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wg-backend-django/dell-env/lib/python3.11/site-packages/plotly/graph_objs/_box.py

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Add iptable-parser as submodule
2023-10-30 03:40:43 -04:00
from plotly.basedatatypes import BaseTraceType as _BaseTraceType
import copy as _copy
class Box(_BaseTraceType):
# class properties
# --------------------
_parent_path_str = ""
_path_str = "box"
_valid_props = {
"alignmentgroup",
"boxmean",
"boxpoints",
"customdata",
"customdatasrc",
"dx",
"dy",
"fillcolor",
"hoverinfo",
"hoverinfosrc",
"hoverlabel",
"hoveron",
"hovertemplate",
"hovertemplatesrc",
"hovertext",
"hovertextsrc",
"ids",
"idssrc",
"jitter",
"legend",
"legendgroup",
"legendgrouptitle",
"legendrank",
"legendwidth",
"line",
"lowerfence",
"lowerfencesrc",
"marker",
"mean",
"meansrc",
"median",
"mediansrc",
"meta",
"metasrc",
"name",
"notched",
"notchspan",
"notchspansrc",
"notchwidth",
"offsetgroup",
"opacity",
"orientation",
"pointpos",
"q1",
"q1src",
"q3",
"q3src",
"quartilemethod",
"sd",
"sdmultiple",
"sdsrc",
"selected",
"selectedpoints",
"showlegend",
"showwhiskers",
"sizemode",
"stream",
"text",
"textsrc",
"type",
"uid",
"uirevision",
"unselected",
"upperfence",
"upperfencesrc",
"visible",
"whiskerwidth",
"width",
"x",
"x0",
"xaxis",
"xcalendar",
"xhoverformat",
"xperiod",
"xperiod0",
"xperiodalignment",
"xsrc",
"y",
"y0",
"yaxis",
"ycalendar",
"yhoverformat",
"yperiod",
"yperiod0",
"yperiodalignment",
"ysrc",
}
# alignmentgroup
# --------------
@property
def alignmentgroup(self):
"""
Set several traces linked to the same position axis or matching
axes to the same alignmentgroup. This controls whether bars
compute their positional range dependently or independently.
The 'alignmentgroup' property is a string and must be specified as:
- A string
- A number that will be converted to a string
Returns
-------
str
"""
return self["alignmentgroup"]
@alignmentgroup.setter
def alignmentgroup(self, val):
self["alignmentgroup"] = val
# boxmean
# -------
@property
def boxmean(self):
"""
If True, the mean of the box(es)' underlying distribution is
drawn as a dashed line inside the box(es). If "sd" the standard
deviation is also drawn. Defaults to True when `mean` is set.
Defaults to "sd" when `sd` is set Otherwise defaults to False.
The 'boxmean' property is an enumeration that may be specified as:
- One of the following enumeration values:
[True, 'sd', False]
Returns
-------
Any
"""
return self["boxmean"]
@boxmean.setter
def boxmean(self, val):
self["boxmean"] = val
# boxpoints
# ---------
@property
def boxpoints(self):
"""
If "outliers", only the sample points lying outside the
whiskers are shown If "suspectedoutliers", the outlier points
are shown and points either less than 4*Q1-3*Q3 or greater than
4*Q3-3*Q1 are highlighted (see `outliercolor`) If "all", all
sample points are shown If False, only the box(es) are shown
with no sample points Defaults to "suspectedoutliers" when
`marker.outliercolor` or `marker.line.outliercolor` is set.
Defaults to "all" under the q1/median/q3 signature. Otherwise
defaults to "outliers".
The 'boxpoints' property is an enumeration that may be specified as:
- One of the following enumeration values:
['all', 'outliers', 'suspectedoutliers', False]
Returns
-------
Any
"""
return self["boxpoints"]
@boxpoints.setter
def boxpoints(self, val):
self["boxpoints"] = val
# customdata
# ----------
@property
def customdata(self):
"""
Assigns extra data each datum. This may be useful when
listening to hover, click and selection events. Note that,
"scatter" traces also appends customdata items in the markers
DOM elements
The 'customdata' property is an array that may be specified as a tuple,
list, numpy array, or pandas Series
Returns
-------
numpy.ndarray
"""
return self["customdata"]
@customdata.setter
def customdata(self, val):
self["customdata"] = val
# customdatasrc
# -------------
@property
def customdatasrc(self):
"""
Sets the source reference on Chart Studio Cloud for
`customdata`.
The 'customdatasrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str
"""
return self["customdatasrc"]
@customdatasrc.setter
def customdatasrc(self, val):
self["customdatasrc"] = val
# dx
# --
@property
def dx(self):
"""
Sets the x coordinate step for multi-box traces set using
q1/median/q3.
The 'dx' property is a number and may be specified as:
- An int or float
Returns
-------
int|float
"""
return self["dx"]
@dx.setter
def dx(self, val):
self["dx"] = val
# dy
# --
@property
def dy(self):
"""
Sets the y coordinate step for multi-box traces set using
q1/median/q3.
The 'dy' property is a number and may be specified as:
- An int or float
Returns
-------
int|float
"""
return self["dy"]
@dy.setter
def dy(self, val):
self["dy"] = val
# fillcolor
# ---------
@property
def fillcolor(self):
"""
Sets the fill color. Defaults to a half-transparent variant of
the line color, marker color, or marker line color, whichever
is available.
The 'fillcolor' property is a color and may be specified as:
- A hex string (e.g. '#ff0000')
- An rgb/rgba string (e.g. 'rgb(255,0,0)')
- An hsl/hsla string (e.g. 'hsl(0,100%,50%)')
- An hsv/hsva string (e.g. 'hsv(0,100%,100%)')
- A named CSS color:
aliceblue, antiquewhite, aqua, aquamarine, azure,
beige, bisque, black, blanchedalmond, blue,
blueviolet, brown, burlywood, cadetblue,
chartreuse, chocolate, coral, cornflowerblue,
cornsilk, crimson, cyan, darkblue, darkcyan,
darkgoldenrod, darkgray, darkgrey, darkgreen,
darkkhaki, darkmagenta, darkolivegreen, darkorange,
darkorchid, darkred, darksalmon, darkseagreen,
darkslateblue, darkslategray, darkslategrey,
darkturquoise, darkviolet, deeppink, deepskyblue,
dimgray, dimgrey, dodgerblue, firebrick,
floralwhite, forestgreen, fuchsia, gainsboro,
ghostwhite, gold, goldenrod, gray, grey, green,
greenyellow, honeydew, hotpink, indianred, indigo,
ivory, khaki, lavender, lavenderblush, lawngreen,
lemonchiffon, lightblue, lightcoral, lightcyan,
lightgoldenrodyellow, lightgray, lightgrey,
lightgreen, lightpink, lightsalmon, lightseagreen,
lightskyblue, lightslategray, lightslategrey,
lightsteelblue, lightyellow, lime, limegreen,
linen, magenta, maroon, mediumaquamarine,
mediumblue, mediumorchid, mediumpurple,
mediumseagreen, mediumslateblue, mediumspringgreen,
mediumturquoise, mediumvioletred, midnightblue,
mintcream, mistyrose, moccasin, navajowhite, navy,
oldlace, olive, olivedrab, orange, orangered,
orchid, palegoldenrod, palegreen, paleturquoise,
palevioletred, papayawhip, peachpuff, peru, pink,
plum, powderblue, purple, red, rosybrown,
royalblue, rebeccapurple, saddlebrown, salmon,
sandybrown, seagreen, seashell, sienna, silver,
skyblue, slateblue, slategray, slategrey, snow,
springgreen, steelblue, tan, teal, thistle, tomato,
turquoise, violet, wheat, white, whitesmoke,
yellow, yellowgreen
Returns
-------
str
"""
return self["fillcolor"]
@fillcolor.setter
def fillcolor(self, val):
self["fillcolor"] = val
# hoverinfo
# ---------
@property
def hoverinfo(self):
"""
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.
The 'hoverinfo' property is a flaglist and may be specified
as a string containing:
- Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters
(e.g. 'x+y')
OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip')
- A list or array of the above
Returns
-------
Any|numpy.ndarray
"""
return self["hoverinfo"]
@hoverinfo.setter
def hoverinfo(self, val):
self["hoverinfo"] = val
# hoverinfosrc
# ------------
@property
def hoverinfosrc(self):
"""
Sets the source reference on Chart Studio Cloud for
`hoverinfo`.
The 'hoverinfosrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str
"""
return self["hoverinfosrc"]
@hoverinfosrc.setter
def hoverinfosrc(self, val):
self["hoverinfosrc"] = val
# hoverlabel
# ----------
@property
def hoverlabel(self):
"""
The 'hoverlabel' property is an instance of Hoverlabel
that may be specified as:
- An instance of :class:`plotly.graph_objs.box.Hoverlabel`
- A dict of string/value properties that will be passed
to the Hoverlabel constructor
Supported dict properties:
align
Sets the horizontal alignment of the text
content within hover label box. Has an effect
only if the hover label text spans more two or
more lines
alignsrc
Sets the source reference on Chart Studio Cloud
for `align`.
bgcolor
Sets the background color of the hover labels
for this trace
bgcolorsrc
Sets the source reference on Chart Studio Cloud
for `bgcolor`.
bordercolor
Sets the border color of the hover labels for
this trace.
bordercolorsrc
Sets the source reference on Chart Studio Cloud
for `bordercolor`.
font
Sets the font used in hover labels.
namelength
Sets the default length (in number of
characters) of the trace name in the hover
labels for all traces. -1 shows the whole name
regardless of length. 0-3 shows the first 0-3
characters, and an integer >3 will show the
whole name if it is less than that many
characters, but if it is longer, will truncate
to `namelength - 3` characters and add an
ellipsis.
namelengthsrc
Sets the source reference on Chart Studio Cloud
for `namelength`.
Returns
-------
plotly.graph_objs.box.Hoverlabel
"""
return self["hoverlabel"]
@hoverlabel.setter
def hoverlabel(self, val):
self["hoverlabel"] = val
# hoveron
# -------
@property
def hoveron(self):
"""
Do the hover effects highlight individual boxes or sample
points or both?
The 'hoveron' property is a flaglist and may be specified
as a string containing:
- Any combination of ['boxes', 'points'] joined with '+' characters
(e.g. 'boxes+points')
Returns
-------
Any
"""
return self["hoveron"]
@hoveron.setter
def hoveron(self, val):
self["hoveron"] = val
# hovertemplate
# -------------
@property
def hovertemplate(self):
"""
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}"
as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When
showing info for several points, "xother" will be added to
those with different x positions from the first point. An
underscore before or after "(x|y)other" will add a space on
that side, only when this field is shown. Numbers are formatted
using d3-format's syntax %{variable:d3-format}, for example
"Price: %{y:$.2f}".
https://github.com/d3/d3-format/tree/v1.4.5#d3-format for
details on the formatting syntax. Dates are formatted using
d3-time-format's syntax %{variable|d3-time-format}, for example
"Day: %{2019-01-01|%A}". https://github.com/d3/d3-time-
format/tree/v2.2.3#locale_format for details on the date
formatting syntax. The variables available in `hovertemplate`
are the ones emitted as event data described at this link
https://plotly.com/javascript/plotlyjs-events/#event-data.
