from plotly.basedatatypes import BaseTraceType import copy class Histogram(BaseTraceType): # autobinx # -------- @property def autobinx(self): """ Obsolete: since v1.42 each bin attribute is auto-determined separately and `autobinx` is not needed. However, we accept `autobinx: true` or `false` and will update `xbins` accordingly before deleting `autobinx` from the trace. The 'autobinx' property must be specified as a bool (either True, or False) Returns ------- bool """ return self['autobinx'] @autobinx.setter def autobinx(self, val): self['autobinx'] = val # autobiny # -------- @property def autobiny(self): """ Obsolete: since v1.42 each bin attribute is auto-determined separately and `autobiny` is not needed. However, we accept `autobiny: true` or `false` and will update `ybins` accordingly before deleting `autobiny` from the trace. The 'autobiny' property must be specified as a bool (either True, or False) Returns ------- bool """ return self['autobiny'] @autobiny.setter def autobiny(self, val): self['autobiny'] = val # cumulative # ---------- @property def cumulative(self): """ The 'cumulative' property is an instance of Cumulative that may be specified as: - An instance of plotly.graph_objs.histogram.Cumulative - A dict of string/value properties that will be passed to the Cumulative constructor Supported dict properties: currentbin Only applies if cumulative is enabled. Sets whether the current bin is included, excluded, or has half of its value included in the current cumulative value. "include" is the default for compatibility with various other tools, however it introduces a half-bin bias to the results. "exclude" makes the opposite half- bin bias, and "half" removes it. direction Only applies if cumulative is enabled. If "increasing" (default) we sum all prior bins, so the result increases from left to right. If "decreasing" we sum later bins so the result decreases from left to right. enabled If true, display the cumulative distribution by summing the binned values. Use the `direction` and `centralbin` attributes to tune the accumulation method. Note: in this mode, the "density" `histnorm` settings behave the same as their equivalents without "density": "" and "density" both rise to the number of data points, and "probability" and *probability density* both rise to the number of sample points. Returns ------- plotly.graph_objs.histogram.Cumulative """ return self['cumulative'] @cumulative.setter def cumulative(self, val): self['cumulative'] = 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 plot.ly 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 # error_x # ------- @property def error_x(self): """ The 'error_x' property is an instance of ErrorX that may be specified as: - An instance of plotly.graph_objs.histogram.ErrorX - A dict of string/value properties that will be passed to the ErrorX constructor Supported dict properties: array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_ystyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "array", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- plotly.graph_objs.histogram.ErrorX """ return self['error_x'] @error_x.setter def error_x(self, val): self['error_x'] = val # error_y # ------- @property def error_y(self): """ The 'error_y' property is an instance of ErrorY that may be specified as: - An instance of plotly.graph_objs.histogram.ErrorY - A dict of string/value properties that will be passed to the ErrorY constructor Supported dict properties: array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "array", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- plotly.graph_objs.histogram.ErrorY """ return self['error_y'] @error_y.setter def error_y(self, val): self['error_y'] = val # histfunc # -------- @property def histfunc(self): """ Specifies the binning function used for this histogram trace. If "count", the histogram values are computed by counting the number of values lying inside each bin. If "sum", "avg", "min", "max", the histogram values are computed using the sum, the average, the minimum or the maximum of the values lying inside each bin respectively. The 'histfunc' property is an enumeration that may be specified as: - One of the following enumeration values: ['count', 'sum', 'avg', 'min', 'max'] Returns ------- Any """ return self['histfunc'] @histfunc.setter def histfunc(self, val): self['histfunc'] = val # histnorm # -------- @property def histnorm(self): """ Specifies the type of normalization used for this histogram trace. If "", the span of each bar corresponds to the number of occurrences (i.e. the number of data points lying inside the bins). If "percent" / "probability", the span of each bar corresponds to the percentage / fraction of occurrences with respect to the total number of sample points (here, the sum of all bin HEIGHTS equals 100% / 1). If "density", the