def __init__(self,
arg=None,
arrangement=None,
bundlecolors=None,
counts=None,
countssrc=None,
dimensions=None,
dimensiondefaults=None,
domain=None,
hoverinfo=None,
hoveron=None,
hovertemplate=None,
labelfont=None,
line=None,
name=None,
sortpaths=None,
stream=None,
tickfont=None,
uid=None,
uirevision=None,
visible=None,
**kwargs):
"""
Construct a new Parcats object
Parallel categories diagram for multidimensional categorical
data.
Parameters
----------
arg
dict of properties compatible with this constructor or
an instance of plotly.graph_objs.Parcats
arrangement
Sets the drag interaction mode for categories and
dimensions. If `perpendicular`, the categories can only
move along a line perpendicular to the paths. If
`freeform`, the categories can freely move on the
plane. If `fixed`, the categories and dimensions are
stationary.
bundlecolors
Sort paths so that like colors are bundled together
within each category.
counts
The number of observations represented by each state.
Defaults to 1 so that each state represents one
observation
countssrc
Sets the source reference on plot.ly for counts .
dimensions
The dimensions (variables) of the parallel categories
diagram.
dimensiondefaults
When used in a template (as
layout.template.data.parcats.dimensiondefaults), sets
the default property values to use for elements of
parcats.dimensions
domain
plotly.graph_objs.parcats.Domain instance or dict with
compatible properties
hoverinfo
Determines which trace information appear on hover. If
`none` or `skip` are set, no information is displayed
upon hovering. But, if `none` is set, click and hover
events are still fired.
hoveron
Sets the hover interaction mode for the parcats
diagram. If `category`, hover interaction take place
per category. If `color`, hover interactions take place
per color per category. If `dimension`, hover
interactions take place across all categories per
dimension.
hovertemplate
Template string used for rendering the information that
appear on hover box. Note that this will override
`hoverinfo`. Variables are inserted using %{variable},
for example "y: %{y}". Numbers are formatted using
d3-format's syntax %{variable:d3-format}, for example
"Price: %{y:$.2f}". See https://github.com/d3/d3-format
/blob/master/README.md#locale_format for details on the
formatting syntax. The variables available in
`hovertemplate` are the ones emitted as event data
described at this link
https://plot.ly/javascript/plotlyjs-events/#event-data.
Additionally, every attributes that can be specified
per-point (the ones that are `arrayOk: true`) are
available. variables `count`, `probability`,
`category`, `categorycount`, `colorcount` and
`bandcolorcount`. Anything contained in tag `<extra>`
is displayed in the secondary box, for example
"<extra>{fullData.name}</extra>".
labelfont
Sets the font for the `dimension` labels.
line
plotly.graph_objs.parcats.Line instance or dict with
compatible properties
name
Sets the trace name. The trace name appear as the
legend item and on hover.
sortpaths
Sets the path sorting algorithm. If `forward`, sort
paths based on dimension categories from left to right.
If `backward`, sort paths based on dimensions
categories from right to left.
stream
plotly.graph_objs.parcats.Stream instance or dict with
compatible properties
tickfont
Sets the font for the `category` labels.
uid
Assign an id to this trace, Use this to provide object
constancy between traces during animations and
transitions.
uirevision
Controls persistence of some user-driven changes to the
trace: `constraintrange` in `parcoords` traces, as well
as some `editable: true` modifications such as `name`
and `colorbar.title`. Defaults to `layout.uirevision`.
Note that other user-driven trace attribute changes are
controlled by `layout` attributes: `trace.visible` is
controlled by `layout.legend.uirevision`,
`selectedpoints` is controlled by
`layout.selectionrevision`, and `colorbar.(x|y)`
(accessible with `config: {editable: true}`) is
controlled by `layout.editrevision`. Trace changes are
tracked by `uid`, which only falls back on trace index
if no `uid` is provided. So if your app can add/remove
traces before the end of the `data` array, such that
the same trace has a different index, you can still
preserve user-driven changes if you give each trace a
`uid` that stays with it as it moves.
visible
Determines whether or not this trace is visible. If
"legendonly", the trace is not drawn, but can appear as
a legend item (provided that the legend itself is
visible).