Additionally, every attributes that can be specified per-point
(the ones that are `arrayOk: true`) are available. Anything
contained in tag `<extra>` is displayed in the secondary box,
for example "<extra>{fullData.name}</extra>". To hide the
secondary box completely, use an empty tag `<extra></extra>`.
The 'hovertemplate' property is a string and must be specified as:
- A string
- A number that will be converted to a string
- A tuple, list, or one-dimensional numpy array of the above
Returns
-------
str|numpy.ndarray
"""
return self["hovertemplate"]
@hovertemplate.setter
def hovertemplate(self, val):
self["hovertemplate"] = val
# hovertemplatesrc
# ----------------
@property
def hovertemplatesrc(self):
"""
Sets the source reference on Chart Studio Cloud for
`hovertemplate`.
The 'hovertemplatesrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str
"""
return self["hovertemplatesrc"]
@hovertemplatesrc.setter
def hovertemplatesrc(self, val):
self["hovertemplatesrc"] = val
# hovertext
# ---------
@property
def hovertext(self):
"""
Same as `text`.
The 'hovertext' property is a string and must be specified as:
- A string
- A number that will be converted to a string
- A tuple, list, or one-dimensional numpy array of the above
Returns
-------
str|numpy.ndarray
"""
return self["hovertext"]
@hovertext.setter
def hovertext(self, val):
self["hovertext"] = val
# hovertextsrc
# ------------
@property
def hovertextsrc(self):
"""
Sets the source reference on Chart Studio Cloud for
`hovertext`.
The 'hovertextsrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str
"""
return self["hovertextsrc"]
@hovertextsrc.setter
def hovertextsrc(self, val):
self["hovertextsrc"] = val
# ids
# ---
@property
def ids(self):
"""
Assigns id labels to each datum. These ids for object constancy
of data points during animation. Should be an array of strings,
not numbers or any other type.
The 'ids' property is an array that may be specified as a tuple,
list, numpy array, or pandas Series
Returns
-------
numpy.ndarray
"""
return self["ids"]
@ids.setter
def ids(self, val):
self["ids"] = val
# idssrc
# ------
@property
def idssrc(self):
"""
Sets the source reference on Chart Studio Cloud for `ids`.
The 'idssrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str
"""
return self["idssrc"]
@idssrc.setter
def idssrc(self, val):
self["idssrc"] = val
# jitter
# ------
@property
def jitter(self):
"""
Sets the amount of jitter in the sample points drawn. If 0, the
sample points align along the distribution axis. If 1, the
sample points are drawn in a random jitter of width equal to
the width of the box(es).
The 'jitter' property is a number and may be specified as:
- An int or float in the interval [0, 1]
Returns
-------
int|float
"""
return self["jitter"]
@jitter.setter
def jitter(self, val):
self["jitter"] = val
# legend
# ------
@property
def legend(self):
"""
Sets the reference to a legend to show this trace in.
References to these legends are "legend", "legend2", "legend3",
etc. Settings for these legends are set in the layout, under
`layout.legend`, `layout.legend2`, etc.
The 'legend' property is an identifier of a particular
subplot, of type 'legend', that may be specified as the string 'legend'
optionally followed by an integer >= 1
(e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.)
Returns
-------
str
"""
return self["legend"]
@legend.setter
def legend(self, val):
self["legend"] = val
# legendgroup
# -----------
@property
def legendgroup(self):
"""
Sets the legend group for this trace. Traces and shapes part of
the same legend group hide/show at the same time when toggling
legend items.
The 'legendgroup' property is a string and must be specified as:
- A string
- A number that will be converted to a string
Returns
-------
str
"""
return self["legendgroup"]
@legendgroup.setter
def legendgroup(self, val):
self["legendgroup"] = val
# legendgrouptitle
# ----------------
@property
def legendgrouptitle(self):
"""
The 'legendgrouptitle' property is an instance of Legendgrouptitle
that may be specified as:
- An instance of :class:`plotly.graph_objs.box.Legendgrouptitle`
- A dict of string/value properties that will be passed
to the Legendgrouptitle constructor
Supported dict properties:
font
Sets this legend group's title font.
text
Sets the title of the legend group.
Returns
-------
plotly.graph_objs.box.Legendgrouptitle
"""
return self["legendgrouptitle"]
@legendgrouptitle.setter
def legendgrouptitle(self, val):
self["legendgrouptitle"] = val
# legendrank
# ----------
@property
def legendrank(self):
"""
Sets the legend rank for this trace. Items and groups with
smaller ranks are presented on top/left side while with
"reversed" `legend.traceorder` they are on bottom/right side.
The default legendrank is 1000, so that you can use ranks less
than 1000 to place certain items before all unranked items, and
ranks greater than 1000 to go after all unranked items. When
having unranked or equal rank items shapes would be displayed
after traces i.e. according to their order in data and layout.
The 'legendrank' property is a number and may be specified as:
- An int or float
Returns
-------
int|float
"""
return self["legendrank"]
@legendrank.setter
def legendrank(self, val):
self["legendrank"] = val
# legendwidth
# -----------
@property
def legendwidth(self):
"""
Sets the width (in px or fraction) of the legend for this
trace.
The 'legendwidth' property is a number and may be specified as:
- An int or float in the interval [0, inf]
Returns
-------
int|float
"""
return self["legendwidth"]
@legendwidth.setter
def legendwidth(self, val):
self["legendwidth"] = val
# line
# ----
@property
def line(self):
"""
The 'line' property is an instance of Line
that may be specified as:
- An instance of :class:`plotly.graph_objs.box.Line`
- A dict of string/value properties that will be passed
to the Line constructor
Supported dict properties:
color
Sets the color of line bounding the box(es).
width
Sets the width (in px) of line bounding the
box(es).
Returns
-------
plotly.graph_objs.box.Line
"""
return self["line"]
@line.setter
def line(self, val):
self["line"] = val
# lowerfence
# ----------
@property
def lowerfence(self):
"""
Sets the lower fence values. There should be as many items as
the number of boxes desired. This attribute has effect only
under the q1/median/q3 signature. If `lowerfence` is not
provided but a sample (in `y` or `x`) is set, we compute the
lower as the last sample point below 1.5 times the IQR.
The 'lowerfence' property is an array that may be specified as a tuple,
list, numpy array, or pandas Series
Returns
-------
numpy.ndarray
"""
return self["lowerfence"]
@lowerfence.setter
def lowerfence(self, val):
self["lowerfence"] = val
# lowerfencesrc
# -------------
@property
def lowerfencesrc(self):
"""
Sets the source reference on Chart Studio Cloud for
`lowerfence`.
The 'lowerfencesrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str
"""
return self["lowerfencesrc"]
@lowerfencesrc.setter
def lowerfencesrc(self, val):
self["lowerfencesrc"] = val
# marker
# ------
@property
def marker(self):
"""
The 'marker' property is an instance of Marker
that may be specified as:
- An instance of :class:`plotly.graph_objs.box.Marker`
- A dict of string/value properties that will be passed
to the Marker constructor
Supported dict properties:
angle
Sets the marker angle in respect to `angleref`.
color
Sets the marker color. It accepts either a
specific color or an array of numbers that are
mapped to the colorscale relative to the max
and min values of the array or relative to
`marker.cmin` and `marker.cmax` if set.
line
:class:`plotly.graph_objects.box.marker.Line`
instance or dict with compatible properties
opacity
Sets the marker opacity.
outliercolor
Sets the color of the outlier sample points.
size
Sets the marker size (in px).
symbol
Sets the marker symbol type. Adding 100 is
equivalent to appending "-open" to a symbol
name. Adding 200 is equivalent to appending
"-dot" to a symbol name. Adding 300 is
equivalent to appending "-open-dot" or "dot-
open" to a symbol name.
Returns
-------
plotly.graph_objs.box.Marker
"""
return self["marker"]
@marker.setter
def marker(self, val):
self["marker"] = val
# mean
# ----
@property
def mean(self):
"""
Sets the mean values. There should be as many items as the
number of boxes desired. This attribute has effect only under
the q1/median/q3 signature. If `mean` is not provided but a
sample (in `y` or `x`) is set, we compute the mean for each box
using the sample values.
The 'mean' property is an array that may be specified as a tuple,
list, numpy array, or pandas Series
Returns
-------
numpy.ndarray
"""
return self["mean"]
@mean.setter
def mean(self, val):
self["mean"] = val
# meansrc
# -------
@property
def meansrc(self):
"""
Sets the source reference on Chart Studio Cloud for `mean`.
The 'meansrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str
"""
return self["meansrc"]
@meansrc.setter
def meansrc(self, val):
self["meansrc"] = val
# median
# ------
@property
def median(self):
"""
Sets the median values. There should be as many items as the
number of boxes desired.
The 'median' property is an array that may be specified as a tuple,
list, numpy array, or pandas Series
Returns
-------
numpy.ndarray
"""
return self["median"]
@median.setter
def median(self, val):
self["median"] = val
# mediansrc
# ---------
@property
def mediansrc(self):
"""
Sets the source reference on Chart Studio Cloud for `median`.
The 'mediansrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str
"""
return self["mediansrc"]
@mediansrc.setter
def mediansrc(self, val):
self["mediansrc"] = val
# meta
# ----
@property
def meta(self):
"""
Assigns extra meta information associated with this trace that
can be used in various text attributes. Attributes such as
trace `name`, graph, axis and colorbar `title.text`, annotation
`text` `rangeselector`, `updatemenues` and `sliders` `label`
text all support `meta`. To access the trace `meta` values in
an attribute in the same trace, simply use `%{meta[i]}` where
`i` is the index or key of the `meta` item in question. To
access trace `meta` in layout attributes, use
`%{data[n[.meta[i]}` where `i` is the index or key of the
`meta` and `n` is the trace index.
The 'meta' property accepts values of any type
Returns
-------
Any|numpy.ndarray
"""
return self["meta"]
@meta.setter
def meta(self, val):
self["meta"] = val
# metasrc
# -------
@property
def metasrc(self):
"""
Sets the source reference on Chart Studio Cloud for `meta`.
The 'metasrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str
"""
return self["metasrc"]
@metasrc.setter
def metasrc(self, val):
self["metasrc"] = val
# name
# ----
@property
def name(self):
"""
Sets the trace name. The trace name appears as the legend item
and on hover. For box traces, the name will also be used for
the position coordinate, if `x` and `x0` (`y` and `y0` if
horizontal) are missing and the position axis is categorical
The 'name' property is a string and must be specified as:
- A string
- A number that will be converted to a string
Returns
-------
str
"""
return self["name"]
@name.setter
def name(self, val):
self["name"] = val
# notched
# -------
@property
def notched(self):
"""
Determines whether or not notches are drawn. Notches displays a
confidence interval around the median. We compute the
confidence interval as median +/- 1.57 * IQR / sqrt(N), where
IQR is the interquartile range and N is the sample size. If two
boxes' notches do not overlap there is 95% confidence their
medians differ. See
https://sites.google.com/site/davidsstatistics/home/notched-
box-plots for more info. Defaults to False unless `notchwidth`
or `notchspan` is set.
