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Python Figure Reference: histogram2dcontour Traces

A plotly.graph_objects.Histogram2Dcontour 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` and `y` (where `x` and `y` represent marginal distributions, binning is set in `xbins` and `ybins` in this case) or `z` (where `z` represent the 2D distribution and binning set, binning is set by `x` and `y` in this case). The resulting distribution is visualized as a contour plot.

  • name
    Code: fig.update_traces(name=<VALUE>, selector=dict(type='histogram2dcontour'))
    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='histogram2dcontour'))
    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='histogram2dcontour'))
    Type: boolean
    Default: True

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

  • legendgroup
    Code: fig.update_traces(legendgroup=<VALUE>, selector=dict(type='histogram2dcontour'))
    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.

  • opacity
    Code: fig.update_traces(opacity=<VALUE>, selector=dict(type='histogram2dcontour'))
    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='histogram2dcontour'))
    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='histogram2dcontour'))
    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='histogram2dcontour'))
    Type: list, numpy array, or Pandas series of numbers, strings, or datetimes.

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

  • z
    Code: fig.update_traces(z=<VALUE>, selector=dict(type='histogram2dcontour'))
    Type: list, numpy array, or Pandas series of numbers, strings, or datetimes.

    Sets the aggregation data.

  • hoverinfo
    Code: fig.update_traces(hoverinfo=<VALUE>, selector=dict(type='histogram2dcontour'))
    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='histogram2dcontour'))
    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}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". https://github.com/d3/d3-3.x-api-reference/blob/master/Formatting.md#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#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 `z` 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>`.

  • meta
    Code: fig.update_traces(meta=<VALUE>, selector=dict(type='histogram2dcontour'))
    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='histogram2dcontour'))
    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='histogram2dcontour'))
    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='histogram2dcontour'))
    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.

  • coloraxis
    Code: fig.update_traces(coloraxis=<VALUE>, selector=dict(type='histogram2dcontour'))
    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.

  • histfunc
    Code: fig.update_traces(histfunc=<VALUE>, selector=dict(type='histogram2dcontour'))
    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='histogram2dcontour'))
    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).

  • nbinsx
    Code: fig.update_traces(nbinsx=<VALUE>, selector=dict(type='histogram2dcontour'))
    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='histogram2dcontour'))
    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='histogram2dcontour'))
    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='histogram2dcontour'))
    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='histogram2dcontour'))
    Type: string
    Default: ""

    Set the `xbingroup` and `ybingroup` default prefix For example, setting a `bingroup` of "1" on two histogram2d traces will make them their x-bins and y-bins match separately.

  • xbingroup
    Code: fig.update_traces(xbingroup=<VALUE>, selector=dict(type='histogram2dcontour'))
    Type: string
    Default: ""

    Set a group of histogram traces which will have compatible x-bin settings. Using `xbingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible x-bin settings. Note that the same `xbingroup` value can be used to set (1D) histogram `bingroup`

  • xbins
    Code: fig.update_traces(xbins=dict(...), selector=dict(type='histogram2dcontour'))
    Type: dict containing one or more of the keys listed below.
    • start
      Code: fig.update_traces(xbins_start=<VALUE>, selector=dict(type='histogram2dcontour'))
      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.

    • end
      Code: fig.update_traces(xbins_end=<VALUE>, selector=dict(type='histogram2dcontour'))
      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='histogram2dcontour'))
      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).

  • ybingroup
    Code: fig.update_traces(ybingroup=<VALUE>, selector=dict(type='histogram2dcontour'))
    Type: string
    Default: ""

    Set a group of histogram traces which will have compatible y-bin settings. Using `ybingroup`, histogram2d and histogram2dcontour traces (on axes of the same axis type) can have compatible y-bin settings. Note that the same `ybingroup` value can be used to set (1D) histogram `bingroup`

  • ybins
    Code: fig.update_traces(ybins=dict(...), selector=dict(type='histogram2dcontour'))
    Type: dict containing one or more of the keys listed below.
    • start
      Code: fig.update_traces(ybins_start=<VALUE>, selector=dict(type='histogram2dcontour'))
      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.

    • end
      Code: fig.update_traces(ybins_end=<VALUE>, selector=dict(type='histogram2dcontour'))
      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='histogram2dcontour'))
      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).