span of each bar corresponds to the number of occurrences in a bin divided by the size of the bin interval (here, the sum of all bin AREAS equals the total number of sample points). If *probability density*, the area of each bar corresponds to the probability that an event will fall into the corresponding bin (here, the sum of all bin AREAS equals 1). The 'histnorm' property is an enumeration that may be specified as: - One of the following enumeration values: ['', 'percent', 'probability', 'density', 'probability density'] Returns ------- Any """ return self['histnorm'] @histnorm.setter def histnorm(self, val): self['histnorm'] = 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 plot.ly 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 plotly.graph_objs.histogram.Hoverlabel - A dict of string/value properties that will be passed to the Hoverlabel constructor Supported dict properties: bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the length (in number of characters) of the trace name in the hover labels for this trace. -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 plot.ly for namelength . Returns ------- plotly.graph_objs.histogram.Hoverlabel """ return self['hoverlabel'] @hoverlabel.setter def hoverlabel(self, val): self['hoverlabel'] = 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 plot.ly 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 # legendgroup # ----------- @property def legendgroup(self): """ Sets the legend group for this trace. Traces 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 # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of plotly.graph_objs.histogram.Marker - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. 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. colorbar plotly.graph_objs.histogram.marker.ColorBar instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)', [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu ,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,R ainbow,Portland,Jet,Hot,Blackbody,Earth,Electri c,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line plotly.graph_objs.histogram.marker.Line instance or dict with compatible properties opacity Sets the opacity of the bars. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. Returns ------- plotly.graph_objs.histogram.Marker """ return self['marker'] @marker.setter def marker(self, val): self['marker'] = val # name # ---- @property def name(self): """ Sets the trace name. The trace name appear as the legend item and on hover. 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 # nbinsx # ------ @property def nbinsx(self): """ Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `xbins.size` is provided. The 'nbinsx' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self['nbinsx'] @nbinsx.setter def nbinsx(self, val): self['nbinsx'] = val # nbinsy # ------ @property def nbinsy(self): """ Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `ybins.size` is provided. The 'nbinsy' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self['nbinsy'] @nbinsy.setter def nbinsy(self, val): self['nbinsy'] = 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 bars. With "v" ("h"), the value of the each bar spans 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 # selected # -------- @property def selected(self): """ The 'selected' property is an instance of Selected that may be specified as: - An instance of plotly.graph_objs.histogram.Selected - A dict of string/value properties that will be passed to the Selected constructor Supported dict properties: marker plotly.graph_objs.histogram.selected.Marker instance or dict with compatible properties textfont plotly.graph_objs.histogram.selected.Textfont instance or dict with compatible properties Returns ------- plotly.graph_objs.histogram.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 # stream # ------ @property def stream(self): """ The 'stream' property is an instance of Stream that may be specified as: - An instance of plotly.graph_objs.histogram.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://plot.ly/settings for more details. Returns ------- plotly.graph_objs.histogram.Stream """ return self['stream'] @stream.setter def stream(self, val): self['stream'] = val # text # ---- @property def text(self): """ Sets text elements associated with each (x,y) pair. 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. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. 