The 'notched' property must be specified as a bool
(either True, or False)
Returns
-------
bool
"""
return self["notched"]
@notched.setter
def notched(self, val):
self["notched"] = val
# notchspan
# ---------
@property
def notchspan(self):
"""
Sets the notch span from the boxes' `median` values. There
should be as many items as the number of boxes desired. This
attribute has effect only under the q1/median/q3 signature. If
`notchspan` is not provided but a sample (in `y` or `x`) is
set, we compute it as 1.57 * IQR / sqrt(N), where N is the
sample size.
The 'notchspan' property is an array that may be specified as a tuple,
list, numpy array, or pandas Series
Returns
-------
numpy.ndarray
"""
return self["notchspan"]
@notchspan.setter
def notchspan(self, val):
self["notchspan"] = val
# notchspansrc
# ------------
@property
def notchspansrc(self):
"""
Sets the source reference on Chart Studio Cloud for
`notchspan`.
The 'notchspansrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str
"""
return self["notchspansrc"]
@notchspansrc.setter
def notchspansrc(self, val):
self["notchspansrc"] = val
# notchwidth
# ----------
@property
def notchwidth(self):
"""
Sets the width of the notches relative to the box' width. For
example, with 0, the notches are as wide as the box(es).
The 'notchwidth' property is a number and may be specified as:
- An int or float in the interval [0, 0.5]
Returns
-------
int|float
"""
return self["notchwidth"]
@notchwidth.setter
def notchwidth(self, val):
self["notchwidth"] = val
# offsetgroup
# -----------
@property
def offsetgroup(self):
"""
Set several traces linked to the same position axis or matching
axes to the same offsetgroup where bars of the same position
coordinate will line up.
The 'offsetgroup' property is a string and must be specified as:
- A string
- A number that will be converted to a string
Returns
-------
str
"""
return self["offsetgroup"]
@offsetgroup.setter
def offsetgroup(self, val):
self["offsetgroup"] = val
# opacity
# -------
@property
def opacity(self):
"""
Sets the opacity of the trace.
The 'opacity' property is a number and may be specified as:
- An int or float in the interval [0, 1]
Returns
-------
int|float
"""
return self["opacity"]
@opacity.setter
def opacity(self, val):
self["opacity"] = val
# orientation
# -----------
@property
def orientation(self):
"""
Sets the orientation of the box(es). If "v" ("h"), the
distribution is visualized along the vertical (horizontal).
The 'orientation' property is an enumeration that may be specified as:
- One of the following enumeration values:
['v', 'h']
Returns
-------
Any
"""
return self["orientation"]
@orientation.setter
def orientation(self, val):
self["orientation"] = val
# pointpos
# --------
@property
def pointpos(self):
"""
Sets the position of the sample points in relation to the
box(es). If 0, the sample points are places over the center of
the box(es). Positive (negative) values correspond to positions
to the right (left) for vertical boxes and above (below) for
horizontal boxes
The 'pointpos' property is a number and may be specified as:
- An int or float in the interval [-2, 2]
Returns
-------
int|float
"""
return self["pointpos"]
@pointpos.setter
def pointpos(self, val):
self["pointpos"] = val
# q1
# --
@property
def q1(self):
"""
Sets the Quartile 1 values. There should be as many items as
the number of boxes desired.
The 'q1' property is an array that may be specified as a tuple,
list, numpy array, or pandas Series
Returns
-------
numpy.ndarray
"""
return self["q1"]
@q1.setter
def q1(self, val):
self["q1"] = val
# q1src
# -----
@property
def q1src(self):
"""
Sets the source reference on Chart Studio Cloud for `q1`.
The 'q1src' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str
"""
return self["q1src"]
@q1src.setter
def q1src(self, val):
self["q1src"] = val
# q3
# --
@property
def q3(self):
"""
Sets the Quartile 3 values. There should be as many items as
the number of boxes desired.
The 'q3' property is an array that may be specified as a tuple,
list, numpy array, or pandas Series
Returns
-------
numpy.ndarray
"""
return self["q3"]
@q3.setter
def q3(self, val):
self["q3"] = val
# q3src
# -----
@property
def q3src(self):
"""
Sets the source reference on Chart Studio Cloud for `q3`.
The 'q3src' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str
"""
return self["q3src"]
@q3src.setter
def q3src(self, val):
self["q3src"] = val
# quartilemethod
# --------------
@property
def quartilemethod(self):
"""
Sets the method used to compute the sample's Q1 and Q3
quartiles. The "linear" method uses the 25th percentile for Q1
and 75th percentile for Q3 as computed using method #10 (listed
on http://jse.amstat.org/v14n3/langford.html). The "exclusive"
method uses the median to divide the ordered dataset into two
halves if the sample is odd, it does not include the median in
either half - Q1 is then the median of the lower half and Q3
the median of the upper half. The "inclusive" method also uses
the median to divide the ordered dataset into two halves but if
the sample is odd, it includes the median in both halves - Q1
is then the median of the lower half and Q3 the median of the
upper half.
The 'quartilemethod' property is an enumeration that may be specified as:
- One of the following enumeration values:
['linear', 'exclusive', 'inclusive']
Returns
-------
Any
"""
return self["quartilemethod"]
@quartilemethod.setter
def quartilemethod(self, val):
self["quartilemethod"] = val
# sd
# --
@property
def sd(self):
"""
Sets the standard deviation values. There should be as many
items as the number of boxes desired. This attribute has effect
only under the q1/median/q3 signature. If `sd` is not provided
but a sample (in `y` or `x`) is set, we compute the standard
deviation for each box using the sample values.
The 'sd' property is an array that may be specified as a tuple,
list, numpy array, or pandas Series
Returns
-------
numpy.ndarray
"""
return self["sd"]
@sd.setter
def sd(self, val):
self["sd"] = val
# sdmultiple
# ----------
@property
def sdmultiple(self):
"""
Scales the box size when sizemode=sd Allowing boxes to be drawn
across any stddev range For example 1-stddev, 3-stddev,
5-stddev
The 'sdmultiple' property is a number and may be specified as:
- An int or float in the interval [0, inf]
Returns
-------
int|float
"""
return self["sdmultiple"]
@sdmultiple.setter
def sdmultiple(self, val):
self["sdmultiple"] = val
# sdsrc
# -----
@property
def sdsrc(self):
"""
Sets the source reference on Chart Studio Cloud for `sd`.
The 'sdsrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str
"""
return self["sdsrc"]
@sdsrc.setter
def sdsrc(self, val):
self["sdsrc"] = val
# selected
# --------
@property
def selected(self):
"""
The 'selected' property is an instance of Selected
that may be specified as:
- An instance of :class:`plotly.graph_objs.box.Selected`
- A dict of string/value properties that will be passed
to the Selected constructor
Supported dict properties:
marker
:class:`plotly.graph_objects.box.selected.Marke
r` instance or dict with compatible properties
Returns
-------
plotly.graph_objs.box.Selected
"""
return self["selected"]
@selected.setter
def selected(self, val):
self["selected"] = val
# selectedpoints
# --------------
@property
def selectedpoints(self):
"""
Array containing integer indices of selected points. Has an
effect only for traces that support selections. Note that an
empty array means an empty selection where the `unselected` are
turned on for all points, whereas, any other non-array values
means no selection all where the `selected` and `unselected`
styles have no effect.
The 'selectedpoints' property accepts values of any type
Returns
-------
Any
"""
return self["selectedpoints"]
@selectedpoints.setter
def selectedpoints(self, val):
self["selectedpoints"] = val
# showlegend
# ----------
@property
def showlegend(self):
"""
Determines whether or not an item corresponding to this trace
is shown in the legend.
The 'showlegend' property must be specified as a bool
(either True, or False)
Returns
-------
bool
"""
return self["showlegend"]
@showlegend.setter
def showlegend(self, val):
self["showlegend"] = val
# showwhiskers
# ------------
@property
def showwhiskers(self):
"""
Determines whether or not whiskers are visible. Defaults to
true for `sizemode` "quartiles", false for "sd".
The 'showwhiskers' property must be specified as a bool
(either True, or False)
Returns
-------
bool
"""
return self["showwhiskers"]
@showwhiskers.setter
def showwhiskers(self, val):
self["showwhiskers"] = val
# sizemode
# --------
@property
def sizemode(self):
"""
Sets the upper and lower bound for the boxes quartiles means
box is drawn between Q1 and Q3 SD means the box is drawn
between Mean +- Standard Deviation Argument sdmultiple (default
1) to scale the box size So it could be drawn 1-stddev,
3-stddev etc
The 'sizemode' property is an enumeration that may be specified as:
- One of the following enumeration values:
['quartiles', 'sd']
Returns
-------
Any
"""
return self["sizemode"]
@sizemode.setter
def sizemode(self, val):
self["sizemode"] = val
# stream
# ------
@property
def stream(self):
"""
The 'stream' property is an instance of Stream
that may be specified as:
- An instance of :class:`plotly.graph_objs.box.Stream`
- A dict of string/value properties that will be passed
to the Stream constructor
Supported dict properties:
maxpoints
Sets the maximum number of points to keep on
the plots from an incoming stream. If
`maxpoints` is set to 50, only the newest 50
points will be displayed on the plot.
token
The stream id number links a data trace on a
plot with a stream. See https://chart-
studio.plotly.com/settings for more details.
Returns
-------
plotly.graph_objs.box.Stream
"""
return self["stream"]
@stream.setter
def stream(self, val):
self["stream"] = val
# text
# ----
@property
def text(self):
"""
Sets the text elements associated with each sample value. If a
single string, the same string appears over all the data
points. If an array of string, the items are mapped in order to
the this trace's (x,y) coordinates. To be seen, trace
`hoverinfo` must contain a "text" flag.
The 'text' property is a string and must be specified as:
- A string
- A number that will be converted to a string
- A tuple, list, or one-dimensional numpy array of the above
Returns
-------
str|numpy.ndarray
"""
return self["text"]
@text.setter
def text(self, val):
self["text"] = val
# textsrc
# -------
@property
def textsrc(self):
"""
Sets the source reference on Chart Studio Cloud for `text`.
The 'textsrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str
"""
return self["textsrc"]
@textsrc.setter
def textsrc(self, val):
self["textsrc"] = val
# uid
# ---
@property
def uid(self):
"""
Assign an id to this trace, Use this to provide object
constancy between traces during animations and transitions.
The 'uid' property is a string and must be specified as:
- A string
- A number that will be converted to a string
Returns
-------
str
"""
return self["uid"]
@uid.setter
def uid(self, val):
self["uid"] = val
# uirevision
# ----------
@property
def uirevision(self):
"""
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.