  • marker
    Code: fig.update_traces(marker=dict(...), selector=dict(type='histogram2dcontour'))
    Type: dict containing one or more of the keys listed below.
    • color
      Code: fig.update_traces(marker_color=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: list, numpy array, or Pandas series of numbers, strings, or datetimes.

      Sets the aggregation data.

  • line
    Code: fig.update_traces(line=dict(...), selector=dict(type='histogram2dcontour'))
    Type: dict containing one or more of the keys listed below.
    • color
      Code: fig.update_traces(line_color=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: color

      Sets the color of the contour level. Has no effect if `contours.coloring` is set to "lines".

    • width
      Code: fig.update_traces(line_width=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: number greater than or equal to 0
      Default: 0.5

      Sets the contour line width in (in px)

    • dash
      Code: fig.update_traces(line_dash=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: string
      Default: "solid"

      Sets the dash style of lines. Set to a dash type string ("solid", "dot", "dash", "longdash", "dashdot", or "longdashdot") or a dash length list in px (eg "5px,10px,2px,2px").

    • smoothing
      Code: fig.update_traces(line_smoothing=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: number between or equal to 0 and 1.3
      Default: 1

      Sets the amount of smoothing for the contour lines, where "0" corresponds to no smoothing.

  • colorbar
    Code: fig.update_traces(colorbar=dict(...), selector=dict(type='histogram2dcontour'))
    Type: dict containing one or more of the keys listed below.
    • thicknessmode
      Code: fig.update_traces(colorbar_thicknessmode=<VALUE>, selector=dict(type='histogram2dcontour'))
      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.

    • thickness
      Code: fig.update_traces(colorbar_thickness=<VALUE>, selector=dict(type='histogram2dcontour'))
      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.

    • lenmode
      Code: fig.update_traces(colorbar_lenmode=<VALUE>, selector=dict(type='histogram2dcontour'))
      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.

    • len
      Code: fig.update_traces(colorbar_len=<VALUE>, selector=dict(type='histogram2dcontour'))
      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.

    • x
      Code: fig.update_traces(colorbar_x=<VALUE>, selector=dict(type='histogram2dcontour'))
      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(colorbar_xanchor=<VALUE>, selector=dict(type='histogram2dcontour'))
      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(colorbar_xpad=<VALUE>, selector=dict(type='histogram2dcontour'))
      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(colorbar_y=<VALUE>, selector=dict(type='histogram2dcontour'))
      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(colorbar_yanchor=<VALUE>, selector=dict(type='histogram2dcontour'))
      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(colorbar_ypad=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: number greater than or equal to 0
      Default: 10

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

    • outlinecolor
      Code: fig.update_traces(colorbar_outlinecolor=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: color
      Default: "#444"

      Sets the axis line color.

    • outlinewidth
      Code: fig.update_traces(colorbar_outlinewidth=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: number greater than or equal to 0
      Default: 1

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

    • bordercolor
      Code: fig.update_traces(colorbar_bordercolor=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: color
      Default: "#444"

      Sets the axis line color.

    • borderwidth
      Code: fig.update_traces(colorbar_borderwidth=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: number greater than or equal to 0
      Default: 0

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

    • bgcolor
      Code: fig.update_traces(colorbar_bgcolor=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: color
      Default: "rgba(0,0,0,0)"

      Sets the color of padded area.

    • tickmode
      Code: fig.update_traces(colorbar_tickmode=<VALUE>, selector=dict(type='histogram2dcontour'))
      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).

    • nticks
      Code: fig.update_traces(colorbar_nticks=<VALUE>, selector=dict(type='histogram2dcontour'))
      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".

    • tick0
      Code: fig.update_traces(colorbar_tick0=<VALUE>, selector=dict(type='histogram2dcontour'))
      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.

    • dtick
      Code: fig.update_traces(colorbar_dtick=<VALUE>, selector=dict(type='histogram2dcontour'))
      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"

    • tickvals
      Code: fig.update_traces(colorbar_tickvals=<VALUE>, selector=dict(type='histogram2dcontour'))
      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`.

    • ticktext
      Code: fig.update_traces(colorbar_ticktext=<VALUE>, selector=dict(type='histogram2dcontour'))
      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`.

    • ticks
      Code: fig.update_traces(colorbar_ticks=<VALUE>, selector=dict(type='histogram2dcontour'))
      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.

    • ticklen
      Code: fig.update_traces(colorbar_ticklen=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: number greater than or equal to 0
      Default: 5

      Sets the tick length (in px).

