Python Figure Reference: histogram Traces

A plotly.graph_objects.Histogram trace is a graph object in the figure's data list with any of the named arguments or attributes listed below.

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.

  • name
    Code: fig.update_traces(name=<VALUE>, selector=dict(type='histogram'))
    Type: string

    Sets the trace name. The trace name appear as the legend item and on hover.

  • visible
    Code: fig.update_traces(visible=<VALUE>, selector=dict(type='histogram'))
    Type: enumerated , one of ( True | False | "legendonly" )
    Default: True

    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).

  • showlegend
    Code: fig.update_traces(showlegend=<VALUE>, selector=dict(type='histogram'))
    Type: boolean
    Default: True

    Determines whether or not an item corresponding to this trace is shown in the legend.

  • legendrank
    Code: fig.update_traces(legendrank=<VALUE>, selector=dict(type='histogram'))
    Type: number
    Default: 1000

    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.

  • legendgroup
    Code: fig.update_traces(legendgroup=<VALUE>, selector=dict(type='histogram'))
    Type: string
    Default: ""

    Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items.

  • legendgrouptitle
    Code: fig.update_traces(legendgrouptitle=dict(...), selector=dict(type='histogram'))
    Type: dict containing one or more of the keys listed below.
    • font
      Code: fig.update_traces(legendgrouptitle_font=dict(...), selector=dict(type='histogram'))
      Type: dict containing one or more of the keys listed below.

      Sets this legend group's title font.

      • color
        Code: fig.update_traces(legendgrouptitle_font_color=<VALUE>, selector=dict(type='histogram'))
        Type: color
      • family
        Code: fig.update_traces(legendgrouptitle_font_family=<VALUE>, selector=dict(type='histogram'))
        Type: string

        HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The Chart Studio Cloud (at https://chart-studio.plotly.com or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman".

      • size
        Code: fig.update_traces(legendgrouptitle_font_size=<VALUE>, selector=dict(type='histogram'))
        Type: number greater than or equal to 1
    • text
      Code: fig.update_traces(legendgrouptitle_text=<VALUE>, selector=dict(type='histogram'))
      Type: string
      Default: ""

      Sets the title of the legend group.

  • opacity
    Code: fig.update_traces(opacity=<VALUE>, selector=dict(type='histogram'))
    Type: number between or equal to 0 and 1
    Default: 1

    Sets the opacity of the trace.

  • ids
    Code: fig.update_traces(ids=<VALUE>, selector=dict(type='histogram'))
    Type: list, numpy array, or Pandas series of numbers, strings, or datetimes.

    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.

  • x
    Code: fig.update_traces(x=<VALUE>, selector=dict(type='histogram'))
    Type: list, numpy array, or Pandas series of numbers, strings, or datetimes.

    Sets the sample data to be binned on the x axis.

  • y
    Code: fig.update_traces(y=<VALUE>, selector=dict(type='histogram'))
    Type: list, numpy array, or Pandas series of numbers, strings, or datetimes.

    Sets the sample data to be binned on the y axis.

  • text
    Code: fig.update_traces(text=<VALUE>, selector=dict(type='histogram'))
    Type: string or array of strings
    Default: ""

    Sets hover text elements associated with each bar. If a single string, the same string appears over all bars. If an array of string, the items are mapped in order to the this trace's coordinates.

  • hovertext
    Code: fig.update_traces(hovertext=<VALUE>, selector=dict(type='histogram'))
    Type: string or array of strings
    Default: ""

    Same as `text`.

  • hoverinfo
    Code: fig.update_traces(hoverinfo=<VALUE>, selector=dict(type='histogram'))
    Type: flaglist string. Any combination of "x", "y", "z", "text", "name" joined with a "+" OR "all" or "none" or "skip".
    Examples: "x", "y", "x+y", "x+y+z", "all"
    Default: "all"

    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.

  • hovertemplate
    Code: fig.update_traces(hovertemplate=<VALUE>, selector=dict(type='histogram'))
    Type: string or array of strings
    Default: ""

    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. variable `binNumber` Anything contained in tag `<extra>` is displayed in the secondary box, for example "<extra>{fullData.name}</extra>". To hide the secondary box completely, use an empty tag `<extra></extra>`.

  • xhoverformat
    Code: fig.update_traces(xhoverformat=<VALUE>, selector=dict(type='histogram'))
    Type: string
    Default: ""

    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`.

  • yhoverformat
    Code: fig.update_traces(yhoverformat=<VALUE>, selector=dict(type='histogram'))
    Type: string
    Default: ""

    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`.

  • meta
    Code: fig.update_traces(meta=<VALUE>, selector=dict(type='histogram'))
    Type: number or categorical coordinate string

    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.

  • customdata
    Code: fig.update_traces(customdata=<VALUE>, selector=dict(type='histogram'))
    Type: list, numpy array, or Pandas series of numbers, strings, or datetimes.