The 'uirevision' property accepts values of any type
Returns
-------
Any
"""
return self["uirevision"]
@uirevision.setter
def uirevision(self, val):
self["uirevision"] = val
# unselected
# ----------
@property
def unselected(self):
"""
The 'unselected' property is an instance of Unselected
that may be specified as:
- An instance of :class:`plotly.graph_objs.box.Unselected`
- A dict of string/value properties that will be passed
to the Unselected constructor
Supported dict properties:
marker
:class:`plotly.graph_objects.box.unselected.Mar
ker` instance or dict with compatible
properties
Returns
-------
plotly.graph_objs.box.Unselected
"""
return self["unselected"]
@unselected.setter
def unselected(self, val):
self["unselected"] = val
# upperfence
# ----------
@property
def upperfence(self):
"""
Sets the upper fence values. There should be as many items as
the number of boxes desired. This attribute has effect only
under the q1/median/q3 signature. If `upperfence` is not
provided but a sample (in `y` or `x`) is set, we compute the
lower as the last sample point above 1.5 times the IQR.
The 'upperfence' property is an array that may be specified as a tuple,
list, numpy array, or pandas Series
Returns
-------
numpy.ndarray
"""
return self["upperfence"]
@upperfence.setter
def upperfence(self, val):
self["upperfence"] = val
# upperfencesrc
# -------------
@property
def upperfencesrc(self):
"""
Sets the source reference on Chart Studio Cloud for
`upperfence`.
The 'upperfencesrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str
"""
return self["upperfencesrc"]
@upperfencesrc.setter
def upperfencesrc(self, val):
self["upperfencesrc"] = val
# visible
# -------
@property
def visible(self):
"""
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).
The 'visible' property is an enumeration that may be specified as:
- One of the following enumeration values:
[True, False, 'legendonly']
Returns
-------
Any
"""
return self["visible"]
@visible.setter
def visible(self, val):
self["visible"] = val
# whiskerwidth
# ------------
@property
def whiskerwidth(self):
"""
Sets the width of the whiskers relative to the box' width. For
example, with 1, the whiskers are as wide as the box(es).
The 'whiskerwidth' property is a number and may be specified as:
- An int or float in the interval [0, 1]
Returns
-------
int|float
"""
return self["whiskerwidth"]
@whiskerwidth.setter
def whiskerwidth(self, val):
self["whiskerwidth"] = val
# width
# -----
@property
def width(self):
"""
Sets the width of the box in data coordinate If 0 (default
value) the width is automatically selected based on the
positions of other box traces in the same subplot.
The 'width' property is a number and may be specified as:
- An int or float in the interval [0, inf]
Returns
-------
int|float
"""
return self["width"]
@width.setter
def width(self, val):
self["width"] = val
# x
# -
@property
def x(self):
"""
Sets the x sample data or coordinates. See overview for more
info.
The 'x' property is an array that may be specified as a tuple,
list, numpy array, or pandas Series
Returns
-------
numpy.ndarray
"""
return self["x"]
@x.setter
def x(self, val):
self["x"] = val
# x0
# --
@property
def x0(self):
"""
Sets the x coordinate for single-box traces or the starting
coordinate for multi-box traces set using q1/median/q3. See
overview for more info.
The 'x0' property accepts values of any type
Returns
-------
Any
"""
return self["x0"]
@x0.setter
def x0(self, val):
self["x0"] = val
# xaxis
# -----
@property
def xaxis(self):
"""
Sets a reference between this trace's x coordinates and a 2D
cartesian x axis. If "x" (the default value), the x coordinates
refer to `layout.xaxis`. If "x2", the x coordinates refer to
`layout.xaxis2`, and so on.
The 'xaxis' property is an identifier of a particular
subplot, of type 'x', that may be specified as the string 'x'
optionally followed by an integer >= 1
(e.g. 'x', 'x1', 'x2', 'x3', etc.)
Returns
-------
str
"""
return self["xaxis"]
@xaxis.setter
def xaxis(self, val):
self["xaxis"] = val
# xcalendar
# ---------
@property
def xcalendar(self):
"""
Sets the calendar system to use with `x` date data.
The 'xcalendar' property is an enumeration that may be specified as:
- One of the following enumeration values:
['chinese', 'coptic', 'discworld', 'ethiopian',
'gregorian', 'hebrew', 'islamic', 'jalali', 'julian',
'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan',
'thai', 'ummalqura']
Returns
-------
Any
"""
return self["xcalendar"]
@xcalendar.setter
def xcalendar(self, val):
self["xcalendar"] = val
# xhoverformat
# ------------
@property
def xhoverformat(self):
"""
Sets the hover text formatting rulefor `x` using d3 formatting
mini-languages which are very similar to those in Python. For
numbers, see:
https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for
dates see: https://github.com/d3/d3-time-
format/tree/v2.2.3#locale_format. We add two items to d3's date
formatter: "%h" for half of the year as a decimal number as
well as "%{n}f" for fractional seconds with n digits. For
example, *2016-10-13 09:15:23.456* with tickformat
"%H~%M~%S.%2f" would display *09~15~23.46*By default the values
are formatted using `xaxis.hoverformat`.
The 'xhoverformat' property is a string and must be specified as:
- A string
- A number that will be converted to a string
Returns
-------
str
"""
return self["xhoverformat"]
@xhoverformat.setter
def xhoverformat(self, val):
self["xhoverformat"] = val
# xperiod
# -------
@property
def xperiod(self):
"""
Only relevant when the axis `type` is "date". Sets the period
positioning in milliseconds or "M<n>" on the x axis. Special
values in the form of "M<n>" could be used to declare the
number of months. In this case `n` must be a positive integer.
The 'xperiod' property accepts values of any type
Returns
-------
Any
"""
return self["xperiod"]
@xperiod.setter
def xperiod(self, val):
self["xperiod"] = val
# xperiod0
# --------
@property
def xperiod0(self):
"""
Only relevant when the axis `type` is "date". Sets the base for
period positioning in milliseconds or date string on the x0
axis. When `x0period` is round number of weeks, the `x0period0`
by default would be on a Sunday i.e. 2000-01-02, otherwise it
would be at 2000-01-01.
The 'xperiod0' property accepts values of any type
Returns
-------
Any
"""
return self["xperiod0"]
@xperiod0.setter
def xperiod0(self, val):
self["xperiod0"] = val
# xperiodalignment
# ----------------
@property
def xperiodalignment(self):
"""
Only relevant when the axis `type` is "date". Sets the
alignment of data points on the x axis.
The 'xperiodalignment' property is an enumeration that may be specified as:
- One of the following enumeration values:
['start', 'middle', 'end']
Returns
-------
Any
"""
return self["xperiodalignment"]
@xperiodalignment.setter
def xperiodalignment(self, val):
self["xperiodalignment"] = val
# xsrc
# ----
@property
def xsrc(self):
"""
Sets the source reference on Chart Studio Cloud for `x`.
The 'xsrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str
"""
return self["xsrc"]
@xsrc.setter
def xsrc(self, val):
self["xsrc"] = val
# y
# -
@property
def y(self):
"""
Sets the y sample data or coordinates. See overview for more
info.
The 'y' property is an array that may be specified as a tuple,
list, numpy array, or pandas Series
Returns
-------
numpy.ndarray
"""
return self["y"]
@y.setter
def y(self, val):
self["y"] = val
# y0
# --
@property
def y0(self):
"""
Sets the y coordinate for single-box traces or the starting
coordinate for multi-box traces set using q1/median/q3. See
overview for more info.
The 'y0' property accepts values of any type
Returns
-------
Any
"""
return self["y0"]
@y0.setter
def y0(self, val):
self["y0"] = val
# yaxis
# -----
@property
def yaxis(self):
"""
Sets a reference between this trace's y coordinates and a 2D
cartesian y axis. If "y" (the default value), the y coordinates
refer to `layout.yaxis`. If "y2", the y coordinates refer to
`layout.yaxis2`, and so on.
The 'yaxis' property is an identifier of a particular
subplot, of type 'y', that may be specified as the string 'y'
optionally followed by an integer >= 1
(e.g. 'y', 'y1', 'y2', 'y3', etc.)
Returns
-------
str
"""
return self["yaxis"]
@yaxis.setter
def yaxis(self, val):
self["yaxis"] = val
# ycalendar
# ---------
@property
def ycalendar(self):
"""
Sets the calendar system to use with `y` date data.
The 'ycalendar' property is an enumeration that may be specified as:
- One of the following enumeration values:
['chinese', 'coptic', 'discworld', 'ethiopian',
'gregorian', 'hebrew', 'islamic', 'jalali', 'julian',
'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan',
'thai', 'ummalqura']
Returns
-------
Any
"""
return self["ycalendar"]
@ycalendar.setter
def ycalendar(self, val):
self["ycalendar"] = val
# yhoverformat
# ------------
@property
def yhoverformat(self):
"""
Sets the hover text formatting rulefor `y` using d3 formatting
mini-languages which are very similar to those in Python. For
numbers, see:
https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for
dates see: https://github.com/d3/d3-time-
format/tree/v2.2.3#locale_format. We add two items to d3's date
formatter: "%h" for half of the year as a decimal number as
well as "%{n}f" for fractional seconds with n digits. For
example, *2016-10-13 09:15:23.456* with tickformat
"%H~%M~%S.%2f" would display *09~15~23.46*By default the values
are formatted using `yaxis.hoverformat`.
The 'yhoverformat' property is a string and must be specified as:
- A string
- A number that will be converted to a string
Returns
-------
str
"""
return self["yhoverformat"]
@yhoverformat.setter
def yhoverformat(self, val):
self["yhoverformat"] = val
# yperiod
# -------
@property
def yperiod(self):
"""
Only relevant when the axis `type` is "date". Sets the period
positioning in milliseconds or "M<n>" on the y axis. Special
values in the form of "M<n>" could be used to declare the
number of months. In this case `n` must be a positive integer.
The 'yperiod' property accepts values of any type
Returns
-------
Any
"""
return self["yperiod"]
@yperiod.setter
def yperiod(self, val):
self["yperiod"] = val
# yperiod0
# --------
@property
def yperiod0(self):
"""
Only relevant when the axis `type` is "date". Sets the base for
period positioning in milliseconds or date string on the y0
axis. When `y0period` is round number of weeks, the `y0period0`
by default would be on a Sunday i.e. 2000-01-02, otherwise it
would be at 2000-01-01.
The 'yperiod0' property accepts values of any type
Returns
-------
Any
"""
return self["yperiod0"]
@yperiod0.setter
def yperiod0(self, val):
self["yperiod0"] = val
# yperiodalignment
# ----------------
@property
def yperiodalignment(self):
"""
Only relevant when the axis `type` is "date". Sets the
alignment of data points on the y axis.
The 'yperiodalignment' property is an enumeration that may be specified as:
- One of the following enumeration values:
['start', 'middle', 'end']
Returns
-------
Any
"""
return self["yperiodalignment"]
@yperiodalignment.setter
def yperiodalignment(self, val):
self["yperiodalignment"] = val
# ysrc
# ----
@property
def ysrc(self):
"""
Sets the source reference on Chart Studio Cloud for `y`.
The 'ysrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str
"""
return self["ysrc"]
@ysrc.setter
def ysrc(self, val):
self["ysrc"] = val
# type
# ----
@property
def type(self):
return self._props["type"]
# Self properties description
# ---------------------------
@property
def _prop_descriptions(self):
return """\
alignmentgroup
Set several traces linked to the same position axis or
matching axes to the same alignmentgroup. This controls
whether bars compute their positional range dependently
or independently.
boxmean
If True, the mean of the box(es)' underlying
distribution is drawn as a dashed line inside the
box(es). If "sd" the standard deviation is also drawn.
