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This example shows how to use [bingroup](https://plotly.com/python/reference/#histogram-bingroup) attribute to have a compatible bin settings for both histograms. To define `start`, `end` and `size` value of x-axis and y-axis seperatly, set [ybins](https://plotly.com/python/reference/#histogram2dcontour-ybins) and `xbins`.
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This example shows how to use [bingroup](https://plotly.com/python/reference/histogram/#histogram-bingroup) attribute to have a compatible bin settings for both histograms. To define `start`, `end` and `size` value of x-axis and y-axis seperatly, set [ybins](https://plotly.com/python/reference/histogram2dcontour/#histogram2dcontour-ybins) and `xbins`.
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```python
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import plotly.graph_objects as go
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```
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#### Reference
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See https://plotly.com/python/reference/#histogram2d for more information and chart attribute options!
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See https://plotly.com/python/reference/histogram2d/ for more information and chart attribute options!
sizeref=750, # info on sizeref: https://plotly.com/python/reference/#scatter-marker-sizeref
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sizeref=750, # info on sizeref: https://plotly.com/python/reference/scatter/#scatter-marker-sizeref
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size= planet_diameter,
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color= planet_colors,
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)
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mode='markers',
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marker=dict(
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sizemode='diameter',
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sizeref=750, # info on sizeref: https://plotly.com/python/reference/#scatter-marker-sizeref
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sizeref=750, # info on sizeref: https://plotly.com/python/reference/scatter/#scatter-marker-sizeref
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size= planet_diameter,
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color= temperatures,
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colorbar_title='Mean<br>Temperature',
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#### Reference
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See https://plotly.com/python/reference/#scatter3d and https://plotly.com/python/reference/#scatter-marker-sizeref <br>for more information and chart attribute options!
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See https://plotly.com/python/reference/scatter3d/ and https://plotly.com/python/reference/scatter/#scatter-marker-sizeref <br>for more information and chart attribute options!
Copy file name to clipboardExpand all lines: doc/python/3d-surface-plots.md
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#### Surface Plot With Contours
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Display and customize contour data for each axis using the `contours` attribute ([reference](plotly.com/python/reference/#surface-contours)).
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Display and customize contour data for each axis using the `contours` attribute ([reference](plotly.com/python/reference/surface/#surface-contours)).
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```python
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import plotly.graph_objects as go
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fig.show()
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```
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#### Configure Surface Contour Levels
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This example shows how to slice the surface graph on the desired position for each of x, y and z axis. [contours.x.start](https://plotly.com/python/reference/#surface-contours-x-start) sets the starting contour level value, `end` sets the end of it, and `size` sets the step between each contour level.
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This example shows how to slice the surface graph on the desired position for each of x, y and z axis. [contours.x.start](https://plotly.com/python/reference/surface/#surface-contours-x-start) sets the starting contour level value, `end` sets the end of it, and `size` sets the step between each contour level.
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```python
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import plotly.graph_objects as go
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#### Reference
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See https://plotly.com/python/reference/#surface for more information!
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See https://plotly.com/python/reference/surface/ for more information!
Copy file name to clipboardExpand all lines: doc/python/animations.md
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#### Adding Control Buttons to Animations
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You can add play and pause buttons to control your animated charts by adding an `updatemenus` array to the `layout` of your `figure`. More information on style and placement of the buttons is available in Plotly's [`updatemenus` reference](https://plotly.com/python/reference/#layout-updatemenus).
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You can add play and pause buttons to control your animated charts by adding an `updatemenus` array to the `layout` of your `figure`. More information on style and placement of the buttons is available in Plotly's [`updatemenus` reference](https://plotly.com/python/reference/layout/updatemenus/).