    • tickwidth
      Code: fig.update_traces(colorbar_tickwidth=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: number greater than or equal to 0
      Default: 1

      Sets the tick width (in px).

    • tickcolor
      Code: fig.update_traces(colorbar_tickcolor=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: color
      Default: "#444"

      Sets the tick color.

    • showticklabels
      Code: fig.update_traces(colorbar_showticklabels=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: boolean
      Default: True

      Determines whether or not the tick labels are drawn.

    • tickfont
      Code: fig.update_traces(colorbar_tickfont=dict(...), selector=dict(type='histogram2dcontour'))
      Type: dict containing one or more of the keys listed below.

      Sets the color bar's tick label font

      • family
        Code: fig.update_traces(colorbar_tickfont_family=<VALUE>, selector=dict(type='histogram2dcontour'))
        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(colorbar_tickfont_size=<VALUE>, selector=dict(type='histogram2dcontour'))
        Type: number greater than or equal to 1
      • color
        Code: fig.update_traces(colorbar_tickfont_color=<VALUE>, selector=dict(type='histogram2dcontour'))
        Type: color
    • tickangle
      Code: fig.update_traces(colorbar_tickangle=<VALUE>, selector=dict(type='histogram2dcontour'))
      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.

    • tickformat
      Code: fig.update_traces(colorbar_tickformat=<VALUE>, selector=dict(type='histogram2dcontour'))
      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/d3-3.x-api-reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-time-format#locale_format We add one item to d3's date formatter: "%{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(colorbar_tickformatstops=list(...), selector=dict(type='histogram2dcontour'))
      Type: list of dict where each dict has one or more of the keys listed below.
      • enabled
        Parent: data[type=histogram2dcontour].colorbar.tickformatstops[]
        Type: boolean
        Default: True

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

      • dtickrange
        Parent: data[type=histogram2dcontour].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"

      • value
        Parent: data[type=histogram2dcontour].colorbar.tickformatstops[]
        Type: string
        Default: ""

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

      • name
        Parent: data[type=histogram2dcontour].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=histogram2dcontour].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`.

    • tickprefix
      Code: fig.update_traces(colorbar_tickprefix=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: string
      Default: ""

      Sets a tick label prefix.

    • showtickprefix
      Code: fig.update_traces(colorbar_showtickprefix=<VALUE>, selector=dict(type='histogram2dcontour'))
      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.

    • ticksuffix
      Code: fig.update_traces(colorbar_ticksuffix=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: string
      Default: ""

      Sets a tick label suffix.

    • showticksuffix
      Code: fig.update_traces(colorbar_showticksuffix=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: enumerated , one of ( "all" | "first" | "last" | "none" )
      Default: "all"

      Same as `showtickprefix` but for tick suffixes.

    • separatethousands
      Code: fig.update_traces(colorbar_separatethousands=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: boolean

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

    • exponentformat
      Code: fig.update_traces(colorbar_exponentformat=<VALUE>, selector=dict(type='histogram2dcontour'))
      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.

    • minexponent
      Code: fig.update_traces(colorbar_minexponent=<VALUE>, selector=dict(type='histogram2dcontour'))
      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".

    • showexponent
      Code: fig.update_traces(colorbar_showexponent=<VALUE>, selector=dict(type='histogram2dcontour'))
      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.

    • title
      Code: fig.update_traces(colorbar_title=dict(...), selector=dict(type='histogram2dcontour'))
      Type: dict containing one or more of the keys listed below.
      • text
        Code: fig.update_traces(colorbar_title_text=<VALUE>, selector=dict(type='histogram2dcontour'))
        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.

      • font
        Code: fig.update_traces(colorbar_title_font=dict(...), selector=dict(type='histogram2dcontour'))
        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.

        • family
          Code: fig.update_traces(colorbar_title_font_family=<VALUE>, selector=dict(type='histogram2dcontour'))
          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(colorbar_title_font_size=<VALUE>, selector=dict(type='histogram2dcontour'))
          Type: number greater than or equal to 1
        • color
          Code: fig.update_traces(colorbar_title_font_color=<VALUE>, selector=dict(type='histogram2dcontour'))
          Type: color
      • side
        Code: fig.update_traces(colorbar_title_side=<VALUE>, selector=dict(type='histogram2dcontour'))
        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.