Defaults to True when `mean` is set. Defaults to "sd"
when `sd` is set Otherwise defaults to False.
boxpoints
If "outliers", only the sample points lying outside the
whiskers are shown If "suspectedoutliers", the outlier
points are shown and points either less than 4*Q1-3*Q3
or greater than 4*Q3-3*Q1 are highlighted (see
`outliercolor`) If "all", all sample points are shown
If False, only the box(es) are shown with no sample
points Defaults to "suspectedoutliers" when
`marker.outliercolor` or `marker.line.outliercolor` is
set. Defaults to "all" under the q1/median/q3
signature. Otherwise defaults to "outliers".
customdata
Assigns extra data each datum. This may be useful when
listening to hover, click and selection events. Note
that, "scatter" traces also appends customdata items in
the markers DOM elements
customdatasrc
Sets the source reference on Chart Studio Cloud for
`customdata`.
dx
Sets the x coordinate step for multi-box traces set
using q1/median/q3.
dy
Sets the y coordinate step for multi-box traces set
using q1/median/q3.
fillcolor
Sets the fill color. Defaults to a half-transparent
variant of the line color, marker color, or marker line
color, whichever is available.
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.
hoverinfosrc
Sets the source reference on Chart Studio Cloud for
`hoverinfo`.
hoverlabel
:class:`plotly.graph_objects.box.Hoverlabel` instance
or dict with compatible properties
hoveron
Do the hover effects highlight individual boxes or
sample points or both?
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}" as well as %{xother}, {%_xother},
{%_xother_}, {%xother_}. When showing info for several
points, "xother" will be added to those with different
x positions from the first point. An underscore before
or after "(x|y)other" will add a space on that side,
only when this field is shown. Numbers are formatted
using d3-format's syntax %{variable:d3-format}, for
example "Price: %{y:$.2f}".
https://github.com/d3/d3-format/tree/v1.4.5#d3-format
for details on the formatting syntax. Dates are
formatted using d3-time-format's syntax
%{variable|d3-time-format}, for example "Day:
%{2019-01-01|%A}". https://github.com/d3/d3-time-
format/tree/v2.2.3#locale_format for details on the
date formatting syntax. The variables available in
`hovertemplate` are the ones emitted as event data
described at this link
https://plotly.com/javascript/plotlyjs-events/#event-
data. Additionally, every attributes that can be
specified per-point (the ones that are `arrayOk: true`)
are available. Anything contained in tag `<extra>` is
displayed in the secondary box, for example
"<extra>{fullData.name}</extra>". To hide the secondary
box completely, use an empty tag `<extra></extra>`.
hovertemplatesrc
Sets the source reference on Chart Studio Cloud for
`hovertemplate`.
hovertext
Same as `text`.
hovertextsrc
Sets the source reference on Chart Studio Cloud for
`hovertext`.
ids
Assigns id labels to each datum. These ids for object
constancy of data points during animation. Should be an
array of strings, not numbers or any other type.
idssrc
Sets the source reference on Chart Studio Cloud for
`ids`.
jitter
Sets the amount of jitter in the sample points drawn.
If 0, the sample points align along the distribution
axis. If 1, the sample points are drawn in a random
jitter of width equal to the width of the box(es).
legend
Sets the reference to a legend to show this trace in.
References to these legends are "legend", "legend2",
"legend3", etc. Settings for these legends are set in
the layout, under `layout.legend`, `layout.legend2`,
etc.
legendgroup
Sets the legend group for this trace. Traces and shapes
part of the same legend group hide/show at the same
time when toggling legend items.
legendgrouptitle
:class:`plotly.graph_objects.box.Legendgrouptitle`
instance or dict with compatible properties
legendrank
Sets the legend rank for this trace. Items and groups
with smaller ranks are presented on top/left side while
with "reversed" `legend.traceorder` they are on
bottom/right side. The default legendrank is 1000, so
that you can use ranks less than 1000 to place certain
items before all unranked items, and ranks greater than
1000 to go after all unranked items. When having
unranked or equal rank items shapes would be displayed
after traces i.e. according to their order in data and
layout.
legendwidth
Sets the width (in px or fraction) of the legend for
this trace.
line
:class:`plotly.graph_objects.box.Line` instance or dict
with compatible properties
lowerfence
Sets the lower fence values. There should be as many
items as the number of boxes desired. This attribute
has effect only under the q1/median/q3 signature. If
`lowerfence` is not provided but a sample (in `y` or
`x`) is set, we compute the lower as the last sample
point below 1.5 times the IQR.
lowerfencesrc
Sets the source reference on Chart Studio Cloud for
`lowerfence`.
marker
:class:`plotly.graph_objects.box.Marker` instance or
dict with compatible properties
mean
Sets the mean values. There should be as many items as
the number of boxes desired. This attribute has effect
only under the q1/median/q3 signature. If `mean` is not
provided but a sample (in `y` or `x`) is set, we
compute the mean for each box using the sample values.
meansrc
Sets the source reference on Chart Studio Cloud for
`mean`.
median
Sets the median values. There should be as many items
as the number of boxes desired.
mediansrc
Sets the source reference on Chart Studio Cloud for
`median`.
meta
Assigns extra meta information associated with this
trace that can be used in various text attributes.
Attributes such as trace `name`, graph, axis and
colorbar `title.text`, annotation `text`
`rangeselector`, `updatemenues` and `sliders` `label`
text all support `meta`. To access the trace `meta`
values in an attribute in the same trace, simply use
`%{meta[i]}` where `i` is the index or key of the
`meta` item in question. To access trace `meta` in
layout attributes, use `%{data[n[.meta[i]}` where `i`
is the index or key of the `meta` and `n` is the trace
index.
metasrc
Sets the source reference on Chart Studio Cloud for
`meta`.
name
Sets the trace name. The trace name appears as the
legend item and on hover. For box traces, the name will
also be used for the position coordinate, if `x` and
`x0` (`y` and `y0` if horizontal) are missing and the
position axis is categorical
notched
Determines whether or not notches are drawn. Notches
displays a confidence interval around the median. We
compute the confidence interval as median +/- 1.57 *
IQR / sqrt(N), where IQR is the interquartile range and
N is the sample size. If two boxes' notches do not
overlap there is 95% confidence their medians differ.
See https://sites.google.com/site/davidsstatistics/home
/notched-box-plots for more info. Defaults to False
unless `notchwidth` or `notchspan` is set.
notchspan
Sets the notch span from the boxes' `median` values.
There should be as many items as the number of boxes
desired. This attribute has effect only under the
q1/median/q3 signature. If `notchspan` is not provided
but a sample (in `y` or `x`) is set, we compute it as
1.57 * IQR / sqrt(N), where N is the sample size.
notchspansrc
Sets the source reference on Chart Studio Cloud for
`notchspan`.
notchwidth
Sets the width of the notches relative to the box'
width. For example, with 0, the notches are as wide as
the box(es).
offsetgroup
Set several traces linked to the same position axis or
matching axes to the same offsetgroup where bars of the
same position coordinate will line up.
opacity
Sets the opacity of the trace.
orientation
Sets the orientation of the box(es). If "v" ("h"), the
distribution is visualized along the vertical
(horizontal).
pointpos
Sets the position of the sample points in relation to
the box(es). If 0, the sample points are places over
the center of the box(es). Positive (negative) values
correspond to positions to the right (left) for
vertical boxes and above (below) for horizontal boxes
q1
Sets the Quartile 1 values. There should be as many
items as the number of boxes desired.
q1src
Sets the source reference on Chart Studio Cloud for
`q1`.
q3
Sets the Quartile 3 values. There should be as many
items as the number of boxes desired.
q3src
Sets the source reference on Chart Studio Cloud for
`q3`.
quartilemethod
Sets the method used to compute the sample's Q1 and Q3
quartiles. The "linear" method uses the 25th percentile
for Q1 and 75th percentile for Q3 as computed using
method #10 (listed on
http://jse.amstat.org/v14n3/langford.html). The
"exclusive" method uses the median to divide the
ordered dataset into two halves if the sample is odd,
it does not include the median in either half - Q1 is
then the median of the lower half and Q3 the median of
the upper half. The "inclusive" method also uses the
median to divide the ordered dataset into two halves
but if the sample is odd, it includes the median in
both halves - Q1 is then the median of the lower half
and Q3 the median of the upper half.
sd
Sets the standard deviation values. There should be as
many items as the number of boxes desired. This
attribute has effect only under the q1/median/q3
signature. If `sd` is not provided but a sample (in `y`
or `x`) is set, we compute the standard deviation for
each box using the sample values.
sdmultiple
Scales the box size when sizemode=sd Allowing boxes to
be drawn across any stddev range For example 1-stddev,
3-stddev, 5-stddev
sdsrc
Sets the source reference on Chart Studio Cloud for
`sd`.
selected
:class:`plotly.graph_objects.box.Selected` instance or
dict with compatible properties
selectedpoints
Array containing integer indices of selected points.
Has an effect only for traces that support selections.
Note that an empty array means an empty selection where
the `unselected` are turned on for all points, whereas,
any other non-array values means no selection all where
the `selected` and `unselected` styles have no effect.
showlegend
Determines whether or not an item corresponding to this
trace is shown in the legend.
showwhiskers
Determines whether or not whiskers are visible.
Defaults to true for `sizemode` "quartiles", false for
"sd".
sizemode
Sets the upper and lower bound for the boxes quartiles
means box is drawn between Q1 and Q3 SD means the box
is drawn between Mean +- Standard Deviation Argument
sdmultiple (default 1) to scale the box size So it
could be drawn 1-stddev, 3-stddev etc
stream
:class:`plotly.graph_objects.box.Stream` instance or
dict with compatible properties
text
Sets the text elements associated with each sample
value. If a single string, the same string appears over
all the data points. If an array of string, the items
are mapped in order to the this trace's (x,y)
coordinates. To be seen, trace `hoverinfo` must contain
a "text" flag.
textsrc
Sets the source reference on Chart Studio Cloud for
`text`.
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.
unselected
:class:`plotly.graph_objects.box.Unselected` instance
or dict with compatible properties
upperfence
Sets the upper fence values. There should be as many
items as the number of boxes desired. This attribute
has effect only under the q1/median/q3 signature. If
`upperfence` is not provided but a sample (in `y` or
`x`) is set, we compute the lower as the last sample
point above 1.5 times the IQR.
upperfencesrc
Sets the source reference on Chart Studio Cloud for
`upperfence`.
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).
whiskerwidth
Sets the width of the whiskers relative to the box'
width. For example, with 1, the whiskers are as wide as
the box(es).
width
Sets the width of the box in data coordinate If 0
(default value) the width is automatically selected
based on the positions of other box traces in the same
subplot.
x
Sets the x sample data or coordinates. See overview for
more info.
x0
Sets the x coordinate for single-box traces or the
starting coordinate for multi-box traces set using
q1/median/q3. See overview for more info.
xaxis
Sets a reference between this trace's x coordinates and
a 2D cartesian x axis. If "x" (the default value), the
x coordinates refer to `layout.xaxis`. If "x2", the x
coordinates refer to `layout.xaxis2`, and so on.
xcalendar
Sets the calendar system to use with `x` date data.
xhoverformat
Sets the hover text formatting rulefor `x` using d3
formatting mini-languages which are very similar to
those in Python. For numbers, see:
https://github.com/d3/d3-format/tree/v1.4.5#d3-format.
