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Diff for: 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](/python/figure-structure/#2d-cartesian-trace-types-and-subplots), namely [`go.layout.XAxis`](/python/reference/layout/xaxis/) and [`go.layout.YAxis`](python/reference/layout/xaxis/).
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This tutorial explain how to set the properties of [2-dimensional Cartesian axes](/python/figure-structure/#2d-cartesian-trace-types-and-subplots), namely [`go.layout.XAxis`](/python/reference/layout/xaxis/) and [`go.layout.YAxis`](/python/reference/layout/xaxis/).
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Other kinds of subplots and axes are described in other tutorials:
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fig.show()
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```
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#### Specifying Label Aliases
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#### Specifying Label Aliases
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*New in 5.14*
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To plot on Mapbox maps with Plotly you _may_ need a Mapbox account and a public [Mapbox Access Token](https://www.mapbox.com/studio). See our [Mapbox Map Layers](/python/mapbox-layers/) documentation for more information.
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To draw a line on your map, you either can use [`px.line_mapbox()`](https://www.plotly.express/plotly_express/#plotly_express.line_mapbox) in Plotly Express, or [`Scattermapbox`](https://plotly.com/python/reference/scattermapbox/) traces. Below we show you how to draw a line on Mapbox using Plotly Express.
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To draw a line on your map, you either can use [`px.line_mapbox()`](https://plotly.com/python-api-reference/generated/plotly.express.line_mapbox.html) in Plotly Express, or [`Scattermapbox`](https://plotly.com/python/reference/scattermapbox/) traces. Below we show you how to draw a line on Mapbox using Plotly Express.
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### Lines on Mapbox maps using Plotly Express
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#### Reference
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See [function reference for `px.(line_mapbox)`](https://plotly.com/python-api-reference/generated/plotly.express.line_mapbox) or
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See [function reference for `px.(line_mapbox)`](https://plotly.com/python-api-reference/generated/plotly.express.line_mapbox) or
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https://plotly.com/python/reference/scattermapbox/ for more information about mapbox and their attribute options.

Diff for: doc/python/marker-style.md

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The `marker_symbol` attribute allows you to choose from a wide array of symbols to represent markers in your figures.
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The basic symbols are: `circle`, `square`, `diamond`, `cross`, `x`, `triangle`, `pentagon`, `hexagram`, `star`, `diamond`, `hourglass`, `bowtie`, `asterisk`, `hash`, `y`, and `line`.
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The basic symbols are: `circle`, `square`, `diamond`, `cross`, `x`, `triangle`, `pentagon`, `hexagram`, `star`, `hourglass`, `bowtie`, `asterisk`, `hash`, `y`, and `line`.
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Each basic symbol is also represented by a number. Adding 100 to that number is equivalent to appending the suffix "-open" to a symbol name. Adding 200 is equivalent to appending "-dot" to a symbol name. Adding 300 is equivalent to appending "-open-dot" or "dot-open" to a symbol name.
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Diff for: doc/python/parallel-categories-diagram.md

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This example visualizes the restaurant bills of a sample of 244 people. Hovering over a category rectangle (sex, smoker, etc) displays a tooltip with the number of people with that single trait. Hovering over a ribbon in the diagram displays a tooltip with the number of people with a particular combination of the five traits connected by the ribbon.
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By default, `px.parallel_categories` will display any column in the `data_frame` that has a cardinality (or number of unique values) of less than 50. This can be overridden either by passing in a specific list of columns to `dimensions` or by setting `dimensions_max_cardinality` to something other than 50.
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By default, `px.parallel_categories` will display any column in the `data_frame` that has a cardinality (or number of unique values) of less than 50. This can be overridden either by passing in a specific list of columns to `dimensions` or by setting `dimensions_max_cardinality` to something other than 50.
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```python
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#### Style Diagram
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In this example `dimensions` represents a list of stings or the columns of data frame, and `labels` is a dictionary with string keys (column name) and string values ('desired label to be displayed'). See [Plotly express reference page](https://www.plotly.express/plotly_express/#plotly_express.parallel_categories) for more information.
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In this example `dimensions` represents a list of stings or the columns of data frame, and `labels` is a dictionary with string keys (column name) and string values ('desired label to be displayed'). See [Plotly express reference page](https://plotly.com/python-api-reference/generated/plotly.express.parallel_categories) for more information.
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```python
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import plotly.express as px

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