    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

  • xaxis
    Code: fig.update_traces(xaxis=<VALUE>, selector=dict(type='histogram'))
    Type: subplotid
    Default: x

    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.

  • yaxis
    Code: fig.update_traces(yaxis=<VALUE>, selector=dict(type='histogram'))
    Type: subplotid
    Default: y

    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.

  • orientation
    Code: fig.update_traces(orientation=<VALUE>, selector=dict(type='histogram'))
    Type: enumerated , one of ( "v" | "h" )

    Sets the orientation of the bars. With "v" ("h"), the value of the each bar spans along the vertical (horizontal).

  • histfunc
    Code: fig.update_traces(histfunc=<VALUE>, selector=dict(type='histogram'))
    Type: enumerated , one of ( "count" | "sum" | "avg" | "min" | "max" )
    Default: "count"

    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
    Code: fig.update_traces(histnorm=<VALUE>, selector=dict(type='histogram'))
    Type: enumerated , one of ( "" | "percent" | "probability" | "density" | "probability density" )
    Default: ""

    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).

  • alignmentgroup
    Code: fig.update_traces(alignmentgroup=<VALUE>, selector=dict(type='histogram'))
    Type: string
    Default: ""

    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.

  • offsetgroup
    Code: fig.update_traces(offsetgroup=<VALUE>, selector=dict(type='histogram'))
    Type: string
    Default: ""

    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.

  • nbinsx
    Code: fig.update_traces(nbinsx=<VALUE>, selector=dict(type='histogram'))
    Type: integer greater than or equal to 0
    Default: 0

    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
    Code: fig.update_traces(nbinsy=<VALUE>, selector=dict(type='histogram'))
    Type: integer greater than or equal to 0
    Default: 0

    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.

  • autobinx
    Code: fig.update_traces(autobinx=<VALUE>, selector=dict(type='histogram'))
    Type: boolean

    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
    Code: fig.update_traces(autobiny=<VALUE>, selector=dict(type='histogram'))
    Type: boolean

    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.

  • bingroup
    Code: fig.update_traces(bingroup=<VALUE>, selector=dict(type='histogram'))
    Type: string
    Default: ""

    Set a group of histogram traces which will have compatible bin settings. Note that traces on the same subplot and with the same "orientation" under `barmode` "stack", "relative" and "group" are forced into the same bingroup, Using `bingroup`, traces under `barmode` "overlay" and on different axes (of the same axis type) can have compatible bin settings. Note that histogram and histogram2d" trace can share the same `bingroup`

  • xbins
    Code: fig.update_traces(xbins=dict(...), selector=dict(type='histogram'))
    Type: dict containing one or more of the keys listed below.
    • end
      Code: fig.update_traces(xbins_end=<VALUE>, selector=dict(type='histogram'))
      Type: number or categorical coordinate string

      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
      Code: fig.update_traces(xbins_size=<VALUE>, selector=dict(type='histogram'))
      Type: number or categorical coordinate string

      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<n>" 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
      Code: fig.update_traces(xbins_start=<VALUE>, selector=dict(type='histogram'))
      Type: number or categorical coordinate string

      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.

  • ybins
    Code: fig.update_traces(ybins=dict(...), selector=dict(type='histogram'))
    Type: dict containing one or more of the keys listed below.
    • end
      Code: fig.update_traces(ybins_end=<VALUE>, selector=dict(type='histogram'))
      Type: number or categorical coordinate string

      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
      Code: fig.update_traces(ybins_size=<VALUE>, selector=dict(type='histogram'))
      Type: number or categorical coordinate string

      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<n>" 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
      Code: fig.update_traces(ybins_start=<VALUE>, selector=dict(type='histogram'))
      Type: number or categorical coordinate string

      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.

  • marker
    Code: fig.update_traces(marker=dict(...), selector=dict(type='histogram'))
    Type: dict containing one or more of the keys listed below.
    • autocolorscale
      Code: fig.update_traces(marker_autocolorscale=<VALUE>, selector=dict(type='histogram'))
      Type: boolean
      Default: True

      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
      Code: fig.update_traces(marker_cauto=<VALUE>, selector=dict(type='histogram'))
      Type: boolean
      Default: True

      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
      Code: fig.update_traces(marker_cmax=<VALUE>, selector=dict(type='histogram'))
      Type: number

      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.

    • cmid
      Code: fig.update_traces(marker_cmid=<VALUE>, selector=dict(type='histogram'))
      Type: number

      Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `False`.

    • cmin
      Code: fig.update_traces(marker_cmin=<VALUE>, selector=dict(type='histogram'))
      Type: number

      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
      Code: fig.update_traces(marker_color=<VALUE>, selector=dict(type='histogram'))
      Type: color or array of colors

      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.

    • coloraxis
      Code: fig.update_traces(marker_coloraxis=<VALUE>, selector=dict(type='histogram'))
      Type: subplotid

      Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis.