And for dates see: https://github.com/d3/d3-time-
format/tree/v2.2.3#locale_format. We add two items to
d3's date formatter: "%h" for half of the year as a
decimal number as well as "%{n}f" for fractional
seconds with n digits. For example, *2016-10-13
09:15:23.456* with tickformat "%H~%M~%S.%2f" would
display *09~15~23.46*By default the values are
formatted using `xaxis.hoverformat`.
xperiod
Only relevant when the axis `type` is "date". Sets the
period positioning in milliseconds or "M<n>" on the x
axis. Special values in the form of "M<n>" could be
used to declare the number of months. In this case `n`
must be a positive integer.
xperiod0
Only relevant when the axis `type` is "date". Sets the
base for period positioning in milliseconds or date
string on the x0 axis. When `x0period` is round number
of weeks, the `x0period0` by default would be on a
Sunday i.e. 2000-01-02, otherwise it would be at
2000-01-01.
xperiodalignment
Only relevant when the axis `type` is "date". Sets the
alignment of data points on the x axis.
xsrc
Sets the source reference on Chart Studio Cloud for
`x`.
y
Sets the y sample data or coordinates. See overview for
more info.
y0
Sets the y coordinate for single-box traces or the
starting coordinate for multi-box traces set using
q1/median/q3. See overview for more info.
yaxis
Sets a reference between this trace's y coordinates and
a 2D cartesian y axis. If "y" (the default value), the
y coordinates refer to `layout.yaxis`. If "y2", the y
coordinates refer to `layout.yaxis2`, and so on.
ycalendar
Sets the calendar system to use with `y` date data.
yhoverformat
Sets the hover text formatting rulefor `y` using d3
formatting mini-languages which are very similar to
those in Python. For numbers, see:
https://github.com/d3/d3-format/tree/v1.4.5#d3-format.
And for dates see: https://github.com/d3/d3-time-
format/tree/v2.2.3#locale_format. We add two items to
d3's date formatter: "%h" for half of the year as a
decimal number as well as "%{n}f" for fractional
seconds with n digits. For example, *2016-10-13
09:15:23.456* with tickformat "%H~%M~%S.%2f" would
display *09~15~23.46*By default the values are
formatted using `yaxis.hoverformat`.
yperiod
Only relevant when the axis `type` is "date". Sets the
period positioning in milliseconds or "M<n>" on the y
axis. Special values in the form of "M<n>" could be
used to declare the number of months. In this case `n`
must be a positive integer.
yperiod0
Only relevant when the axis `type` is "date". Sets the
base for period positioning in milliseconds or date
string on the y0 axis. When `y0period` is round number
of weeks, the `y0period0` by default would be on a
Sunday i.e. 2000-01-02, otherwise it would be at
2000-01-01.
yperiodalignment
Only relevant when the axis `type` is "date". Sets the
alignment of data points on the y axis.
ysrc
Sets the source reference on Chart Studio Cloud for
`y`.
"""
def __init__(
self,
arg=None,
alignmentgroup=None,
boxmean=None,
boxpoints=None,
customdata=None,
customdatasrc=None,
dx=None,
dy=None,
fillcolor=None,
hoverinfo=None,
hoverinfosrc=None,
hoverlabel=None,
hoveron=None,
hovertemplate=None,
hovertemplatesrc=None,
hovertext=None,
hovertextsrc=None,
ids=None,
idssrc=None,
jitter=None,
legend=None,
legendgroup=None,
legendgrouptitle=None,
legendrank=None,
legendwidth=None,
line=None,
lowerfence=None,
lowerfencesrc=None,
marker=None,
mean=None,
meansrc=None,
median=None,
mediansrc=None,
meta=None,
metasrc=None,
name=None,
notched=None,
notchspan=None,
notchspansrc=None,
notchwidth=None,
offsetgroup=None,
opacity=None,
orientation=None,
pointpos=None,
q1=None,
q1src=None,
q3=None,
q3src=None,
quartilemethod=None,
sd=None,
sdmultiple=None,
sdsrc=None,
selected=None,
selectedpoints=None,
showlegend=None,
showwhiskers=None,
sizemode=None,
stream=None,
text=None,
textsrc=None,
uid=None,
uirevision=None,
unselected=None,
upperfence=None,
upperfencesrc=None,
visible=None,
whiskerwidth=None,
width=None,
x=None,
x0=None,
xaxis=None,
xcalendar=None,
xhoverformat=None,
xperiod=None,
xperiod0=None,
xperiodalignment=None,
xsrc=None,
y=None,
y0=None,
yaxis=None,
ycalendar=None,
yhoverformat=None,
yperiod=None,
yperiod0=None,
yperiodalignment=None,
ysrc=None,
**kwargs,
):
"""
Construct a new Box object
Each box spans from quartile 1 (Q1) to quartile 3 (Q3). The
second quartile (Q2, i.e. the median) is marked by a line
inside the box. The fences grow outward from the boxes' edges,
by default they span +/- 1.5 times the interquartile range
(IQR: Q3-Q1), The sample mean and standard deviation as well as
notches and the sample, outlier and suspected outliers points
can be optionally added to the box plot. The values and
positions corresponding to each boxes can be input using two
signatures. The first signature expects users to supply the
sample values in the `y` data array for vertical boxes (`x` for
horizontal boxes). By supplying an `x` (`y`) array, one box per
distinct `x` (`y`) value is drawn If no `x` (`y`) list is
provided, a single box is drawn. In this case, the box is
positioned with the trace `name` or with `x0` (`y0`) if
provided. The second signature expects users to supply the
boxes corresponding Q1, median and Q3 statistics in the `q1`,
`median` and `q3` data arrays respectively. Other box features
relying on statistics namely `lowerfence`, `upperfence`,
`notchspan` can be set directly by the users. To have plotly
compute them or to show sample points besides the boxes, users
can set the `y` data array for vertical boxes (`x` for
horizontal boxes) to a 2D array with the outer length
corresponding to the number of boxes in the traces and the
inner length corresponding the sample size.
Parameters
----------
arg
dict of properties compatible with this constructor or
an instance of :class:`plotly.graph_objs.Box`
alignmentgroup
Set several traces linked to the same position axis or
matching axes to the same alignmentgroup. This controls
whether bars compute their positional range dependently
or independently.
boxmean
If True, the mean of the box(es)' underlying
distribution is drawn as a dashed line inside the
box(es). If "sd" the standard deviation is also drawn.
Defaults to True when `mean` is set. Defaults to "sd"
when `sd` is set Otherwise defaults to False.
boxpoints
If "outliers", only the sample points lying outside the
whiskers are shown If "suspectedoutliers", the outlier
points are shown and points either less than 4*Q1-3*Q3
or greater than 4*Q3-3*Q1 are highlighted (see
`outliercolor`) If "all", all sample points are shown
If False, only the box(es) are shown with no sample
points Defaults to "suspectedoutliers" when
`marker.outliercolor` or `marker.line.outliercolor` is
set. Defaults to "all" under the q1/median/q3
signature. Otherwise defaults to "outliers".
customdata
Assigns extra data each datum. This may be useful when
listening to hover, click and selection events. Note
that, "scatter" traces also appends customdata items in
the markers DOM elements
customdatasrc
Sets the source reference on Chart Studio Cloud for
`customdata`.
dx
Sets the x coordinate step for multi-box traces set
using q1/median/q3.
dy
Sets the y coordinate step for multi-box traces set
using q1/median/q3.
fillcolor
Sets the fill color. Defaults to a half-transparent
variant of the line color, marker color, or marker line
color, whichever is available.
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.
hoverinfosrc
Sets the source reference on Chart Studio Cloud for
`hoverinfo`.
hoverlabel
:class:`plotly.graph_objects.box.Hoverlabel` instance
or dict with compatible properties
hoveron
Do the hover effects highlight individual boxes or
sample points or both?
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}" as well as %{xother}, {%_xother},
{%_xother_}, {%xother_}. When showing info for several
points, "xother" will be added to those with different
x positions from the first point. An underscore before
or after "(x|y)other" will add a space on that side,
only when this field is shown. Numbers are formatted
using d3-format's syntax %{variable:d3-format}, for
example "Price: %{y:$.2f}".
https://github.com/d3/d3-format/tree/v1.4.5#d3-format
for details on the formatting syntax. Dates are
formatted using d3-time-format's syntax
%{variable|d3-time-format}, for example "Day:
%{2019-01-01|%A}". https://github.com/d3/d3-time-
format/tree/v2.2.3#locale_format for details on the
date formatting syntax. The variables available in
`hovertemplate` are the ones emitted as event data
described at this link
https://plotly.com/javascript/plotlyjs-events/#event-
data. Additionally, every attributes that can be
specified per-point (the ones that are `arrayOk: true`)
are available. Anything contained in tag `<extra>` is
displayed in the secondary box, for example
"<extra>{fullData.name}</extra>". To hide the secondary
box completely, use an empty tag `<extra></extra>`.
hovertemplatesrc
Sets the source reference on Chart Studio Cloud for
`hovertemplate`.
hovertext
Same as `text`.
hovertextsrc
Sets the source reference on Chart Studio Cloud for
`hovertext`.
ids
Assigns id labels to each datum. These ids for object
constancy of data points during animation. Should be an
array of strings, not numbers or any other type.
idssrc
Sets the source reference on Chart Studio Cloud for
`ids`.
jitter
Sets the amount of jitter in the sample points drawn.
If 0, the sample points align along the distribution
axis. If 1, the sample points are drawn in a random
jitter of width equal to the width of the box(es).
legend
Sets the reference to a legend to show this trace in.
References to these legends are "legend", "legend2",
"legend3", etc. Settings for these legends are set in
the layout, under `layout.legend`, `layout.legend2`,
etc.
legendgroup
Sets the legend group for this trace. Traces and shapes
part of the same legend group hide/show at the same
time when toggling legend items.
legendgrouptitle
:class:`plotly.graph_objects.box.Legendgrouptitle`
instance or dict with compatible properties
legendrank
Sets the legend rank for this trace. Items and groups
with smaller ranks are presented on top/left side while
with "reversed" `legend.traceorder` they are on
bottom/right side. The default legendrank is 1000, so
that you can use ranks less than 1000 to place certain
items before all unranked items, and ranks greater than
1000 to go after all unranked items. When having
unranked or equal rank items shapes would be displayed
after traces i.e. according to their order in data and
layout.
legendwidth
Sets the width (in px or fraction) of the legend for
this trace.
line
:class:`plotly.graph_objects.box.Line` instance or dict
with compatible properties
lowerfence
Sets the lower fence values. There should be as many
items as the number of boxes desired. This attribute
has effect only under the q1/median/q3 signature. If
`lowerfence` is not provided but a sample (in `y` or
`x`) is set, we compute the lower as the last sample
point below 1.5 times the IQR.
lowerfencesrc
Sets the source reference on Chart Studio Cloud for
`lowerfence`.
marker
:class:`plotly.graph_objects.box.Marker` instance or
dict with compatible properties
mean
Sets the mean values. There should be as many items as
the number of boxes desired. This attribute has effect
only under the q1/median/q3 signature. If `mean` is not
provided but a sample (in `y` or `x`) is set, we
compute the mean for each box using the sample values.
meansrc
Sets the source reference on Chart Studio Cloud for
`mean`.
median
Sets the median values. There should be as many items
as the number of boxes desired.
mediansrc
Sets the source reference on Chart Studio Cloud for
`median`.
meta
Assigns extra meta information associated with this
trace that can be used in various text attributes.
