    670 

TypingError: Failed in nopython mode pipeline (step: nopython frontend)
non-precise type pyobject
[1] During: typing of argument at <extend_cpu> (4)

File "<extend_cpu>", line 4:
<source missing, REPL/exec in use?>

This error may have been caused by the following argument(s):
- argument 4: cannot determine Numba type of <class 'dask.array.core.Array'>

I recognize that the best place for this issue might be in another repo, but I thought I would try here first.

Thanks for contacting us! Please read and follow these instructions carefully, then delete this introductory text to keep your issue easy to read. Note that the issue tracker is NOT the place for usage questions and technical assistance; post those at Discourse instead. Issues without the required information below may be closed immediately.

ALL software version info

(this library, plus any other relevant software, e.g. bokeh, python, notebook, OS, browser, etc) bokeh 2.0.0, python 3.7.6, hvplot 0.5.2

Description of expected behavior and the observed behavior

hvplot 0.5.2 is not compatible with bokeh 2.0.0, giving the following error message:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/yy939/mgh/miniconda3/envs/pegasus-github/lib/python3.7/site-packages/hvplot/__init__.py", line 12, in <module>
    from .converter import HoloViewsConverter
  File "/Users/yy939/mgh/miniconda3/envs/pegasus-github/lib/python3.7/site-packages/hvplot/converter.py", line 25, in <module>
    from holoviews.plotting.bokeh import OverlayPlot
  File "/Users/yy939/mgh/miniconda3/envs/pegasus-github/lib/python3.7/site-packages/holoviews/plotting/bokeh/__init__.py", line 30, in <module>
    from .annotation import (TextPlot, LineAnnotationPlot, SplinePlot,
  File "/Users/yy939/mgh/miniconda3/envs/pegasus-github/lib/python3.7/site-packages/holoviews/plotting/bokeh/annotation.py", line 23, in <module>
    from .element import AnnotationPlot, ElementPlot, CompositeElementPlot, ColorbarPlot
  File "/Users/yy939/mgh/miniconda3/envs/pegasus-github/lib/python3.7/site-packages/holoviews/plotting/bokeh/element.py", line 23, in <module>
    from bokeh.plotting.helpers import _known_tools as known_tools
ModuleNotFoundError: No module named 'bokeh.plotting.helpers'

But it's compatible with bokeh 1.4.0.

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

pip install --upgrade hvplot
pip install --upgrade bokeh
python
>>> import hvplot

Stack traceback and/or browser JavaScript console output

Screenshots or screencasts of the bug in action

This is an attempt to

• sharpen the elevator pitch
• describe hvPlot as it is today
• Make the communication more engaging using examples and images
• Make it easy to find what you need via menus and links.
• Mention hvPlot as the entry point to the HoloViz ecosystem (See https://github.com/holoviz/hvplot/issues/533).

You can see the README rendered here.

Additional Context

Maybe the rest of the HoloViz ecosystem READMEs could need a similar update?

Versions

hvplot = 0.8.2

Description

the .loc method can take a row plus a column parameter in Pandas. When using an interactive DataFrame, this behavior should be conserved. But when using an interactive boolean Series as the row parameter, specifying a column leads to an error message.

Example

import hvplot.pandas
from bokeh.sampledata.penguins import data as df

dfi = df.interactive()

# ERROR
dfi.loc[dfi['body_mass_g'] > 4000,'bill_length_mm']         #  interactive boolean Series + column

On the other hand, those slight modifications all work.