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 plot.ly 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): """ 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 # unselected # ---------- @property def unselected(self): """ The 'unselected' property is an instance of Unselected that may be specified as: - An instance of plotly.graph_objs.histogram.Unselected - A dict of string/value properties that will be passed to the Unselected constructor Supported dict properties: marker plotly.graph_objs.histogram.unselected.Marker instance or dict with compatible properties textfont plotly.graph_objs.histogram.unselected.Textfont instance or dict with compatible properties Returns ------- plotly.graph_objs.histogram.Unselected """ return self['unselected'] @unselected.setter def unselected(self, val): self['unselected'] = 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 # x # - @property def x(self): """ Sets the sample data to be binned on the x axis. 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 # 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 # xbins # ----- @property def xbins(self): """ The 'xbins' property is an instance of XBins that may be specified as: - An instance of plotly.graph_objs.histogram.XBins - A dict of string/value properties that will be passed to the XBins constructor Supported dict properties: end Sets the end value for the x axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each x axis bin. Default behavior: If `nbinsx` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsx` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). If multiple non-overlaying histograms share a subplot, the first explicit `size` is used and all others discarded. If no `size` is provided,the sample data from all traces is combined to determine `size` as described above. start Sets the starting value for the x axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. If multiple non- overlaying histograms share a subplot, the first explicit `start` is used exactly and all others are shifted down (if necessary) to differ from that one by an integer number of bins. Returns ------- plotly.graph_objs.histogram.XBins """ return self['xbins'] @xbins.setter def xbins(self, val): self['xbins'] = 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: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self['xcalendar'] @xcalendar.setter def xcalendar(self, val): self['xcalendar'] = val # xsrc # ---- @property def xsrc(self): """ Sets the source reference on plot.ly 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 sample data to be binned on the y axis. 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 # 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 # ybins # ----- @property def ybins(self): """ The 'ybins' property is an instance of YBins that may be specified as: - An instance of plotly.graph_objs.histogram.YBins - A dict of string/value properties that will be passed to the YBins constructor Supported dict properties: end Sets the end value for the y axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each y axis bin. Default behavior: If `nbinsy` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsy` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). If multiple non-overlaying histograms share a subplot, the first explicit `size` is used and all others discarded. If no `size` is provided,the sample data from all traces is combined to determine `size` as described above. start Sets the starting value for the y axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. If multiple non- overlaying histograms share a subplot, the first explicit `start` is used exactly and all others are shifted down (if necessary) to differ from that one by an integer number of bins. Returns ------- plotly.graph_objs.histogram.YBins """ return self['ybins'] @ybins.setter def ybins(self, val): self['ybins'] = 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: ['gregorian', 'chinese', 'coptic', 'discworld', 'ethiopian', 'hebrew', 'islamic', 'julian', 'mayan', 'nanakshahi', 'nepali', 'persian', 'jalali', 'taiwan', 'thai', 'ummalqura'] Returns ------- Any """ return self['ycalendar'] @ycalendar.setter def ycalendar(self, val): self['ycalendar'] = val # ysrc # ---- @property def ysrc(self): """ Sets the source reference on plot.ly 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'] # property parent name # -------------------- @property def _parent_path_str(self): return '' # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autobinx Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobinx` is not needed. However, we accept `autobinx: true` or `false` and will update `xbins` accordingly before deleting `autobinx` from the trace. autobiny Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobiny` is not needed. However, we accept `autobiny: true` or `false` and will update `ybins` accordingly before deleting `autobiny` from the trace. cumulative plotly.graph_objs.histogram.Cumulative instance or dict with compatible properties 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 plot.ly for customdata . error_x plotly.graph_objs.histogram.ErrorX instance or dict with compatible properties error_y