Attributes such as trace `name`, graph, axis and
colorbar `title.text`, annotation `text`
`rangeselector`, `updatemenues` and `sliders` `label`
text all support `meta`. To access the trace `meta`
values in an attribute in the same trace, simply use
`%{meta[i]}` where `i` is the index or key of the
`meta` item in question. To access trace `meta` in
layout attributes, use `%{data[n[.meta[i]}` where `i`
is the index or key of the `meta` and `n` is the trace
index.
metasrc
Sets the source reference on Chart Studio Cloud for
`meta`.
name
Sets the trace name. The trace name appears as the
legend item and on hover. For box traces, the name will
also be used for the position coordinate, if `x` and
`x0` (`y` and `y0` if horizontal) are missing and the
position axis is categorical
notched
Determines whether or not notches are drawn. Notches
displays a confidence interval around the median. We
compute the confidence interval as median +/- 1.57 *
IQR / sqrt(N), where IQR is the interquartile range and
N is the sample size. If two boxes' notches do not
overlap there is 95% confidence their medians differ.
See https://sites.google.com/site/davidsstatistics/home
/notched-box-plots for more info. Defaults to False
unless `notchwidth` or `notchspan` is set.
notchspan
Sets the notch span from the boxes' `median` values.
There should be as many items as the number of boxes
desired. This attribute has effect only under the
q1/median/q3 signature. If `notchspan` is not provided
but a sample (in `y` or `x`) is set, we compute it as
1.57 * IQR / sqrt(N), where N is the sample size.
notchspansrc
Sets the source reference on Chart Studio Cloud for
`notchspan`.
notchwidth
Sets the width of the notches relative to the box'
width. For example, with 0, the notches are as wide as
the box(es).
offsetgroup
Set several traces linked to the same position axis or
matching axes to the same offsetgroup where bars of the
same position coordinate will line up.
opacity
Sets the opacity of the trace.
orientation
Sets the orientation of the box(es). If "v" ("h"), the
distribution is visualized along the vertical
(horizontal).
pointpos
Sets the position of the sample points in relation to
the box(es). If 0, the sample points are places over
the center of the box(es). Positive (negative) values
correspond to positions to the right (left) for
vertical boxes and above (below) for horizontal boxes
q1
Sets the Quartile 1 values. There should be as many
items as the number of boxes desired.
q1src
Sets the source reference on Chart Studio Cloud for
`q1`.
q3
Sets the Quartile 3 values. There should be as many
items as the number of boxes desired.
q3src
Sets the source reference on Chart Studio Cloud for
`q3`.
quartilemethod
Sets the method used to compute the sample's Q1 and Q3
quartiles. The "linear" method uses the 25th percentile
for Q1 and 75th percentile for Q3 as computed using
method #10 (listed on
http://jse.amstat.org/v14n3/langford.html). The
"exclusive" method uses the median to divide the
ordered dataset into two halves if the sample is odd,
it does not include the median in either half - Q1 is
then the median of the lower half and Q3 the median of
the upper half. The "inclusive" method also uses the
median to divide the ordered dataset into two halves
but if the sample is odd, it includes the median in
both halves - Q1 is then the median of the lower half
and Q3 the median of the upper half.
sd
Sets the standard deviation values. There should be as
many items as the number of boxes desired. This
attribute has effect only under the q1/median/q3
signature. If `sd` is not provided but a sample (in `y`
or `x`) is set, we compute the standard deviation for
each box using the sample values.
sdmultiple
Scales the box size when sizemode=sd Allowing boxes to
be drawn across any stddev range For example 1-stddev,
3-stddev, 5-stddev
sdsrc
Sets the source reference on Chart Studio Cloud for
`sd`.
selected
:class:`plotly.graph_objects.box.Selected` instance or
dict with compatible properties
selectedpoints
Array containing integer indices of selected points.
Has an effect only for traces that support selections.
Note that an empty array means an empty selection where
the `unselected` are turned on for all points, whereas,
any other non-array values means no selection all where
the `selected` and `unselected` styles have no effect.
showlegend
Determines whether or not an item corresponding to this
trace is shown in the legend.
showwhiskers
Determines whether or not whiskers are visible.
Defaults to true for `sizemode` "quartiles", false for
"sd".
sizemode
Sets the upper and lower bound for the boxes quartiles
means box is drawn between Q1 and Q3 SD means the box
is drawn between Mean +- Standard Deviation Argument
sdmultiple (default 1) to scale the box size So it
could be drawn 1-stddev, 3-stddev etc
stream
:class:`plotly.graph_objects.box.Stream` instance or
dict with compatible properties
text
Sets the text elements associated with each sample
value. If a single string, the same string appears over
all the data points. If an array of string, the items
are mapped in order to the this trace's (x,y)
coordinates. To be seen, trace `hoverinfo` must contain
a "text" flag.
textsrc
Sets the source reference on Chart Studio Cloud for
`text`.
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.
unselected
:class:`plotly.graph_objects.box.Unselected` instance
or dict with compatible properties
upperfence
Sets the upper fence values. There should be as many
items as the number of boxes desired. This attribute
has effect only under the q1/median/q3 signature. If
`upperfence` is not provided but a sample (in `y` or
`x`) is set, we compute the lower as the last sample
point above 1.5 times the IQR.
upperfencesrc
Sets the source reference on Chart Studio Cloud for
`upperfence`.
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).
whiskerwidth
Sets the width of the whiskers relative to the box'
width. For example, with 1, the whiskers are as wide as
the box(es).
width
Sets the width of the box in data coordinate If 0
(default value) the width is automatically selected
based on the positions of other box traces in the same
subplot.
x
Sets the x sample data or coordinates. See overview for
more info.
x0
Sets the x coordinate for single-box traces or the
starting coordinate for multi-box traces set using
q1/median/q3. See overview for more info.
xaxis
Sets a reference between this trace's x coordinates and
a 2D cartesian x axis. If "x" (the default value), the
x coordinates refer to `layout.xaxis`. If "x2", the x
coordinates refer to `layout.xaxis2`, and so on.
xcalendar
Sets the calendar system to use with `x` date data.
xhoverformat
Sets the hover text formatting rulefor `x` using d3
formatting mini-languages which are very similar to
those in Python. For numbers, see:
https://github.com/d3/d3-format/tree/v1.4.5#d3-format.
And for dates see: https://github.com/d3/d3-time-
format/tree/v2.2.3#locale_format. We add two items to
d3's date formatter: "%h" for half of the year as a
decimal number as well as "%{n}f" for fractional
seconds with n digits. For example, *2016-10-13
09:15:23.456* with tickformat "%H~%M~%S.%2f" would
display *09~15~23.46*By default the values are
formatted using `xaxis.hoverformat`.
xperiod
Only relevant when the axis `type` is "date". Sets the
period positioning in milliseconds or "M<n>" on the x
axis. Special values in the form of "M<n>" could be
used to declare the number of months. In this case `n`
must be a positive integer.
xperiod0
Only relevant when the axis `type` is "date". Sets the
base for period positioning in milliseconds or date
string on the x0 axis. When `x0period` is round number
of weeks, the `x0period0` by default would be on a
Sunday i.e. 2000-01-02, otherwise it would be at
2000-01-01.
xperiodalignment
Only relevant when the axis `type` is "date". Sets the
alignment of data points on the x axis.
xsrc
Sets the source reference on Chart Studio Cloud for
`x`.
y
Sets the y sample data or coordinates. See overview for
more info.
y0
Sets the y coordinate for single-box traces or the
starting coordinate for multi-box traces set using
q1/median/q3. See overview for more info.
yaxis
Sets a reference between this trace's y coordinates and
a 2D cartesian y axis. If "y" (the default value), the
y coordinates refer to `layout.yaxis`. If "y2", the y
coordinates refer to `layout.yaxis2`, and so on.
ycalendar
Sets the calendar system to use with `y` date data.
yhoverformat
Sets the hover text formatting rulefor `y` using d3
formatting mini-languages which are very similar to
those in Python. For numbers, see:
https://github.com/d3/d3-format/tree/v1.4.5#d3-format.
And for dates see: https://github.com/d3/d3-time-
format/tree/v2.2.3#locale_format. We add two items to
d3's date formatter: "%h" for half of the year as a
decimal number as well as "%{n}f" for fractional
seconds with n digits. For example, *2016-10-13
09:15:23.456* with tickformat "%H~%M~%S.%2f" would
display *09~15~23.46*By default the values are
formatted using `yaxis.hoverformat`.
yperiod
Only relevant when the axis `type` is "date". Sets the
period positioning in milliseconds or "M<n>" on the y
axis. Special values in the form of "M<n>" could be
used to declare the number of months. In this case `n`
must be a positive integer.
yperiod0
Only relevant when the axis `type` is "date". Sets the
base for period positioning in milliseconds or date
string on the y0 axis. When `y0period` is round number
of weeks, the `y0period0` by default would be on a
Sunday i.e. 2000-01-02, otherwise it would be at
2000-01-01.
yperiodalignment
Only relevant when the axis `type` is "date". Sets the
alignment of data points on the y axis.
ysrc
Sets the source reference on Chart Studio Cloud for
`y`.