    • colorbar
      Code: fig.update_traces(marker_colorbar=dict(...), selector=dict(type='histogram'))
      Type: dict containing one or more of the keys listed below.
      • bgcolor
        Code: fig.update_traces(marker_colorbar_bgcolor=<VALUE>, selector=dict(type='histogram'))
        Type: color
        Default: "rgba(0,0,0,0)"

        Sets the color of padded area.

      • bordercolor
        Code: fig.update_traces(marker_colorbar_bordercolor=<VALUE>, selector=dict(type='histogram'))
        Type: color
        Default: "#444"

        Sets the axis line color.

      • borderwidth
        Code: fig.update_traces(marker_colorbar_borderwidth=<VALUE>, selector=dict(type='histogram'))
        Type: number greater than or equal to 0
        Default: 0

        Sets the width (in px) or the border enclosing this color bar.

      • dtick
        Code: fig.update_traces(marker_colorbar_dtick=<VALUE>, selector=dict(type='histogram'))
        Type: number or categorical coordinate string

        Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n"dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L<f>", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M<n>" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48"

      • exponentformat
        Code: fig.update_traces(marker_colorbar_exponentformat=<VALUE>, selector=dict(type='histogram'))
        Type: enumerated , one of ( "none" | "e" | "E" | "power" | "SI" | "B" )
        Default: "B"

        Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B.

      • len
        Code: fig.update_traces(marker_colorbar_len=<VALUE>, selector=dict(type='histogram'))
        Type: number greater than or equal to 0
        Default: 1

        Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends.

      • lenmode
        Code: fig.update_traces(marker_colorbar_lenmode=<VALUE>, selector=dict(type='histogram'))
        Type: enumerated , one of ( "fraction" | "pixels" )
        Default: "fraction"

        Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in "pixels. Use `len` to set the value.

      • minexponent
        Code: fig.update_traces(marker_colorbar_minexponent=<VALUE>, selector=dict(type='histogram'))
        Type: number greater than or equal to 0
        Default: 3

        Hide SI prefix for 10^n if |n| is below this number. This only has an effect when `tickformat` is "SI" or "B".

      • nticks
        Code: fig.update_traces(marker_colorbar_nticks=<VALUE>, selector=dict(type='histogram'))
        Type: integer greater than or equal to 0
        Default: 0

        Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto".

      • outlinecolor
        Code: fig.update_traces(marker_colorbar_outlinecolor=<VALUE>, selector=dict(type='histogram'))
        Type: color
        Default: "#444"

        Sets the axis line color.

      • outlinewidth
        Code: fig.update_traces(marker_colorbar_outlinewidth=<VALUE>, selector=dict(type='histogram'))
        Type: number greater than or equal to 0
        Default: 1

        Sets the width (in px) of the axis line.

      • separatethousands
        Code: fig.update_traces(marker_colorbar_separatethousands=<VALUE>, selector=dict(type='histogram'))
        Type: boolean

        If "True", even 4-digit integers are separated

      • showexponent
        Code: fig.update_traces(marker_colorbar_showexponent=<VALUE>, selector=dict(type='histogram'))
        Type: enumerated , one of ( "all" | "first" | "last" | "none" )
        Default: "all"

        If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear.

      • showticklabels
        Code: fig.update_traces(marker_colorbar_showticklabels=<VALUE>, selector=dict(type='histogram'))
        Type: boolean
        Default: True

        Determines whether or not the tick labels are drawn.

      • showtickprefix
        Code: fig.update_traces(marker_colorbar_showtickprefix=<VALUE>, selector=dict(type='histogram'))
        Type: enumerated , one of ( "all" | "first" | "last" | "none" )
        Default: "all"

        If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden.

      • showticksuffix
        Code: fig.update_traces(marker_colorbar_showticksuffix=<VALUE>, selector=dict(type='histogram'))
        Type: enumerated , one of ( "all" | "first" | "last" | "none" )
        Default: "all"

        Same as `showtickprefix` but for tick suffixes.

      • thickness
        Code: fig.update_traces(marker_colorbar_thickness=<VALUE>, selector=dict(type='histogram'))
        Type: number greater than or equal to 0
        Default: 30

        Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels.

      • thicknessmode
        Code: fig.update_traces(marker_colorbar_thicknessmode=<VALUE>, selector=dict(type='histogram'))
        Type: enumerated , one of ( "fraction" | "pixels" )
        Default: "pixels"

        Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value.

      • tick0
        Code: fig.update_traces(marker_colorbar_tick0=<VALUE>, selector=dict(type='histogram'))
        Type: number or categorical coordinate string

        Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`="L<f>" (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears.

      • tickangle
        Code: fig.update_traces(marker_colorbar_tickangle=<VALUE>, selector=dict(type='histogram'))
        Type: angle
        Default: "auto"

        Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically.

      • tickcolor
        Code: fig.update_traces(marker_colorbar_tickcolor=<VALUE>, selector=dict(type='histogram'))
        Type: color
        Default: "#444"

        Sets the tick color.