# normal DataFrame: works
df.loc[df['body_mass_g'] > 4000,'bill_length_mm']           # works: no interactive DataFrame

# interactive DataFrame: variations that work
dfi.loc[[10,11,12],'bill_length_mm']                        # works: list + column
dfi.loc[dfi['body_mass_g'] > 4000]                          # works: interactive boolean Series
dfi.loc[df['body_mass_g'] > 4000,'bill_length_mm']          # works: normal boolean Series + column
dfi.loc[dfi['body_mass_g'] > 4000]['bill_length_mm']        # works: interactive boolean Series, column selected on output

Traceback

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
Input In [33], in <cell line: 8>()
      4 df.loc[df['body_mass_g'] > 4000,'bill_length_mm']
      6 dfi = df.interactive()
----> 8 dfi.loc[dfi['body_mass_g'] > 4000,'bill_length_mm']

File ~/Dropbox/Berry-Vaziri-Collaboration/.venv/lib/python3.9/site-packages/hvplot/interactive.py:634, in Interactive.__getitem__(self, other)
    632 def __getitem__(self, other):
    633     other = other._transform if isinstance(other, Interactive) else other
--> 634     return self._apply_operator(operator.getitem, other)

File ~/Dropbox/Berry-Vaziri-Collaboration/.venv/lib/python3.9/site-packages/hvplot/interactive.py:521, in Interactive._apply_operator(self, operator, reverse, *args, **kwargs)
    519 transform = new._transform
    520 transform = type(transform)(transform, operator, *args, reverse=reverse)
--> 521 return new._clone(transform)

File ~/Dropbox/Berry-Vaziri-Collaboration/.venv/lib/python3.9/site-packages/hvplot/interactive.py:370, in Interactive._clone(self, transform, plot, loc, center, dmap, copy, max_rows, **kwargs)
    368 else:
    369     kwargs = dict(self._inherit_kwargs, **dict(self._kwargs, **kwargs))
--> 370 return type(self)(self._obj, fn=self._fn, transform=transform, plot=plot, depth=depth,
    371                  loc=loc, center=center, dmap=dmap, _shared_obj=self._shared_obj,
    372                  max_rows=max_rows, **kwargs)

File ~/Dropbox/Berry-Vaziri-Collaboration/.venv/lib/python3.9/site-packages/hvplot/interactive.py:276, in Interactive.__init__(self, obj, transform, fn, plot, depth, loc, center, dmap, inherit_kwargs, max_rows, method, _shared_obj, _current, **kwargs)
    274     self._current = _current
    275 else:
--> 276     self._current = self._transform.apply(ds, keep_index=True, compute=False)
    277 self._init = True
    278 self.hvplot = _hvplot(self)

File ~/Dropbox/Berry-Vaziri-Collaboration/.venv/lib/python3.9/site-packages/holoviews/util/transform.py:773, in dim.apply(self, dataset, flat, expanded, ranges, all_values, keep_index, compute, strict)
    771     drange = ranges.get(eldim, {})
    772     drange = drange.get('combined', drange)
--> 773     data = self._apply_fn(dataset, data, fn, fn_name, args,
    774                           kwargs, accessor, drange)
    775 drop_index = keep_index_for_compute and not keep_index
    776 compute = not compute_for_compute and compute

File ~/Dropbox/Berry-Vaziri-Collaboration/.venv/lib/python3.9/site-packages/holoviews/util/transform.py:673, in dim._apply_fn(self, dataset, data, fn, fn_name, args, kwargs, accessor, drange)
    671                 raise e
    672 else:
--> 673     data = fn(*args, **kwargs)
    675 return data

File ~/Dropbox/Berry-Vaziri-Collaboration/.venv/lib/python3.9/site-packages/pandas/core/indexing.py:1065, in _LocationIndexer.__getitem__(self, key)
   1063 if type(key) is tuple:
   1064     key = tuple(list(x) if is_iterator(x) else x for x in key)
-> 1065     key = tuple(com.apply_if_callable(x, self.obj) for x in key)
   1066     if self._is_scalar_access(key):
   1067         return self.obj._get_value(*key, takeable=self._takeable)