Returns
-------
Box
"""
super(Box, self).__init__("box")
if "_parent" in kwargs:
self._parent = kwargs["_parent"]
return
# 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.Box
constructor must be a dict or
an instance of :class:`plotly.graph_objs.Box`"""
)
# Handle skip_invalid
# -------------------
self._skip_invalid = kwargs.pop("skip_invalid", False)
self._validate = kwargs.pop("_validate", True)
# Populate data dict with properties
# ----------------------------------
_v = arg.pop("alignmentgroup", None)
_v = alignmentgroup if alignmentgroup is not None else _v
if _v is not None:
self["alignmentgroup"] = _v
_v = arg.pop("boxmean", None)
_v = boxmean if boxmean is not None else _v
if _v is not None:
self["boxmean"] = _v
_v = arg.pop("boxpoints", None)
_v = boxpoints if boxpoints is not None else _v
if _v is not None:
self["boxpoints"] = _v
_v = arg.pop("customdata", None)
_v = customdata if customdata is not None else _v
if _v is not None:
self["customdata"] = _v
_v = arg.pop("customdatasrc", None)
_v = customdatasrc if customdatasrc is not None else _v
if _v is not None:
self["customdatasrc"] = _v
_v = arg.pop("dx", None)
_v = dx if dx is not None else _v
if _v is not None:
self["dx"] = _v
_v = arg.pop("dy", None)
_v = dy if dy is not None else _v
if _v is not None:
self["dy"] = _v
_v = arg.pop("fillcolor", None)
_v = fillcolor if fillcolor is not None else _v
if _v is not None:
self["fillcolor"] = _v
_v = arg.pop("hoverinfo", None)
_v = hoverinfo if hoverinfo is not None else _v
if _v is not None:
self["hoverinfo"] = _v
_v = arg.pop("hoverinfosrc", None)
_v = hoverinfosrc if hoverinfosrc is not None else _v
if _v is not None:
self["hoverinfosrc"] = _v
_v = arg.pop("hoverlabel", None)
_v = hoverlabel if hoverlabel is not None else _v
if _v is not None:
self["hoverlabel"] = _v
_v = arg.pop("hoveron", None)
_v = hoveron if hoveron is not None else _v
if _v is not None:
self["hoveron"] = _v
_v = arg.pop("hovertemplate", None)
_v = hovertemplate if hovertemplate is not None else _v
if _v is not None:
self["hovertemplate"] = _v
_v = arg.pop("hovertemplatesrc", None)
_v = hovertemplatesrc if hovertemplatesrc is not None else _v
if _v is not None:
self["hovertemplatesrc"] = _v
_v = arg.pop("hovertext", None)
_v = hovertext if hovertext is not None else _v
if _v is not None:
self["hovertext"] = _v
_v = arg.pop("hovertextsrc", None)
_v = hovertextsrc if hovertextsrc is not None else _v
if _v is not None:
self["hovertextsrc"] = _v
_v = arg.pop("ids", None)
_v = ids if ids is not None else _v
if _v is not None:
self["ids"] = _v
_v = arg.pop("idssrc", None)
_v = idssrc if idssrc is not None else _v
if _v is not None:
self["idssrc"] = _v
_v = arg.pop("jitter", None)
_v = jitter if jitter is not None else _v
if _v is not None:
self["jitter"] = _v
_v = arg.pop("legend", None)
_v = legend if legend is not None else _v
if _v is not None:
self["legend"] = _v
_v = arg.pop("legendgroup", None)
_v = legendgroup if legendgroup is not None else _v
if _v is not None:
self["legendgroup"] = _v
_v = arg.pop("legendgrouptitle", None)
_v = legendgrouptitle if legendgrouptitle is not None else _v
if _v is not None:
self["legendgrouptitle"] = _v
_v = arg.pop("legendrank", None)
_v = legendrank if legendrank is not None else _v
if _v is not None:
self["legendrank"] = _v
_v = arg.pop("legendwidth", None)
_v = legendwidth if legendwidth is not None else _v
if _v is not None:
self["legendwidth"] = _v
_v = arg.pop("line", None)
_v = line if line is not None else _v
if _v is not None:
self["line"] = _v
_v = arg.pop("lowerfence", None)
_v = lowerfence if lowerfence is not None else _v
if _v is not None:
self["lowerfence"] = _v
_v = arg.pop("lowerfencesrc", None)
_v = lowerfencesrc if lowerfencesrc is not None else _v
if _v is not None:
self["lowerfencesrc"] = _v
_v = arg.pop("marker", None)
_v = marker if marker is not None else _v
if _v is not None:
self["marker"] = _v
_v = arg.pop("mean", None)
_v = mean if mean is not None else _v
if _v is not None:
self["mean"] = _v
_v = arg.pop("meansrc", None)
_v = meansrc if meansrc is not None else _v
if _v is not None:
self["meansrc"] = _v
_v = arg.pop("median", None)
_v = median if median is not None else _v
if _v is not None:
self["median"] = _v
_v = arg.pop("mediansrc", None)
_v = mediansrc if mediansrc is not None else _v
if _v is not None:
self["mediansrc"] = _v
_v = arg.pop("meta", None)
_v = meta if meta is not None else _v
if _v is not None:
self["meta"] = _v
_v = arg.pop("metasrc", None)
_v = metasrc if metasrc is not None else _v
if _v is not None:
self["metasrc"] = _v
_v = arg.pop("name", None)
_v = name if name is not None else _v
if _v is not None:
self["name"] = _v
_v = arg.pop("notched", None)
_v = notched if notched is not None else _v
if _v is not None:
self["notched"] = _v
_v = arg.pop("notchspan", None)
_v = notchspan if notchspan is not None else _v
if _v is not None:
self["notchspan"] = _v
_v = arg.pop("notchspansrc", None)
_v = notchspansrc if notchspansrc is not None else _v
if _v is not None:
self["notchspansrc"] = _v
_v = arg.pop("notchwidth", None)
_v = notchwidth if notchwidth is not None else _v
if _v is not None:
self["notchwidth"] = _v
_v = arg.pop("offsetgroup", None)
_v = offsetgroup if offsetgroup is not None else _v
if _v is not None:
self["offsetgroup"] = _v
_v = arg.pop("opacity", None)
_v = opacity if opacity is not None else _v
if _v is not None:
self["opacity"] = _v
_v = arg.pop("orientation", None)
_v = orientation if orientation is not None else _v
if _v is not None:
self["orientation"] = _v
_v = arg.pop("pointpos", None)
_v = pointpos if pointpos is not None else _v
if _v is not None:
self["pointpos"] = _v
_v = arg.pop("q1", None)
_v = q1 if q1 is not None else _v
if _v is not None:
self["q1"] = _v
_v = arg.pop("q1src", None)
_v = q1src if q1src is not None else _v
if _v is not None:
self["q1src"] = _v
_v = arg.pop("q3", None)
_v = q3 if q3 is not None else _v
if _v is not None:
self["q3"] = _v
_v = arg.pop("q3src", None)
_v = q3src if q3src is not None else _v
if _v is not None:
self["q3src"] = _v
_v = arg.pop("quartilemethod", None)
_v = quartilemethod if quartilemethod is not None else _v
if _v is not None:
self["quartilemethod"] = _v
_v = arg.pop("sd", None)
_v = sd if sd is not None else _v
if _v is not None:
self["sd"] = _v
_v = arg.pop("sdmultiple", None)
_v = sdmultiple if sdmultiple is not None else _v
if _v is not None:
self["sdmultiple"] = _v
_v = arg.pop("sdsrc", None)
_v = sdsrc if sdsrc is not None else _v
if _v is not None:
self["sdsrc"] = _v
_v = arg.pop("selected", None)
_v = selected if selected is not None else _v
if _v is not None:
self["selected"] = _v
_v = arg.pop("selectedpoints", None)
_v = selectedpoints if selectedpoints is not None else _v
if _v is not None:
self["selectedpoints"] = _v
_v = arg.pop("showlegend", None)
_v = showlegend if showlegend is not None else _v
if _v is not None:
self["showlegend"] = _v
_v = arg.pop("showwhiskers", None)
_v = showwhiskers if showwhiskers is not None else _v
if _v is not None:
self["showwhiskers"] = _v
_v = arg.pop("sizemode", None)
_v = sizemode if sizemode is not None else _v
if _v is not None:
self["sizemode"] = _v
_v = arg.pop("stream", None)
_v = stream if stream is not None else _v
if _v is not None:
self["stream"] = _v
_v = arg.pop("text", None)
_v = text if text is not None else _v
if _v is not None:
self["text"] = _v
_v = arg.pop("textsrc", None)
_v = textsrc if textsrc is not None else _v
if _v is not None:
self["textsrc"] = _v
_v = arg.pop("uid", None)
_v = uid if uid is not None else _v
if _v is not None:
self["uid"] = _v
_v = arg.pop("uirevision", None)
_v = uirevision if uirevision is not None else _v
if _v is not None:
self["uirevision"] = _v
_v = arg.pop("unselected", None)
_v = unselected if unselected is not None else _v
if _v is not None:
self["unselected"] = _v
_v = arg.pop("upperfence", None)
_v = upperfence if upperfence is not None else _v
if _v is not None:
self["upperfence"] = _v
_v = arg.pop("upperfencesrc", None)
_v = upperfencesrc if upperfencesrc is not None else _v
if _v is not None:
self["upperfencesrc"] = _v
_v = arg.pop("visible", None)
_v = visible if visible is not None else _v
if _v is not None:
self["visible"] = _v
_v = arg.pop("whiskerwidth", None)
_v = whiskerwidth if whiskerwidth is not None else _v
if _v is not None:
self["whiskerwidth"] = _v
_v = arg.pop("width", None)
_v = width if width is not None else _v
if _v is not None:
self["width"] = _v
_v = arg.pop("x", None)
_v = x if x is not None else _v
if _v is not None:
self["x"] = _v
_v = arg.pop("x0", None)
_v = x0 if x0 is not None else _v
if _v is not None:
self["x0"] = _v
_v = arg.pop("xaxis", None)
_v = xaxis if xaxis is not None else _v
if _v is not None:
self["xaxis"] = _v
_v = arg.pop("xcalendar", None)
_v = xcalendar if xcalendar is not None else _v
if _v is not None:
self["xcalendar"] = _v
_v = arg.pop("xhoverformat", None)
_v = xhoverformat if xhoverformat is not None else _v
if _v is not None:
self["xhoverformat"] = _v
_v = arg.pop("xperiod", None)
_v = xperiod if xperiod is not None else _v
if _v is not None:
self["xperiod"] = _v
_v = arg.pop("xperiod0", None)
_v = xperiod0 if xperiod0 is not None else _v
if _v is not None:
self["xperiod0"] = _v
_v = arg.pop("xperiodalignment", None)
_v = xperiodalignment if xperiodalignment is not None else _v
if _v is not None:
self["xperiodalignment"] = _v
_v = arg.pop("xsrc", None)
_v = xsrc if xsrc is not None else _v
if _v is not None:
self["xsrc"] = _v
_v = arg.pop("y", None)
_v = y if y is not None else _v
if _v is not None:
self["y"] = _v
_v = arg.pop("y0", None)
_v = y0 if y0 is not None else _v
if _v is not None:
self["y0"] = _v
_v = arg.pop("yaxis", None)
_v = yaxis if yaxis is not None else _v
if _v is not None:
self["yaxis"] = _v
_v = arg.pop("ycalendar", None)
_v = ycalendar if ycalendar is not None else _v
if _v is not None:
self["ycalendar"] = _v
_v = arg.pop("yhoverformat", None)
_v = yhoverformat if yhoverformat is not None else _v
if _v is not None:
self["yhoverformat"] = _v
_v = arg.pop("yperiod", None)
_v = yperiod if yperiod is not None else _v
if _v is not None:
self["yperiod"] = _v
_v = arg.pop("yperiod0", None)
_v = yperiod0 if yperiod0 is not None else _v
if _v is not None:
self["yperiod0"] = _v
_v = arg.pop("yperiodalignment", None)
_v = yperiodalignment if yperiodalignment is not None else _v
if _v is not None:
self["yperiodalignment"] = _v
_v = arg.pop("ysrc", None)
_v = ysrc if ysrc is not None else _v
if _v is not None:
self["ysrc"] = _v
# Read-only literals
# ------------------
self._props["type"] = "box"
arg.pop("type", None)
# Process unknown kwargs
# ----------------------
self._process_kwargs(**dict(arg, **kwargs))
# Reset skip_invalid
# ------------------
self._skip_invalid = False
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