plotly.graph_objs.histogram.ErrorY instance or dict with compatible properties histfunc Specifies the binning function used for this histogram trace. If "count", the histogram values are computed by counting the number of values lying inside each bin. If "sum", "avg", "min", "max", the histogram values are computed using the sum, the average, the minimum or the maximum of the values lying inside each bin respectively. histnorm Specifies the type of normalization used for this histogram trace. If "", the span of each bar corresponds to the number of occurrences (i.e. the number of data points lying inside the bins). If "percent" / "probability", the span of each bar corresponds to the percentage / fraction of occurrences with respect to the total number of sample points (here, the sum of all bin HEIGHTS equals 100% / 1). If "density", the span of each bar corresponds to the number of occurrences in a bin divided by the size of the bin interval (here, the sum of all bin AREAS equals the total number of sample points). If *probability density*, the area of each bar corresponds to the probability that an event will fall into the corresponding bin (here, the sum of all bin AREAS equals 1). 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 plot.ly for hoverinfo . hoverlabel plotly.graph_objs.histogram.Hoverlabel instance or dict with compatible properties 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 plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objs.histogram.Marker instance or dict with compatible properties name Sets the trace name. The trace name appear as the legend item and on hover. nbinsx Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `xbins.size` is provided. nbinsy Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `ybins.size` is provided. opacity Sets the opacity of the trace. orientation Sets the orientation of the bars. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). selected plotly.graph_objs.histogram.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. stream plotly.graph_objs.histogram.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair. 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. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid unselected plotly.graph_objs.histogram.Unselected instance or dict with compatible properties 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). x Sets the sample data to be binned on the x axis. 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. xbins plotly.graph_objs.histogram.XBins instance or dict with compatible properties xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the sample data to be binned on the y axis. 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. ybins plotly.graph_objs.histogram.YBins instance or dict with compatible properties ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . """ def __init__( self, arg=None, autobinx=None, autobiny=None, cumulative=None, customdata=None, customdatasrc=None, error_x=None, error_y=None, histfunc=None, histnorm=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, ids=None, idssrc=None, legendgroup=None, marker=None, name=None, nbinsx=None, nbinsy=None, opacity=None, orientation=None, selected=None, selectedpoints=None, showlegend=None, stream=None, text=None, textsrc=None, uid=None, unselected=None, visible=None, x=None, xaxis=None, xbins=None, xcalendar=None, xsrc=None, y=None, yaxis=None, ybins=None, ycalendar=None, ysrc=None, **kwargs ): """ Construct a new Histogram object The sample data from which statistics are computed is set in `x` for vertically spanning histograms and in `y` for horizontally spanning histograms. Binning options are set `xbins` and `ybins` respectively if no aggregation data is provided. Parameters ---------- arg dict of properties compatible with this constructor or an instance of plotly.graph_objs.Histogram autobinx Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobinx` is not needed. However, we accept `autobinx: true` or `false` and will update `xbins` accordingly before deleting `autobinx` from the trace. autobiny Obsolete: since v1.42 each bin attribute is auto- determined separately and `autobiny` is not needed. However, we accept `autobiny: true` or `false` and will update `ybins` accordingly before deleting `autobiny` from the trace. cumulative plotly.graph_objs.histogram.Cumulative instance or dict with compatible properties 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 plot.ly for customdata . error_x plotly.graph_objs.histogram.ErrorX instance or dict with compatible properties error_y plotly.graph_objs.histogram.ErrorY instance or dict with compatible properties histfunc Specifies the binning function used for this histogram trace. If "count", the histogram values are computed by counting the number of values lying inside each bin. If "sum", "avg", "min", "max", the