      • tickfont
        Code: fig.update_traces(marker_colorbar_tickfont=dict(...), selector=dict(type='histogram'))
        Type: dict containing one or more of the keys listed below.

        Sets the color bar's tick label font

        • color
          Code: fig.update_traces(marker_colorbar_tickfont_color=<VALUE>, selector=dict(type='histogram'))
          Type: color
        • family
          Code: fig.update_traces(marker_colorbar_tickfont_family=<VALUE>, selector=dict(type='histogram'))
          Type: string

          HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The Chart Studio Cloud (at https://chart-studio.plotly.com or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman".

        • size
          Code: fig.update_traces(marker_colorbar_tickfont_size=<VALUE>, selector=dict(type='histogram'))
          Type: number greater than or equal to 1
      • tickformat
        Code: fig.update_traces(marker_colorbar_tickformat=<VALUE>, selector=dict(type='histogram'))
        Type: string
        Default: ""

        Sets the tick label formatting rule 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"

      • tickformatstops
        Code: fig.update_traces(marker_colorbar_tickformatstops=list(...), selector=dict(type='histogram'))
        Type: list of dict where each dict has one or more of the keys listed below.
        • dtickrange
          Parent: data[type=histogram].marker.colorbar.tickformatstops[]
          Type: list

          range ["min", "max"], where "min", "max" - dtick values which describe some zoom level, it is possible to omit "min" or "max" value by passing "null"

        • enabled
          Parent: data[type=histogram].marker.colorbar.tickformatstops[]
          Type: boolean
          Default: True

          Determines whether or not this stop is used. If `False`, this stop is ignored even within its `dtickrange`.

        • name
          Parent: data[type=histogram].marker.colorbar.tickformatstops[]
          Type: string

          When used in a template, named items are created in the output figure in addition to any items the figure already has in this array. You can modify these items in the output figure by making your own item with `templateitemname` matching this `name` alongside your modifications (including `visible: False` or `enabled: False` to hide it). Has no effect outside of a template.

        • templateitemname
          Parent: data[type=histogram].marker.colorbar.tickformatstops[]
          Type: string

          Used to refer to a named item in this array in the template. Named items from the template will be created even without a matching item in the input figure, but you can modify one by making an item with `templateitemname` matching its `name`, alongside your modifications (including `visible: False` or `enabled: False` to hide it). If there is no template or no matching item, this item will be hidden unless you explicitly show it with `visible: True`.

        • value
          Parent: data[type=histogram].marker.colorbar.tickformatstops[]
          Type: string
          Default: ""

          string - dtickformat for described zoom level, the same as "tickformat"

      • ticklabeloverflow
        Code: fig.update_traces(marker_colorbar_ticklabeloverflow=<VALUE>, selector=dict(type='histogram'))
        Type: enumerated , one of ( "allow" | "hide past div" | "hide past domain" )

        Determines how we handle tick labels that would overflow either the graph div or the domain of the axis. The default value for inside tick labels is "hide past domain". In other cases the default is "hide past div".

      • ticklabelposition
        Code: fig.update_traces(marker_colorbar_ticklabelposition=<VALUE>, selector=dict(type='histogram'))
        Type: enumerated , one of ( "outside" | "inside" | "outside top" | "inside top" | "outside bottom" | "inside bottom" )
        Default: "outside"

        Determines where tick labels are drawn.

      • ticklen
        Code: fig.update_traces(marker_colorbar_ticklen=<VALUE>, selector=dict(type='histogram'))
        Type: number greater than or equal to 0
        Default: 5

        Sets the tick length (in px).

      • tickmode
        Code: fig.update_traces(marker_colorbar_tickmode=<VALUE>, selector=dict(type='histogram'))
        Type: enumerated , one of ( "auto" | "linear" | "array" )

        Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided).

      • tickprefix
        Code: fig.update_traces(marker_colorbar_tickprefix=<VALUE>, selector=dict(type='histogram'))
        Type: string
        Default: ""

        Sets a tick label prefix.

      • ticks
        Code: fig.update_traces(marker_colorbar_ticks=<VALUE>, selector=dict(type='histogram'))
        Type: enumerated , one of ( "outside" | "inside" | "" )
        Default: ""

        Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines.

      • ticksuffix
        Code: fig.update_traces(marker_colorbar_ticksuffix=<VALUE>, selector=dict(type='histogram'))
        Type: string
        Default: ""

        Sets a tick label suffix.

      • ticktext
        Code: fig.update_traces(marker_colorbar_ticktext=<VALUE>, selector=dict(type='histogram'))
        Type: list, numpy array, or Pandas series of numbers, strings, or datetimes.

        Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`.

      • tickvals
        Code: fig.update_traces(marker_colorbar_tickvals=<VALUE>, selector=dict(type='histogram'))
        Type: list, numpy array, or Pandas series of numbers, strings, or datetimes.

        Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`.

      • tickwidth
        Code: fig.update_traces(marker_colorbar_tickwidth=<VALUE>, selector=dict(type='histogram'))
        Type: number greater than or equal to 0
        Default: 1

        Sets the tick width (in px).

      • title
        Code: fig.update_traces(marker_colorbar_title=dict(...), selector=dict(type='histogram'))
        Type: dict containing one or more of the keys listed below.
        • font
          Code: fig.update_traces(marker_colorbar_title_font=dict(...), selector=dict(type='histogram'))
          Type: dict containing one or more of the keys listed below.

          Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute.

          • color
            Code: fig.update_traces(marker_colorbar_title_font_color=<VALUE>, selector=dict(type='histogram'))
            Type: color
          • family
            Code: fig.update_traces(marker_colorbar_title_font_family=<VALUE>, selector=dict(type='histogram'))
            Type: string

            HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The Chart Studio Cloud (at https://chart-studio.plotly.com or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman".

          • size
            Code: fig.update_traces(marker_colorbar_title_font_size=<VALUE>, selector=dict(type='histogram'))
            Type: number greater than or equal to 1
        • side
          Code: fig.update_traces(marker_colorbar_title_side=<VALUE>, selector=dict(type='histogram'))
          Type: enumerated , one of ( "right" | "top" | "bottom" )
          Default: "top"

          Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute.

        • text
          Code: fig.update_traces(marker_colorbar_title_text=<VALUE>, selector=dict(type='histogram'))
          Type: string

          Sets the title of the color bar. Note that before the existence of `title.text`, the title's contents used to be defined as the `title` attribute itself. This behavior has been deprecated.

      • x
        Code: fig.update_traces(marker_colorbar_x=<VALUE>, selector=dict(type='histogram'))
        Type: number between or equal to -2 and 3
        Default: 1.02

        Sets the x position of the color bar (in plot fraction).

      • xanchor
        Code: fig.update_traces(marker_colorbar_xanchor=<VALUE>, selector=dict(type='histogram'))
        Type: enumerated , one of ( "left" | "center" | "right" )
        Default: "left"

        Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar.

      • xpad
        Code: fig.update_traces(marker_colorbar_xpad=<VALUE>, selector=dict(type='histogram'))
        Type: number greater than or equal to 0
        Default: 10

        Sets the amount of padding (in px) along the x direction.

      • y
        Code: fig.update_traces(marker_colorbar_y=<VALUE>, selector=dict(type='histogram'))
        Type: number between or equal to -2 and 3
        Default: 0.5

        Sets the y position of the color bar (in plot fraction).

      • yanchor
        Code: fig.update_traces(marker_colorbar_yanchor=<VALUE>, selector=dict(type='histogram'))
        Type: enumerated , one of ( "top" | "middle" | "bottom" )
        Default: "middle"

        Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar.

      • ypad
        Code: fig.update_traces(marker_colorbar_ypad=<VALUE>, selector=dict(type='histogram'))
        Type: number greater than or equal to 0
        Default: 10

        Sets the amount of padding (in px) along the y direction.

    • colorscale
      Code: fig.update_traces(marker_colorscale=<VALUE>, selector=dict(type='histogram'))
      Type: 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: Blackbody,Bluered,Blues,Cividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd.

    • line
      Code: fig.update_traces(marker_line=dict(...), selector=dict(type='histogram'))
      Type: dict containing one or more of the keys listed below.
      • autocolorscale
        Code: fig.update_traces(marker_line_autocolorscale=<VALUE>, selector=dict(type='histogram'))
        Type: boolean
        Default: True

        Determines whether the colorscale is a default palette (`autocolorscale: True`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.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
        Code: fig.update_traces(marker_line_cauto=<VALUE>, selector=dict(type='histogram'))
        Type: boolean
        Default: True

        Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `False` when `marker.line.cmin` and `marker.line.cmax` are set by the user.

      • cmax
        Code: fig.update_traces(marker_line_cmax=<VALUE>, selector=dict(type='histogram'))
        Type: number

        Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well.

      • cmid
        Code: fig.update_traces(marker_line_cmid=<VALUE>, selector=dict(type='histogram'))
        Type: number

        Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `False`.

      • cmin
        Code: fig.update_traces(marker_line_cmin=<VALUE>, selector=dict(type='histogram'))
        Type: number

        Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well.

      • color
        Code: fig.update_traces(marker_line_color=<VALUE>, selector=dict(type='histogram'))
        Type: color or array of colors

        Sets themarker.linecolor. 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.line.cmin` and `marker.line.cmax` if set.

      • coloraxis
        Code: fig.update_traces(marker_line_coloraxis=<VALUE>, selector=dict(type='histogram'))
        Type: subplotid

        Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis.