Returns
-------
Parcats
"""
super(Parcats, self).__init__('parcats')
# Validate arg
# ------------
if arg is None:
arg = {}
elif isinstance(arg, self.__class__):
arg = arg.to_plotly_json()
elif isinstance(arg, dict):
arg = copy.copy(arg)
else:
raise ValueError("""\
The first argument to the plotly.graph_objs.Parcats
constructor must be a dict or
an instance of plotly.graph_objs.Parcats""")
# Handle skip_invalid
# -------------------
self._skip_invalid = kwargs.pop('skip_invalid', False)
# Import validators
# -----------------
from plotly.validators import (parcats as v_parcats)
# Initialize validators
# ---------------------
self._validators['arrangement'] = v_parcats.ArrangementValidator()
self._validators['bundlecolors'] = v_parcats.BundlecolorsValidator()
self._validators['counts'] = v_parcats.CountsValidator()
self._validators['countssrc'] = v_parcats.CountssrcValidator()
self._validators['dimensions'] = v_parcats.DimensionsValidator()
self._validators['dimensiondefaults'] = v_parcats.DimensionValidator()
self._validators['domain'] = v_parcats.DomainValidator()
self._validators['hoverinfo'] = v_parcats.HoverinfoValidator()
self._validators['hoveron'] = v_parcats.HoveronValidator()
self._validators['hovertemplate'] = v_parcats.HovertemplateValidator()
self._validators['labelfont'] = v_parcats.LabelfontValidator()
self._validators['line'] = v_parcats.LineValidator()
self._validators['name'] = v_parcats.NameValidator()
self._validators['sortpaths'] = v_parcats.SortpathsValidator()
self._validators['stream'] = v_parcats.StreamValidator()
self._validators['tickfont'] = v_parcats.TickfontValidator()
self._validators['uid'] = v_parcats.UidValidator()
self._validators['uirevision'] = v_parcats.UirevisionValidator()
self._validators['visible'] = v_parcats.VisibleValidator()
# Populate data dict with properties
# ----------------------------------
_v = arg.pop('arrangement', None)
self['arrangement'] = arrangement if arrangement is not None else _v
_v = arg.pop('bundlecolors', None)
self['bundlecolors'] = bundlecolors if bundlecolors is not None else _v
_v = arg.pop('counts', None)
self['counts'] = counts if counts is not None else _v
_v = arg.pop('countssrc', None)
self['countssrc'] = countssrc if countssrc is not None else _v
_v = arg.pop('dimensions', None)
self['dimensions'] = dimensions if dimensions is not None else _v
_v = arg.pop('dimensiondefaults', None)
self[
'dimensiondefaults'] = dimensiondefaults if dimensiondefaults is not None else _v
_v = arg.pop('domain', None)
self['domain'] = domain if domain is not None else _v
_v = arg.pop('hoverinfo', None)
self['hoverinfo'] = hoverinfo if hoverinfo is not None else _v
_v = arg.pop('hoveron', None)
self['hoveron'] = hoveron if hoveron is not None else _v
_v = arg.pop('hovertemplate', None)
self[
'hovertemplate'] = hovertemplate if hovertemplate is not None else _v
_v = arg.pop('labelfont', None)
self['labelfont'] = labelfont if labelfont is not None else _v
_v = arg.pop('line', None)
self['line'] = line if line is not None else _v
_v = arg.pop('name', None)
self['name'] = name if name is not None else _v
_v = arg.pop('sortpaths', None)
self['sortpaths'] = sortpaths if sortpaths is not None else _v
_v = arg.pop('stream', None)
self['stream'] = stream if stream is not None else _v
_v = arg.pop('tickfont', None)
self['tickfont'] = tickfont if tickfont is not None else _v
_v = arg.pop('uid', None)
self['uid'] = uid if uid is not None else _v
_v = arg.pop('uirevision', None)
self['uirevision'] = uirevision if uirevision is not None else _v
_v = arg.pop('visible', None)
self['visible'] = visible if visible is not None else _v
# Read-only literals
# ------------------
from _plotly_utils.basevalidators import LiteralValidator
self._props['type'] = 'parcats'
self._validators['type'] = LiteralValidator(plotly_name='type',
parent_name='parcats',
val='parcats')
arg.pop('type', None)
# Process unknown kwargs
# ----------------------
self._process_kwargs(**dict(arg, **kwargs))
# Reset skip_invalid
# ------------------
self._skip_invalid = False
def __init__(self,
arg=None,
arrangement=None,
bundlecolors=None,
counts=None,
countssrc=None,
dimensions=None,
dimensiondefaults=None,
domain=None,
hoverinfo=None,
hoveron=None,
labelfont=None,
line=None,
name=None,
sortpaths=None,
stream=None,
tickfont=None,
uid=None,
visible=None,
**kwargs):
"""
Construct a new Parcats object
Parallel categories diagram for multidimensional categorical
data.
Parameters
----------
arg
dict of properties compatible with this constructor or
an instance of plotly.graph_objs.Parcats
arrangement
Sets the drag interaction mode for categories and
dimensions. If `perpendicular`, the categories can only
move along a line perpendicular to the paths. If
`freeform`, the categories can freely move on the
plane. If `fixed`, the categories and dimensions are
stationary.
bundlecolors
Sort paths so that like colors are bundled together
within each category.
counts
The number of observations represented by each state.
