fix internal reference links

Author: nicolaskruchten

doc/python/creating-and-updating-figures.md

@@ -68,7 +68,7 @@ The [`plotly.graph_objects` module provides an automatically-generated hierarchy
 Graph objects have several benefits compared to plain Python dictionaries.
 
 1. Graph objects provide precise data validation. If you provide an invalid property name or an invalid property value as the key to a graph object, an exception will be raised with a helpful error message describing the problem. This is not the case if you use plain Python dictionaries and lists to build your figures.
-2. Graph objects contain descriptions of each valid property as Python docstrings, with a [full API reference available](https://plotly.com/python-api-reference/). You can use these docstrings in the development environment of your choice to learn about the available properties as an alternative to consulting the online [Full Reference](/python/reference/).
+2. Graph objects contain descriptions of each valid property as Python docstrings, with a [full API reference available](https://plotly.com/python-api-reference/). You can use these docstrings in the development environment of your choice to learn about the available properties as an alternative to consulting the online [Full Reference](/python/reference/index/).
 3. Properties of graph objects can be accessed using both dictionary-style key lookup (e.g. `fig["layout"]`) or class-style property access (e.g. `fig.layout`).
 4. Graph objects support higher-level convenience functions for making updates to already constructed figures (`.update_layout()`, `.add_trace()` etc) as described below.
 5. Graph object constructors and update methods accept "magic underscores" (e.g. `go.Figure(layout_title_text="The Title")` rather than `dict(layout=dict(title=dict(text="The Title")))`) for more compact code, as described below.
@@ -652,4 +652,4 @@ fig.data[0].marker.line.width = 4
 fig.data[0].marker.line.color = "black"
 
 fig.show()
-```
+```

doc/python/figure-structure.md

@@ -51,13 +51,13 @@ fig.show()
 
 ### Figures as Trees of Attributes
 
-Plotly.js supports inputs adhering to a well-defined schema, whose overall architecture is explained in this page and which is exhaustively documented in the [Figure Reference](/python/reference/) (which is itself generated from a [machine-readable JSON representation of the schema](https://raw.githubusercontent.com/plotly/plotly.js/master/dist/plot-schema.json)). Figures are represented as trees with named nodes called "attributes". The root node of the tree has three top-level attributes: `data`, `layout` and `frames` (see below).
+Plotly.js supports inputs adhering to a well-defined schema, whose overall architecture is explained in this page and which is exhaustively documented in the [Figure Reference](/python/reference/index/) (which is itself generated from a [machine-readable JSON representation of the schema](https://raw.githubusercontent.com/plotly/plotly.js/master/dist/plot-schema.json)). Figures are represented as trees with named nodes called "attributes". The root node of the tree has three top-level attributes: `data`, `layout` and `frames` (see below).
 
-Attributes are referred to in text and in the [Figure Reference](/python/reference/) by their full "path" i.e. the dot-delimited concatenation of their parents. For example `"layout.width"` refers to the attribute whose key is `"width"` inside a dict which is the value associated with a key `"layout"` at the root of the figure. If one of the parents is a list rather than a dict, a set of brackets is inserted in the path when referring to the attribute in the abstract, e.g. `"layout.annotations[].text"`. Finally, as explained below, the top-level "data" attribute defines a list of typed objects called "traces" with the schema dependent upon the type, and these attributes' paths are listed in the [Figure Reference](/python/reference/) as `"data[type=scatter].name"`.
+Attributes are referred to in text and in the [Figure Reference](/python/reference/index/) by their full "path" i.e. the dot-delimited concatenation of their parents. For example `"layout.width"` refers to the attribute whose key is `"width"` inside a dict which is the value associated with a key `"layout"` at the root of the figure. If one of the parents is a list rather than a dict, a set of brackets is inserted in the path when referring to the attribute in the abstract, e.g. `"layout.annotations[].text"`. Finally, as explained below, the top-level "data" attribute defines a list of typed objects called "traces" with the schema dependent upon the type, and these attributes' paths are listed in the [Figure Reference](/python/reference/index/) as `"data[type=scatter].name"`.
 