      • colorscale
        Code: fig.update_traces(marker_line_colorscale=<VALUE>, selector=dict(type='histogram'))
        Type: colorscale

        Sets the colorscale. Has an effect only if in `marker.line.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.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Blackbody,Bluered,Blues,Cividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd.

      • reversescale
        Code: fig.update_traces(marker_line_reversescale=<VALUE>, selector=dict(type='histogram'))
        Type: boolean

        Reverses the color mapping if True. Has an effect only if in `marker.line.color`is set to a numerical array. If True, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color.

      • width
        Code: fig.update_traces(marker_line_width=<VALUE>, selector=dict(type='histogram'))
        Type: number or array of numbers greater than or equal to 0
        Default: 0

        Sets the width (in px) of the lines bounding the marker points.

    • opacity
      Code: fig.update_traces(marker_opacity=<VALUE>, selector=dict(type='histogram'))
      Type: number or array of numbers between or equal to 0 and 1
      Default: 1

      Sets the opacity of the bars.

    • pattern
      Code: fig.update_traces(marker_pattern=dict(...), selector=dict(type='histogram'))
      Type: dict containing one or more of the keys listed below.

      Sets the pattern within the marker.

      • bgcolor
        Code: fig.update_traces(marker_pattern_bgcolor=<VALUE>, selector=dict(type='histogram'))
        Type: color or array of colors

        When there is no colorscale sets the color of background pattern fill. Defaults to a `marker.color` background when `fillmode` is "overlay". Otherwise, defaults to a transparent background.

      • fgcolor
        Code: fig.update_traces(marker_pattern_fgcolor=<VALUE>, selector=dict(type='histogram'))
        Type: color or array of colors

        When there is no colorscale sets the color of foreground pattern fill. Defaults to a `marker.color` background when `fillmode` is "replace". Otherwise, defaults to dark grey or white to increase contrast with the `bgcolor`.

      • fgopacity
        Code: fig.update_traces(marker_pattern_fgopacity=<VALUE>, selector=dict(type='histogram'))
        Type: number between or equal to 0 and 1

        Sets the opacity of the foreground pattern fill. Defaults to a 0.5 when `fillmode` is "overlay". Otherwise, defaults to 1.

      • fillmode
        Code: fig.update_traces(marker_pattern_fillmode=<VALUE>, selector=dict(type='histogram'))
        Type: enumerated , one of ( "replace" | "overlay" )
        Default: "replace"

        Determines whether `marker.color` should be used as a default to `bgcolor` or a `fgcolor`.

      • shape
        Code: fig.update_traces(marker_pattern_shape=<VALUE>, selector=dict(type='histogram'))
        Type: enumerated or array of enumerateds , one of ( "" | "/" | "\" | "x" | "-" | "|" | "+" | "." )
        Default: ""

        Sets the shape of the pattern fill. By default, no pattern is used for filling the area.

      • size
        Code: fig.update_traces(marker_pattern_size=<VALUE>, selector=dict(type='histogram'))
        Type: number or array of numbers greater than or equal to 0
        Default: 8

        Sets the size of unit squares of the pattern fill in pixels, which corresponds to the interval of repetition of the pattern.

      • solidity
        Code: fig.update_traces(marker_pattern_solidity=<VALUE>, selector=dict(type='histogram'))
        Type: number or array of numbers between or equal to 0 and 1
        Default: 0.3

        Sets the solidity of the pattern fill. Solidity is roughly the fraction of the area filled by the pattern. Solidity of 0 shows only the background color without pattern and solidty of 1 shows only the foreground color without pattern.

    • reversescale
      Code: fig.update_traces(marker_reversescale=<VALUE>, selector=dict(type='histogram'))
      Type: boolean

      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
      Code: fig.update_traces(marker_showscale=<VALUE>, selector=dict(type='histogram'))
      Type: boolean

      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.

  • error_x
    Code: fig.update_traces(error_x=dict(...), selector=dict(type='histogram'))
    Type: dict containing one or more of the keys listed below.
    • array
      Code: fig.update_traces(error_x_array=<VALUE>, selector=dict(type='histogram'))
      Type: list, numpy array, or Pandas series of numbers, strings, or datetimes.

      Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data.

    • arrayminus
      Code: fig.update_traces(error_x_arrayminus=<VALUE>, selector=dict(type='histogram'))
      Type: list, numpy array, or Pandas series of numbers, strings, or datetimes.

      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.

    • color
      Code: fig.update_traces(error_x_color=<VALUE>, selector=dict(type='histogram'))
      Type: color

      Sets the stoke color of the error bars.

    • copy_ystyle
      Code: fig.update_traces(error_x_copy_ystyle=<VALUE>, selector=dict(type='histogram'))
      Type: boolean
    • symmetric
      Code: fig.update_traces(error_x_symmetric=<VALUE>, selector=dict(type='histogram'))
      Type: boolean

      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
      Code: fig.update_traces(error_x_thickness=<VALUE>, selector=dict(type='histogram'))
      Type: number greater than or equal to 0
      Default: 2

      Sets the thickness (in px) of the error bars.