Copy file name to clipboardExpand all lines: doc/python/annotated-heatmap.md
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#### Reference
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For more info on Plotly heatmaps, see: https://plotly.com/python/reference/#heatmap.<br> For more info on using colorscales with Plotly see: https://plotly.com/python/heatmap-and-contour-colorscales/ <br>For more info on `ff.create_annotated_heatmap()`, see the [full function reference](https://plotly.com/python-api-reference/generated/plotly.figure_factory.create_annotated_heatmap.html#plotly.figure_factory.create_annotated_heatmap)
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For more info on Plotly heatmaps, see: https://plotly.com/python/reference/heatmap/.<br> For more info on using colorscales with Plotly see: https://plotly.com/python/heatmap-and-contour-colorscales/ <br>For more info on `ff.create_annotated_heatmap()`, see the [full function reference](https://plotly.com/python-api-reference/generated/plotly.figure_factory.create_annotated_heatmap.html#plotly.figure_factory.create_annotated_heatmap)
Copy file name to clipboardExpand all lines: doc/python/axes.md
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thumbnail: thumbnail/axes.png
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---
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This tutorial explain how to set the properties of 2-dimensional Cartesian axes, namely [`go.layout.XAxis`](/python/reference/#layout-xaxis) and [`go.layout.YAxis`](python/reference/#layout-xaxis). Other kinds of axes are described in other tutorials:
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This tutorial explain how to set the properties of 2-dimensional Cartesian axes, namely [`go.layout.XAxis`](/python/reference/layout/xaxis/) and [`go.layout.YAxis`](python/reference/layout/xaxis/). Other kinds of axes are described in other tutorials:
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-[3D axes](/python/3d-axes) The axis object is [`go.layout.Scene`](/python/reference/#layout-scene)
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-[Polar axes](/python/polar-chart/). The axis object is [`go.layout.Polar`](/python/reference/#layout-polar)
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-[Ternary axes](/python/ternary-plots). The axis object is [`go.layout.Ternary`](/python/reference/#layout-ternary)
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-[Geo axes](/python/map-configuration/). The axis object is [`go.layout.Geo`](/python/reference/#layout-geo)
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-[Mapbox axes](/python/mapbox-layers/). The axis object is [`go.layout.Mapbox`](/python/reference/#layout-mapbox)
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-[Color axes](/python/colorscales/). The axis object is [`go.layout.Coloraxis`](/python/reference/#layout-coloraxis).
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-[3D axes](/python/3d-axes) The axis object is [`go.layout.Scene`](/python/reference/layout/scene/)
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-[Polar axes](/python/polar-chart/). The axis object is [`go.layout.Polar`](/python/reference/layout/polar/)
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-[Ternary axes](/python/ternary-plots). The axis object is [`go.layout.Ternary`](/python/reference/layout/ternary/)
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-[Geo axes](/python/map-configuration/). The axis object is [`go.layout.Geo`](/python/reference/layout/geo/)
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-[Mapbox axes](/python/mapbox-layers/). The axis object is [`go.layout.Mapbox`](/python/reference/layout/mapbox/)
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-[Color axes](/python/colorscales/). The axis object is [`go.layout.Coloraxis`](/python/reference/layout/coloraxis/).
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**See also** the tutorials on [subplots](/python/subplots) and [multiple axes](/python/multiple-axes/).
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#### Reference
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See https://plotly.com/python/reference/#layout-xaxis and https://plotly.com/python/reference/#layout-yaxis for more information and chart attribute options!
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See https://plotly.com/python/reference/layout/xaxis/ and https://plotly.com/python/reference/layout/yaxis/ for more information and chart attribute options!
Copy file name to clipboardExpand all lines: doc/python/bar-charts.md
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### Bar Chart with Sorted or Ordered Categories
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Set `categoryorder` to `"category ascending"` or `"category descending"` for the alphanumerical order of the category names or `"total ascending"` or `"total descending"` for numerical order of values. [categoryorder](https://plotly.com/python/reference/#layout-xaxis-categoryorder) for more information. Note that sorting the bars by a particular trace isn't possible right now - it's only possible to sort by the total values. Of course, you can always sort your data _before_ plotting it if you need more customization.
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Set `categoryorder` to `"category ascending"` or `"category descending"` for the alphanumerical order of the category names or `"total ascending"` or `"total descending"` for numerical order of values. [categoryorder](https://plotly.com/python/reference/layout/xaxis/#layout-xaxis-categoryorder) for more information. Note that sorting the bars by a particular trace isn't possible right now - it's only possible to sort by the total values. Of course, you can always sort your data _before_ plotting it if you need more customization.
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This example orders the bar chart alphabetically with `categoryorder: 'category ascending'`
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### Reference
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See https://plotly.com/python/reference/#bar for more information and chart attribute options!
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See https://plotly.com/python/reference/bar/ for more information and chart attribute options!
Copy file name to clipboardExpand all lines: doc/python/box-plots.md
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## Box plot with go.Box
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If Plotly Express does not provide a good starting point, it is also possible to use [the more generic `go.Box` class from `plotly.graph_objects`](/python/graph-objects/). All available options for `go.Box` are described in the reference page https://plotly.com/python/reference/#box.
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If Plotly Express does not provide a good starting point, it is also possible to use [the more generic `go.Box` class from `plotly.graph_objects`](/python/graph-objects/). All available options for `go.Box` are described in the reference page https://plotly.com/python/reference/box/.
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### Basic Box Plot
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#### Reference
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See https://plotly.com/python/reference/#box for more information and chart attribute options!