Defaults to 1 so that each state represents one
observation
countssrc
Sets the source reference on plot.ly for counts .
dimensions
The dimensions (variables) of the parallel categories
diagram.
dimensiondefaults
When used in a template (as
layout.template.data.parcats.dimensiondefaults), sets
the default property values to use for elements of
parcats.dimensions
domain
plotly.graph_objs.parcats.Domain instance or dict with
compatible properties
hoverinfo
Determines which trace information appear on hover. If
`none` or `skip` are set, no information is displayed
upon hovering. But, if `none` is set, click and hover
events are still fired.
hoveron
Sets the hover interaction mode for the parcats
diagram. If `category`, hover interaction take place
per category. If `color`, hover interactions take place
per color per category. If `dimension`, hover
interactions take place across all categories per
dimension.
labelfont
Sets the font for the `dimension` labels.
line
plotly.graph_objs.parcats.Line instance or dict with
compatible properties
name
Sets the trace name. The trace name appear as the
legend item and on hover.
sortpaths
Sets the path sorting algorithm. If `forward`, sort
paths based on dimension categories from left to right.
If `backward`, sort paths based on dimensions
categories from right to left.
stream
plotly.graph_objs.parcats.Stream instance or dict with
compatible properties
tickfont
Sets the font for the `category` labels.
uid
visible
Determines whether or not this trace is visible. If
"legendonly", the trace is not drawn, but can appear as
a legend item (provided that the legend itself is
visible).
Returns
-------
Parcats
"""
super(Parcats, self).__init__('parcats')
# Validate arg
# ------------
if arg is None:
arg = {}
elif isinstance(arg, self.__class__):
arg = arg.to_plotly_json()
elif isinstance(arg, dict):
arg = copy.copy(arg)
else:
raise ValueError("""\
The first argument to the plotly.graph_objs.Parcats
constructor must be a dict or
an instance of plotly.graph_objs.Parcats""")
# Handle skip_invalid
# -------------------
self._skip_invalid = kwargs.pop('skip_invalid', False)
# Import validators
# -----------------
from plotly.validators import (parcats as v_parcats)
# Initialize validators
# ---------------------
self._validators['arrangement'] = v_parcats.ArrangementValidator()
self._validators['bundlecolors'] = v_parcats.BundlecolorsValidator()
self._validators['counts'] = v_parcats.CountsValidator()
self._validators['countssrc'] = v_parcats.CountssrcValidator()
self._validators['dimensions'] = v_parcats.DimensionsValidator()
self._validators['dimensiondefaults'] = v_parcats.DimensionValidator()
self._validators['domain'] = v_parcats.DomainValidator()
self._validators['hoverinfo'] = v_parcats.HoverinfoValidator()
self._validators['hoveron'] = v_parcats.HoveronValidator()
self._validators['labelfont'] = v_parcats.LabelfontValidator()
self._validators['line'] = v_parcats.LineValidator()
self._validators['name'] = v_parcats.NameValidator()
self._validators['sortpaths'] = v_parcats.SortpathsValidator()
self._validators['stream'] = v_parcats.StreamValidator()
self._validators['tickfont'] = v_parcats.TickfontValidator()
self._validators['uid'] = v_parcats.UidValidator()
self._validators['visible'] = v_parcats.VisibleValidator()
# Populate data dict with properties
# ----------------------------------
_v = arg.pop('arrangement', None)
self['arrangement'] = arrangement if arrangement is not None else _v
_v = arg.pop('bundlecolors', None)
self['bundlecolors'] = bundlecolors if bundlecolors is not None else _v
_v = arg.pop('counts', None)
self['counts'] = counts if counts is not None else _v
_v = arg.pop('countssrc', None)
self['countssrc'] = countssrc if countssrc is not None else _v
_v = arg.pop('dimensions', None)
self['dimensions'] = dimensions if dimensions is not None else _v
_v = arg.pop('dimensiondefaults', None)
self[
'dimensiondefaults'] = dimensiondefaults if dimensiondefaults is not None else _v
_v = arg.pop('domain', None)
self['domain'] = domain if domain is not None else _v
_v = arg.pop('hoverinfo', None)
self['hoverinfo'] = hoverinfo if hoverinfo is not None else _v
_v = arg.pop('hoveron', None)
self['hoveron'] = hoveron if hoveron is not None else _v
_v = arg.pop('labelfont', None)
self['labelfont'] = labelfont if labelfont is not None else _v
_v = arg.pop('line', None)
self['line'] = line if line is not None else _v
_v = arg.pop('name', None)
self['name'] = name if name is not None else _v
_v = arg.pop('sortpaths', None)
self['sortpaths'] = sortpaths if sortpaths is not None else _v
_v = arg.pop('stream', None)
self['stream'] = stream if stream is not None else _v
_v = arg.pop('tickfont', None)
self['tickfont'] = tickfont if tickfont is not None else _v
_v = arg.pop('uid', None)
self['uid'] = uid if uid is not None else _v
_v = arg.pop('visible', None)
self['visible'] = visible if visible is not None else _v
# Read-only literals
# ------------------
from _plotly_utils.basevalidators import LiteralValidator
self._props['type'] = 'parcats'
self._validators['type'] = LiteralValidator(plotly_name='type',
parent_name='parcats',
val='parcats')
arg.pop('type', None)
# Process unknown kwargs
# ----------------------
self._process_kwargs(**dict(arg, **kwargs))
# Reset skip_invalid
# ------------------
self._skip_invalid = False