File ~/Dropbox/Berry-Vaziri-Collaboration/.venv/lib/python3.9/site-packages/pandas/core/indexing.py:1065, in <genexpr>(.0)
   1063 if type(key) is tuple:
   1064     key = tuple(list(x) if is_iterator(x) else x for x in key)
-> 1065     key = tuple(com.apply_if_callable(x, self.obj) for x in key)
   1066     if self._is_scalar_access(key):
   1067         return self.obj._get_value(*key, takeable=self._takeable)

File ~/Dropbox/Berry-Vaziri-Collaboration/.venv/lib/python3.9/site-packages/pandas/core/common.py:364, in apply_if_callable(maybe_callable, obj, **kwargs)
    353 """
    354 Evaluate possibly callable input using obj and kwargs if it is callable,
    355 otherwise return as it is.
   (...)
    361 **kwargs
    362 """
    363 if callable(maybe_callable):
--> 364     return maybe_callable(obj, **kwargs)
    366 return maybe_callable

File ~/Dropbox/Berry-Vaziri-Collaboration/.venv/lib/python3.9/site-packages/hvplot/interactive.py:490, in Interactive.__call__(self, *args, **kwargs)
    488         return self._clone(*args, **kwargs)
    489     # TODO: When is this error raised?
--> 490     raise AttributeError
    491 elif self._method == 'plot':
    492     # This - {ax: get_ax} - is passed as kwargs to the plot method in
    493     # the dim expression.
    494     kwargs['ax'] = self._get_ax_fn()

AttributeError: 

We should have a developer guide that:

• is easy to approach
• we trust, i.e. we should make sure that it works
• allows users to test hvPlot and to build its site. Let's keep building packages aside for now, as contributors are less likely to do that

The thumbnails in the gallery are mostly generated on the fly by nbsite. While this is useful to make sure they are in sync with the notebook output and it's somewhat easier to maintain, this has a few drawbacks:

• thumbnails should be crafted with care to make the gallery prettier (e.g. they should be squarish)
• it makes the docs build slower
• it makes the docs build more difficult to set up as you need some browser extension to save Bokeh figures

So let's make some nice thumbnails. When they're built, they'll need to be hosted on S3 as done by e.g. Panel for nbsite to fetch them when it builds the site.

nbsite_gallery_conf = {
    ....
    'thumbnail_url': 'https://assets.holoviews.org/panel/thumbnails',
    ...
}

Closes #998.

Please note https://github.com/holoviz/holoviews/pull/5540 closes the issue about the non-understandable error message when trying to hist categorical data.

In addition, I've added more examples to illustrate what is possible.

Comparing to the plotly documentation there is still a long, long way to go https://plotly.com/python/histograms/.

hvplot==0.8.2

Motivated by #998 I'm trying to improve the hist reference guide.

When I try to create a hist plot from a datetime column it works fine as long as I use the matplotlib or bokeh backends. When I start using the plotly backend it raises an exception.

import pandas as pd
from bokeh.sampledata.commits import data
import hvplot.pandas
backend = "plotly"
hvplot.extension(backend)

data=data.reset_index().sort_values("datetime")
plot = data.hvplot.hist(
    "datetime",
    bin_range=(pd.Timestamp('2012-11-30'), pd.Timestamp('2017-05-01')),
    bins=54, 
)

import holoviews as hv
hv.render(plot, backend)