  • autocolorscale
    Code: fig.update_traces(autocolorscale=<VALUE>, selector=dict(type='histogram2dcontour'))
    Type: boolean
    Default: True

    Determines whether the colorscale is a default palette (`autocolorscale: True`) or the palette determined by `colorscale`. 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.

  • colorscale
    Code: fig.update_traces(colorscale=<VALUE>, selector=dict(type='histogram2dcontour'))
    Type: colorscale

    Sets the colorscale. 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`zmin` and `zmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividis.

  • showscale
    Code: fig.update_traces(showscale=<VALUE>, selector=dict(type='histogram2dcontour'))
    Type: boolean
    Default: True

    Determines whether or not a colorbar is displayed for this trace.

  • reversescale
    Code: fig.update_traces(reversescale=<VALUE>, selector=dict(type='histogram2dcontour'))
    Type: boolean

    Reverses the color mapping if True. If True, `zmin` will correspond to the last color in the array and `zmax` will correspond to the first color.

  • zauto
    Code: fig.update_traces(zauto=<VALUE>, selector=dict(type='histogram2dcontour'))
    Type: boolean
    Default: True

    Determines whether or not the color domain is computed with respect to the input data (here in `z`) or the bounds set in `zmin` and `zmax` Defaults to `False` when `zmin` and `zmax` are set by the user.

  • zhoverformat
    Code: fig.update_traces(zhoverformat=<VALUE>, selector=dict(type='histogram2dcontour'))
    Type: string
    Default: ""

    Sets the hover text formatting rule using d3 formatting mini-languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api-reference/blob/master/Formatting.md#d3_format

  • zmax
    Code: fig.update_traces(zmax=<VALUE>, selector=dict(type='histogram2dcontour'))
    Type: number

    Sets the upper bound of the color domain. Value should have the same units as in `z` and if set, `zmin` must be set as well.

  • zmid
    Code: fig.update_traces(zmid=<VALUE>, selector=dict(type='histogram2dcontour'))
    Type: number

    Sets the mid-point of the color domain by scaling `zmin` and/or `zmax` to be equidistant to this point. Value should have the same units as in `z`. Has no effect when `zauto` is `False`.

  • zmin
    Code: fig.update_traces(zmin=<VALUE>, selector=dict(type='histogram2dcontour'))
    Type: number

    Sets the lower bound of the color domain. Value should have the same units as in `z` and if set, `zmax` must be set as well.

  • autocontour
    Code: fig.update_traces(autocontour=<VALUE>, selector=dict(type='histogram2dcontour'))
    Type: boolean
    Default: True

    Determines whether or not the contour level attributes are picked by an algorithm. If "True", the number of contour levels can be set in `ncontours`. If "False", set the contour level attributes in `contours`.

  • contours
    Code: fig.update_traces(contours=dict(...), selector=dict(type='histogram2dcontour'))
    Type: dict containing one or more of the keys listed below.
    • type
      Code: fig.update_traces(contours_type=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: enumerated , one of ( "levels" | "constraint" )
      Default: "levels"

      If `levels`, the data is represented as a contour plot with multiple levels displayed. If `constraint`, the data is represented as constraints with the invalid region shaded as specified by the `operation` and `value` parameters.

    • start
      Code: fig.update_traces(contours_start=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: number

      Sets the starting contour level value. Must be less than `contours.end`

    • end
      Code: fig.update_traces(contours_end=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: number

      Sets the end contour level value. Must be more than `contours.start`

    • size
      Code: fig.update_traces(contours_size=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: number greater than or equal to 0

      Sets the step between each contour level. Must be positive.

    • coloring
      Code: fig.update_traces(contours_coloring=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: enumerated , one of ( "fill" | "heatmap" | "lines" | "none" )
      Default: "fill"

      Determines the coloring method showing the contour values. If "fill", coloring is done evenly between each contour level If "heatmap", a heatmap gradient coloring is applied between each contour level. If "lines", coloring is done on the contour lines. If "none", no coloring is applied on this trace.

    • showlines
      Code: fig.update_traces(contours_showlines=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: boolean
      Default: True

      Determines whether or not the contour lines are drawn. Has an effect only if `contours.coloring` is set to "fill".

    • showlabels
      Code: fig.update_traces(contours_showlabels=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: boolean

      Determines whether to label the contour lines with their values.