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See https://plotly.com/python/reference/box/ for more information and chart attribute options!
Copy file name to clipboardExpand all lines: doc/python/bubble-charts.md
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To scale the bubble size, use the attribute `sizeref`. We recommend using the following formula to calculate a `sizeref` value:<br>
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`sizeref = 2. * max(array of size values) / (desired maximum marker size ** 2)`<br>
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Note that setting 'sizeref' to a value greater than 1, decreases the rendered marker sizes, while setting 'sizeref' to less than 1, increases the rendered marker sizes. See https://plotly.com/python/reference/#scatter-marker-sizeref for more information.
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Additionally, we recommend setting the sizemode attribute: https://plotly.com/python/reference/#scatter-marker-sizemode to area.
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Note that setting 'sizeref' to a value greater than 1, decreases the rendered marker sizes, while setting 'sizeref' to less than 1, increases the rendered marker sizes. See https://plotly.com/python/reference/scatter/#scatter-marker-sizeref for more information.
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Additionally, we recommend setting the sizemode attribute: https://plotly.com/python/reference/scatter/#scatter-marker-sizemode to area.
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```python
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### Reference
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See https://plotly.com/python/reference/#scatter for more information and chart attribute options!
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See https://plotly.com/python/reference/scatter/ for more information and chart attribute options!
Copy file name to clipboardExpand all lines: doc/python/bubble-maps.md
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Note that setting `sizeref` to a value greater than $1$, decreases the rendered marker sizes, while setting `sizeref` to less than $1$, increases the rendered marker sizes.
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See https://plotly.com/python/reference/#scatter-marker-sizeref for more information. Additionally, we recommend setting the sizemode attribute: https://plotly.com/python/reference/#scatter-marker-sizemode to area.
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See https://plotly.com/python/reference/scatter/#scatter-marker-sizeref for more information. Additionally, we recommend setting the sizemode attribute: https://plotly.com/python/reference/scatter/#scatter-marker-sizemode to area.
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```python
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#### Reference
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See https://plotly.com/python/reference/#choropleth and https://plotly.com/python/reference/#scattergeo for more information and chart attribute options!
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See https://plotly.com/python/reference/choropleth/ and https://plotly.com/python/reference/scattergeo/ for more information and chart attribute options!
Copy file name to clipboardExpand all lines: doc/python/bullet-charts.md
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```
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#### Custom Bullet
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The following example shows how to customize your charts. For more information about all possible options check our [reference page](https://plotly.com/python/reference/#indicator).
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The following example shows how to customize your charts. For more information about all possible options check our [reference page](https://plotly.com/python/reference/indicator/).
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```python
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import plotly.graph_objects as go
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```
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#### Reference
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See https://plotly.com/python/reference/#indicator for more information and chart attribute options!
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See https://plotly.com/python/reference/indicator/ for more information and chart attribute options!
Copy file name to clipboardExpand all lines: doc/python/carpet-contour.md
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### Basic Carpet Plot
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Set the `x` and `y` coorindates, using `x` and `y` attributes. If `x` coorindate values are ommitted a cheater plot will be created. To save parameter values use `a` and `b` attributes. To make changes to the axes, use `aaxis` or `baxis` attributes. For a more detailed list of axes attributes refer to [python reference](https://plotly.com/python/reference/#carpet-aaxis).
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Set the `x` and `y` coorindates, using `x` and `y` attributes. If `x` coorindate values are ommitted a cheater plot will be created. To save parameter values use `a` and `b` attributes. To make changes to the axes, use `aaxis` or `baxis` attributes. For a more detailed list of axes attributes refer to [python reference](https://plotly.com/python/reference/carpet/#carpet-aaxis).
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```python
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### Reference
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See https://plotly.com/python/reference/#contourcarpet for more information and chart attribute options!
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See https://plotly.com/python/reference/contourcarpet/ for more information and chart attribute options!
Copy file name to clipboardExpand all lines: doc/python/carpet-plot.md
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### Add A and B axis
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Use `aaxis` or `baxis` list to make changes to the axes. For a more detailed list of attributes refer to [R reference](https://plotly.com/r/reference/#carpet-aaxis).
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Use `aaxis` or `baxis` list to make changes to the axes. For a more detailed list of attributes refer to [R reference](https://plotly.com/r/reference/carpet/#carpet-aaxis).
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```python inputHidden=false outputHidden=false
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### Reference
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See https://plotly.com/python/reference/#carpet for more information and chart attribute options!
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See https://plotly.com/python/reference/carpet/ for more information and chart attribute options!
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