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 `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. 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" on the x axis. Special values in the form of "M" 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" on the y axis. Special values in the form of "M" 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 `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. 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" on the x axis. Special values in the form of "M" 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" on the y axis. Special values in the form of "M" 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 `` is displayed in the secondary box, for example "{fullData.name}". To hide the secondary box completely, use an empty tag ``. 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" on the x axis. Special values in the form of "M" 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" on the y axis. Special values in the form of "M" 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