    • labelfont
      Code: fig.update_traces(contours_labelfont=dict(...), selector=dict(type='histogram2dcontour'))
      Type: dict containing one or more of the keys listed below.

      Sets the font used for labeling the contour levels. The default color comes from the lines, if shown. The default family and size come from `layout.font`.

      • family
        Code: fig.update_traces(contours_labelfont_family=<VALUE>, selector=dict(type='histogram2dcontour'))
        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(contours_labelfont_size=<VALUE>, selector=dict(type='histogram2dcontour'))
        Type: number greater than or equal to 1
      • color
        Code: fig.update_traces(contours_labelfont_color=<VALUE>, selector=dict(type='histogram2dcontour'))
        Type: color
    • labelformat
      Code: fig.update_traces(contours_labelformat=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: string
      Default: ""

      Sets the contour label formatting rule using d3 formatting mini-language which is very similar to Python, see: https://github.com/d3/d3-3.x-api-reference/blob/master/Formatting.md#d3_format

    • operation
      Code: fig.update_traces(contours_operation=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: enumerated , one of ( "=" | "<" | ">=" | ">" | "<=" | "[]" | "()" | "[)" | "(]" | "][" | ")(" | "](" | ")[" )
      Default: "="

      Sets the constraint operation. "=" keeps regions equal to `value` "<" and "<=" keep regions less than `value` ">" and ">=" keep regions greater than `value` "[]", "()", "[)", and "(]" keep regions inside `value[0]` to `value[1]` "][", ")(", "](", ")[" keep regions outside `value[0]` to value[1]` Open vs. closed intervals make no difference to constraint display, but all versions are allowed for consistency with filter transforms.

    • value
      Code: fig.update_traces(contours_value=<VALUE>, selector=dict(type='histogram2dcontour'))
      Type: number or categorical coordinate string
      Default: 0

      Sets the value or values of the constraint boundary. When `operation` is set to one of the comparison values (=,<,>=,>,<=) "value" is expected to be a number. When `operation` is set to one of the interval values ([],(),[),(],][,)(,](,)[) "value" is expected to be an array of two numbers where the first is the lower bound and the second is the upper bound.

  • hoverlabel
    Code: fig.update_traces(hoverlabel=dict(...), selector=dict(type='histogram2dcontour'))
    Type: dict containing one or more of the keys listed below.
    • bgcolor
      Code: fig.update_traces(hoverlabel_bgcolor=<VALUE>, selector=dict(type='histogram2dcontour'))
      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='histogram2dcontour'))
      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='histogram2dcontour'))
      Type: dict containing one or more of the keys listed below.

      Sets the font used in hover labels.

      • family
        Code: fig.update_traces(hoverlabel_font_family=<VALUE>, selector=dict(type='histogram2dcontour'))
        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='histogram2dcontour'))
        Type: number or array of numbers greater than or equal to 1
      • color
        Code: fig.update_traces(hoverlabel_font_color=<VALUE>, selector=dict(type='histogram2dcontour'))
        Type: color or array of colors
    • align
      Code: fig.update_traces(hoverlabel_align=<VALUE>, selector=dict(type='histogram2dcontour'))
      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

    • namelength
      Code: fig.update_traces(hoverlabel_namelength=<VALUE>, selector=dict(type='histogram2dcontour'))
      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.

  • ncontours
    Code: fig.update_traces(ncontours=<VALUE>, selector=dict(type='histogram2dcontour'))
    Type: integer greater than or equal to 1
    Default: 15

    Sets the maximum number of contour levels. The actual number of contours will be chosen automatically to be less than or equal to the value of `ncontours`. Has an effect only if `autocontour` is "True" or if `contours.size` is missing.

  • xcalendar
    Code: fig.update_traces(xcalendar=<VALUE>, selector=dict(type='histogram2dcontour'))
    Type: enumerated , one of ( "gregorian" | "chinese" | "coptic" | "discworld" | "ethiopian" | "hebrew" | "islamic" | "julian" | "mayan" | "nanakshahi" | "nepali" | "persian" | "jalali" | "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='histogram2dcontour'))
    Type: enumerated , one of ( "gregorian" | "chinese" | "coptic" | "discworld" | "ethiopian" | "hebrew" | "islamic" | "julian" | "mayan" | "nanakshahi" | "nepali" | "persian" | "jalali" | "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='histogram2dcontour'))
    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.