    • traceref
      Code: fig.update_traces(error_x_traceref=<VALUE>, selector=dict(type='histogram'))
      Type: integer greater than or equal to 0
      Default: 0
    • tracerefminus
      Code: fig.update_traces(error_x_tracerefminus=<VALUE>, selector=dict(type='histogram'))
      Type: integer greater than or equal to 0
      Default: 0
    • type
      Code: fig.update_traces(error_x_type=<VALUE>, selector=dict(type='histogram'))
      Type: enumerated , one of ( "percent" | "constant" | "sqrt" | "data" )

      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 square of the underlying data. If "data", the bar lengths are set with data set `array`.

    • value
      Code: fig.update_traces(error_x_value=<VALUE>, selector=dict(type='histogram'))
      Type: number greater than or equal to 0
      Default: 10

      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
      Code: fig.update_traces(error_x_valueminus=<VALUE>, selector=dict(type='histogram'))
      Type: number greater than or equal to 0
      Default: 10

      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
      Code: fig.update_traces(error_x_visible=<VALUE>, selector=dict(type='histogram'))
      Type: boolean

      Determines whether or not this set of error bars is visible.

    • width
      Code: fig.update_traces(error_x_width=<VALUE>, selector=dict(type='histogram'))
      Type: number greater than or equal to 0

      Sets the width (in px) of the cross-bar at both ends of the error bars.

  • error_y
    Code: fig.update_traces(error_y=dict(...), selector=dict(type='histogram'))
    Type: dict containing one or more of the keys listed below.
    • array
      Code: fig.update_traces(error_y_array=<VALUE>, selector=dict(type='histogram'))
      Type: list, numpy array, or Pandas series of numbers, strings, or datetimes.

      Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data.

    • arrayminus
      Code: fig.update_traces(error_y_arrayminus=<VALUE>, selector=dict(type='histogram'))
      Type: list, numpy array, or Pandas series of numbers, strings, or datetimes.

      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.

    • color
      Code: fig.update_traces(error_y_color=<VALUE>, selector=dict(type='histogram'))
      Type: color

      Sets the stoke color of the error bars.

    • symmetric
      Code: fig.update_traces(error_y_symmetric=<VALUE>, selector=dict(type='histogram'))
      Type: boolean

      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
      Code: fig.update_traces(error_y_thickness=<VALUE>, selector=dict(type='histogram'))
      Type: number greater than or equal to 0
      Default: 2

      Sets the thickness (in px) of the error bars.

    • traceref
      Code: fig.update_traces(error_y_traceref=<VALUE>, selector=dict(type='histogram'))
      Type: integer greater than or equal to 0
      Default: 0
    • tracerefminus
      Code: fig.update_traces(error_y_tracerefminus=<VALUE>, selector=dict(type='histogram'))
      Type: integer greater than or equal to 0
      Default: 0
    • type
      Code: fig.update_traces(error_y_type=<VALUE>, selector=dict(type='histogram'))
      Type: enumerated , one of ( "percent" | "constant" | "sqrt" | "data" )

      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 square of the underlying data. If "data", the bar lengths are set with data set `array`.

    • value
      Code: fig.update_traces(error_y_value=<VALUE>, selector=dict(type='histogram'))
      Type: number greater than or equal to 0
      Default: 10

      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
      Code: fig.update_traces(error_y_valueminus=<VALUE>, selector=dict(type='histogram'))
      Type: number greater than or equal to 0
      Default: 10

      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
      Code: fig.update_traces(error_y_visible=<VALUE>, selector=dict(type='histogram'))
      Type: boolean

      Determines whether or not this set of error bars is visible.

    • width
      Code: fig.update_traces(error_y_width=<VALUE>, selector=dict(type='histogram'))
      Type: number greater than or equal to 0

      Sets the width (in px) of the cross-bar at both ends of the error bars.

  • selectedpoints
    Code: fig.update_traces(selectedpoints=<VALUE>, selector=dict(type='histogram'))
    Type: number or categorical coordinate string

    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.

  • selected
    Code: fig.update_traces(selected=dict(...), selector=dict(type='histogram'))
    Type: dict containing one or more of the keys listed below.
    • marker
      Code: fig.update_traces(selected_marker=dict(...), selector=dict(type='histogram'))
      Type: dict containing one or more of the keys listed below.
      • color
        Code: fig.update_traces(selected_marker_color=<VALUE>, selector=dict(type='histogram'))
        Type: color

        Sets the marker color of selected points.

      • opacity
        Code: fig.update_traces(selected_marker_opacity=<VALUE>, selector=dict(type='histogram'))
        Type: number between or equal to 0 and 1

        Sets the marker opacity of selected points.