 The [`plotly.graph_objects` module contains an automatically-generated hierarchy of  Python classes](/python/graph-objects/) which represent non-leaf attributes in the figure schema and provide a Pythonic API for them. When [manipulating a `plotly.graph_objects.Figure` object](/python/creating-and-updating-figures/), attributes can be set either directly using Python object attributes e.g. `fig.layout.title.font.family="Open Sans"` or using [update methods and "magic underscores"](/python/creating-and-updating-figures/#magic-underscore-notation) e.g. `fig.update_layout(title_font_family="Open Sans")`
 
-When building a figure, it is *not necessary to populate every attribute* of every object. At render-time, the JavaScript layer will compute default values for each required unspecified attribute, depending upon the ones that are specified, as documented in the [Figure Reference](/python/reference/). An example of this would be `layout.xaxis.range`, which may be specified explicitly, but if not will be computed based on the range of `x` values for every trace linked to that axis. The JavaScript layer will ignore unknown attributes or malformed values, although the `plotly.graph_objects` module provides Python-side validation for attribute values. Note also that if [the `layout.template` key is present (as it is by default)](/python/templates/) then default values will be drawn first from the contents of the template and only if missing from there will the JavaScript layer infer further defaults. The built-in template can be disabled by setting `layout.template="none"`.
+When building a figure, it is *not necessary to populate every attribute* of every object. At render-time, the JavaScript layer will compute default values for each required unspecified attribute, depending upon the ones that are specified, as documented in the [Figure Reference](/python/reference/index/). An example of this would be `layout.xaxis.range`, which may be specified explicitly, but if not will be computed based on the range of `x` values for every trace linked to that axis. The JavaScript layer will ignore unknown attributes or malformed values, although the `plotly.graph_objects` module provides Python-side validation for attribute values. Note also that if [the `layout.template` key is present (as it is by default)](/python/templates/) then default values will be drawn first from the contents of the template and only if missing from there will the JavaScript layer infer further defaults. The built-in template can be disabled by setting `layout.template="none"`.
 
 ### The Top-Level `data` Attribute
 

doc/python/graph-objects.md

@@ -50,7 +50,7 @@ The objects contained in the list which is the [value of the attribute `data` ar
 Graph objects have several benefits compared to plain Python dictionaries:
 
 1. Graph objects provide precise data validation. If you provide an invalid property name or an invalid property value as the key to a graph object, an exception will be raised with a helpful error message describing the problem. This is not the case if you use plain Python dictionaries and lists to build your figures.
-2. Graph objects contain descriptions of each valid property as Python docstrings, with a [full API reference available](https://plotly.com/python-api-reference/). You can use these docstrings in the development environment of your choice to learn about the available properties as an alternative to consulting the online [Full Reference](/python/reference/).
+2. Graph objects contain descriptions of each valid property as Python docstrings, with a [full API reference available](https://plotly.com/python-api-reference/). You can use these docstrings in the development environment of your choice to learn about the available properties as an alternative to consulting the online [Full Reference](/python/reference/index/).
 3. Properties of graph objects can be accessed using both dictionary-style key lookup (e.g. `fig["layout"]`) or class-style property access (e.g. `fig.layout`).
 4. Graph objects support higher-level convenience functions for making updates to already constructed figures (`.update_layout()`, `.add_trace()` etc).
 5. Graph object constructors and update methods accept "magic underscores" (e.g. `go.Figure(layout_title_text="The Title")` rather than `dict(layout=dict(title=dict(text="The Title")))`) for more compact code.
@@ -88,4 +88,4 @@ fig.update_layout(legend_title_text = "Contestant")
 fig.update_xaxes(title_text="Fruit")
 fig.update_yaxes(title_text="Number Eaten")
 fig.show()
-```
+```