histogram values are computed using the sum, the average, the minimum or the maximum of the values lying inside each bin respectively. histnorm Specifies the type of normalization used for this histogram trace. If "", the span of each bar corresponds to the number of occurrences (i.e. the number of data points lying inside the bins). If "percent" / "probability", the span of each bar corresponds to the percentage / fraction of occurrences with respect to the total number of sample points (here, the sum of all bin HEIGHTS equals 100% / 1). If "density", the span of each bar corresponds to the number of occurrences in a bin divided by the size of the bin interval (here, the sum of all bin AREAS equals the total number of sample points). If *probability density*, the area of each bar corresponds to the probability that an event will fall into the corresponding bin (here, the sum of all bin AREAS equals 1). 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 plot.ly for hoverinfo . hoverlabel plotly.graph_objs.histogram.Hoverlabel instance or dict with compatible properties 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 plot.ly for ids . legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. marker plotly.graph_objs.histogram.Marker instance or dict with compatible properties name Sets the trace name. The trace name appear as the legend item and on hover. nbinsx Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `xbins.size` is provided. nbinsy Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if `ybins.size` is provided. opacity Sets the opacity of the trace. orientation Sets the orientation of the bars. With "v" ("h"), the value of the each bar spans along the vertical (horizontal). selected plotly.graph_objs.histogram.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. stream plotly.graph_objs.histogram.Stream instance or dict with compatible properties text Sets text elements associated with each (x,y) pair. 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. If trace `hoverinfo` contains a "text" flag and "hovertext" is not set, these elements will be seen in the hover labels. textsrc Sets the source reference on plot.ly for text . uid unselected plotly.graph_objs.histogram.Unselected instance or dict with compatible properties 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). x Sets the sample data to be binned on the x axis. 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. xbins plotly.graph_objs.histogram.XBins instance or dict with compatible properties xcalendar Sets the calendar system to use with `x` date data. xsrc Sets the source reference on plot.ly for x . y Sets the sample data to be binned on the y axis. 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. ybins plotly.graph_objs.histogram.YBins instance or dict with compatible properties ycalendar Sets the calendar system to use with `y` date data. ysrc Sets the source reference on plot.ly for y . Returns ------- Histogram """ super(Histogram, self).__init__('histogram') # 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.Histogram constructor must be a dict or an instance of plotly.graph_objs.Histogram""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop('skip_invalid', False) # Import validators # ----------------- from plotly.validators import (histogram as v_histogram) # Initialize validators # --------------------- self._validators['autobinx'] = v_histogram.AutobinxValidator() self._validators['autobiny'] = v_histogram.AutobinyValidator() self._validators['cumulative'] = v_histogram.CumulativeValidator() self._validators['customdata'] = v_histogram.CustomdataValidator() self._validators['customdatasrc' ] = v_histogram.CustomdatasrcValidator() self._validators['error_x'] = v_histogram.ErrorXValidator() self._validators['error_y'] = v_histogram.ErrorYValidator() self._validators['histfunc'] = v_histogram.HistfuncValidator() self._validators['histnorm'] = v_histogram.HistnormValidator() self._validators['hoverinfo'] = v_histogram.HoverinfoValidator() self._validators['hoverinfosrc'] = v_histogram.HoverinfosrcValidator() self._validators['hoverlabel'] = v_histogram.HoverlabelValidator() self._validators['ids'] = v_histogram.IdsValidator() self._validators['idssrc'] = v_histogram.IdssrcValidator() self._validators['legendgroup'] = v_histogram.LegendgroupValidator() self._validators['marker'] = v_histogram.MarkerValidator() self._validators['name'] = v_histogram.NameValidator() self._validators['nbinsx'] = v_histogram.NbinsxValidator() self._validators['nbinsy'] = v_histogram.NbinsyValidator() self._validators['opacity'] = v_histogram.OpacityValidator() self._validators['orientation'] = v_histogram.OrientationValidator() self._validators['selected'] = v_histogram.SelectedValidator() self._validators['selectedpoints' ] = v_histogram.SelectedpointsValidator() self._validators['showlegend'] = v_histogram.ShowlegendValidator() self._validators['stream'] = v_histogram.StreamValidator() self._validators['text'] = v_histogram.TextValidator() self._validators['textsrc'] = v_histogram.TextsrcValidator() self._validators['uid'] = v_histogram.UidValidator() self._validators['unselected'] = v_histogram.UnselectedValidator() self._validators['visible'] = v_histogram.VisibleValidator() self._validators['x'] = v_histogram.XValidator() self._validators['xaxis'] = v_histogram.XAxisValidator() self._validators['xbins'] = v_histogram.XBinsValidator() self._validators['xcalendar'] = v_histogram.XcalendarValidator() self._validators['xsrc'] = v_histogram.XsrcValidator() self._validators['y'] = v_histogram.YValidator() self._validators['yaxis'] = v_histogram.YAxisValidator() self._validators['ybins'] = v_histogram.YBinsValidator() self._validators['ycalendar'] = v_histogram.YcalendarValidator() self._validators['ysrc'] = v_histogram.YsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop('autobinx', None) self['autobinx'] = autobinx if autobinx is not None else _v _v = arg.pop('autobiny', None) self['autobiny'] = autobiny if autobiny is not None else _v _v = arg.pop('cumulative', None) self['cumulative'] = cumulative if cumulative is not None else _v _v = arg.pop('customdata', None) self['customdata'] = customdata if customdata is not None else _v _v = arg.pop('customdatasrc', None) self['customdatasrc' ] = customdatasrc if customdatasrc is not None else _v _v = arg.pop('error_x', None) self['error_x'] = error_x if error_x is not None else _v _v = arg.pop('error_y', None) self['error_y'] = error_y if error_y is not None else _v _v = arg.pop('histfunc', None) self['histfunc'] = histfunc if histfunc is not None else _v _v = arg.pop('histnorm', None) self['histnorm'] = histnorm if histnorm is not None else _v _v = arg.pop('hoverinfo', None) self['hoverinfo'] = hoverinfo if hoverinfo is not None else _v _v = arg.pop('hoverinfosrc', None) self['hoverinfosrc'] = hoverinfosrc if hoverinfosrc is not None else _v _v = arg.pop('hoverlabel', None) self['hoverlabel'] = hoverlabel if hoverlabel is not None else _v _v = arg.pop('ids', None) self['ids'] = ids if ids is not None else _v _v = arg.pop('idssrc', None) self['idssrc'] = idssrc if idssrc is not None else _v _v = arg.pop('legendgroup', None) self['legendgroup'] = legendgroup if legendgroup is not None else _v _v = arg.pop('marker', None) self['marker'] = marker if marker is not None else _v _v = arg.pop('name', None) self['name'] = name if name is not None else _v _v = arg.pop('nbinsx', None) self['nbinsx'] = nbinsx if nbinsx is not None else _v _v = arg.pop('nbinsy', None) self['nbinsy'] = nbinsy if nbinsy is not None else _v _v = arg.pop('opacity', None) self['opacity'] = opacity if opacity is not None else _v _v = arg.pop('orientation', None) self['orientation'] = orientation if orientation is not None else _v _v = arg.pop('selected', None) self['selected'] = selected if selected is not None else _v _v = arg.pop('selectedpoints', None) self['selectedpoints' ] = selectedpoints if selectedpoints is not None else _v _v = arg.pop('showlegend', None) self['showlegend'] = showlegend if showlegend is not None else _v _v = arg.pop('stream', None) self['stream'] = stream if stream is not None else _v _v = arg.pop('text', None) self['text'] = text if text is not None else _v _v = arg.pop('textsrc', None) self['textsrc'] = textsrc if textsrc is not None else _v _v = arg.pop('uid', None) self['uid'] = uid if uid is not None else _v _v = arg.pop('unselected', None) self['unselected'] = unselected if unselected is not None else _v _v = arg.pop('visible', None) self['visible'] = visible if visible is not None else _v _v = arg.pop('x', None) self['x'] = x if x is not None else _v _v = arg.pop('xaxis', None) self['xaxis'] = xaxis if xaxis is not None else _v _v = arg.pop('xbins', None) self['xbins'] = xbins if xbins is not None else _v _v = arg.pop('xcalendar', None) self['xcalendar'] = xcalendar if xcalendar is not None else _v _v = arg.pop('xsrc', None) self['xsrc'] = xsrc if xsrc is not None else _v _v = arg.pop('y', None) self['y'] = y if y is not None else _v _v = arg.pop('yaxis', None) self['yaxis'] = yaxis if yaxis is not None else _v _v = arg.pop('ybins', None) self['ybins'] = ybins if ybins is not None else _v _v = arg.pop('ycalendar', None) self['ycalendar'] = ycalendar if ycalendar is not None else _v _v = arg.pop('ysrc', None) self['ysrc'] = ysrc if ysrc is not None else _v # Read-only literals # ------------------ from _plotly_utils.basevalidators import LiteralValidator self._props['type'] = 'histogram' self._validators['type'] = LiteralValidator( plotly_name='type', parent_name='histogram', val='histogram' ) arg.pop('type', None) # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False