$ python script.py
Traceback (most recent call last):
  File "C:\repos\private\tmp\holoviews\script.py", line 15, in <module>
    hv.render(plot, backend)
  File "C:\repos\private\tmp\holoviews\holoviews\util\__init__.py", line 829, in render
    return renderer_obj.get_plot_state(obj)
  File "C:\repos\private\tmp\holoviews\holoviews\plotting\plotly\renderer.py", line 86, in get_plot_state
    fig_dict = go.Figure(fig_dict).to_dict()
  File "C:\repos\private\hvplot\.venv\lib\site-packages\plotly\graph_objs\_figure.py", line 616, in __init__
    super(Figure, self).__init__(data, layout, frames, skip_invalid, **kwargs)
  File "C:\repos\private\hvplot\.venv\lib\site-packages\plotly\basedatatypes.py", line 514, in __init__
    data = self._data_validator.validate_coerce(
  File "C:\repos\private\hvplot\.venv\lib\site-packages\_plotly_utils\basevalidators.py", line 2668, in validate_coerce
    trace = self.get_trace_class(trace_type)(
  File "C:\repos\private\hvplot\.venv\lib\site-packages\plotly\graph_objs\_bar.py", line 3199, in __init__
    self["width"] = _v
  File "C:\repos\private\hvplot\.venv\lib\site-packages\plotly\basedatatypes.py", line 4859, in __setitem__
    self._set_prop(prop, value)
  File "C:\repos\private\hvplot\.venv\lib\site-packages\plotly\basedatatypes.py", line 5198, in _set_prop
    val = validator.validate_coerce(val)
  File "C:\repos\private\hvplot\.venv\lib\site-packages\_plotly_utils\basevalidators.py", line 803, in validate_coerce
    if not (self.min_val <= v <= self.max_val):
TypeError: The DType <class 'numpy.dtype[timedelta64]'> could not be promoted by <class 'numpy.dtype[float64]'>. This means that no common DType exists for the given inputs. For example they cannot be stored 
in a single array unless the dtype is `object`. The full list of DTypes is: (<class 'numpy.dtype[timedelta64]'>, <class 'numpy.dtype[float64]'>)

Motivated by #998 I'm trying to improve the hist reference guide. As its not very clear which types of data is supported I'm trying to add an example of creating a hist plot from time data. But this seems not possible.

Please support this

import pandas as pd
from bokeh.sampledata.commits import data

data=data.reset_index().sort_values("datetime")
data["time"] = pd.to_datetime(data['time'],format= '%H:%M:%S' ).dt.time
data.hvplot.hist("time")

Traceback (most recent call last):
  File "C:\repos\private\hvplot\.venv\lib\site-packages\IPython\core\interactiveshell.py", line 3433, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "C:\Users\masma\AppData\Local\Temp\ipykernel_40112\2449246375.py", line 1, in <module>
    data.hvplot.hist("time")
  File "c:\repos\private\hvplot\hvplot\plotting\core.py", line 1324, in hist
    return self(kind="hist", x=None, y=y, by=by, **kwds)
  File "c:\repos\private\hvplot\hvplot\plotting\core.py", line 92, in __call__
    return self._get_converter(x, y, kind, **kwds)(kind, x, y)
  File "c:\repos\private\hvplot\hvplot\converter.py", line 1240, in __call__
    obj = method(x, y)
  File "c:\repos\private\hvplot\hvplot\converter.py", line 1820, in hist
    hists = histogram(ds, dimension=y, **hist_opts)
  File "C:\repos\private\hvplot\.venv\lib\site-packages\param\parameterized.py", line 3654, in __new__
    return inst.__call__(*args,**params)
  File "c:\repos\private\tmp\holoviews\holoviews\core\operation.py", line 220, in __call__
    return element.apply(self, **kwargs)
  File "c:\repos\private\tmp\holoviews\holoviews\core\accessors.py", line 45, in pipelined_call
    result = __call__(*args, **kwargs)
  File "c:\repos\private\tmp\holoviews\holoviews\core\accessors.py", line 202, in __call__
    new_obj = apply_function(self._obj, **inner_kwargs)
  File "c:\repos\private\tmp\holoviews\holoviews\core\operation.py", line 214, in __call__
    return self._apply(element)
  File "c:\repos\private\tmp\holoviews\holoviews\core\operation.py", line 141, in _apply
    ret = self._process(element, key)
  File "c:\repos\private\tmp\holoviews\holoviews\operation\element.py", line 726, in _process
    data = data.astype('datetime64[ns]').astype('int64')
ValueError: Could not convert object to NumPy datetime