    • textfont
      Code: fig.update_traces(selected_textfont=dict(...), selector=dict(type='histogram'))
      Type: dict containing one or more of the keys listed below.
      • color
        Code: fig.update_traces(selected_textfont_color=<VALUE>, selector=dict(type='histogram'))
        Type: color

        Sets the text font color of selected points.

  • unselected
    Code: fig.update_traces(unselected=dict(...), selector=dict(type='histogram'))
    Type: dict containing one or more of the keys listed below.
    • marker
      Code: fig.update_traces(unselected_marker=dict(...), selector=dict(type='histogram'))
      Type: dict containing one or more of the keys listed below.
      • color
        Code: fig.update_traces(unselected_marker_color=<VALUE>, selector=dict(type='histogram'))
        Type: color

        Sets the marker color of unselected points, applied only when a selection exists.

      • opacity
        Code: fig.update_traces(unselected_marker_opacity=<VALUE>, selector=dict(type='histogram'))
        Type: number between or equal to 0 and 1

        Sets the marker opacity of unselected points, applied only when a selection exists.

    • textfont
      Code: fig.update_traces(unselected_textfont=dict(...), selector=dict(type='histogram'))
      Type: dict containing one or more of the keys listed below.
      • color
        Code: fig.update_traces(unselected_textfont_color=<VALUE>, selector=dict(type='histogram'))
        Type: color

        Sets the text font color of unselected points, applied only when a selection exists.

  • cumulative
    Code: fig.update_traces(cumulative=dict(...), selector=dict(type='histogram'))
    Type: dict containing one or more of the keys listed below.
    • currentbin
      Code: fig.update_traces(cumulative_currentbin=<VALUE>, selector=dict(type='histogram'))
      Type: enumerated , one of ( "include" | "exclude" | "half" )
      Default: "include"

      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
      Code: fig.update_traces(cumulative_direction=<VALUE>, selector=dict(type='histogram'))
      Type: enumerated , one of ( "increasing" | "decreasing" )
      Default: "increasing"

      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
      Code: fig.update_traces(cumulative_enabled=<VALUE>, selector=dict(type='histogram'))
      Type: boolean

      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.

  • hoverlabel
    Code: fig.update_traces(hoverlabel=dict(...), selector=dict(type='histogram'))
    Type: dict containing one or more of the keys listed below.
    • align
      Code: fig.update_traces(hoverlabel_align=<VALUE>, selector=dict(type='histogram'))
      Type: enumerated or array of enumerateds , one of ( "left" | "right" | "auto" )
      Default: "auto"

      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

    • bgcolor
      Code: fig.update_traces(hoverlabel_bgcolor=<VALUE>, selector=dict(type='histogram'))
      Type: color or array of colors

      Sets the background color of the hover labels for this trace

    • bordercolor
      Code: fig.update_traces(hoverlabel_bordercolor=<VALUE>, selector=dict(type='histogram'))
      Type: color or array of colors

      Sets the border color of the hover labels for this trace.

    • font
      Code: fig.update_traces(hoverlabel_font=dict(...), selector=dict(type='histogram'))
      Type: dict containing one or more of the keys listed below.

      Sets the font used in hover labels.

      • color
        Code: fig.update_traces(hoverlabel_font_color=<VALUE>, selector=dict(type='histogram'))
        Type: color or array of colors
      • family
        Code: fig.update_traces(hoverlabel_font_family=<VALUE>, selector=dict(type='histogram'))
        Type: string or array of strings

        HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The Chart Studio Cloud (at https://chart-studio.plotly.com or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman".

      • size
        Code: fig.update_traces(hoverlabel_font_size=<VALUE>, selector=dict(type='histogram'))
        Type: number or array of numbers greater than or equal to 1
    • namelength
      Code: fig.update_traces(hoverlabel_namelength=<VALUE>, selector=dict(type='histogram'))
      Type: integer or array of integers greater than or equal to -1
      Default: 15

      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.

  • xcalendar
    Code: fig.update_traces(xcalendar=<VALUE>, selector=dict(type='histogram'))
    Type: enumerated , one of ( "chinese" | "coptic" | "discworld" | "ethiopian" | "gregorian" | "hebrew" | "islamic" | "jalali" | "julian" | "mayan" | "nanakshahi" | "nepali" | "persian" | "taiwan" | "thai" | "ummalqura" )
    Default: "gregorian"

    Sets the calendar system to use with `x` date data.

  • ycalendar
    Code: fig.update_traces(ycalendar=<VALUE>, selector=dict(type='histogram'))
    Type: enumerated , one of ( "chinese" | "coptic" | "discworld" | "ethiopian" | "gregorian" | "hebrew" | "islamic" | "jalali" | "julian" | "mayan" | "nanakshahi" | "nepali" | "persian" | "taiwan" | "thai" | "ummalqura" )
    Default: "gregorian"

    Sets the calendar system to use with `y` date data.

  • uirevision
    Code: fig.update_traces(uirevision=<VALUE>, selector=dict(type='histogram'))
    Type: number or categorical coordinate string

    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.