link up graph objects page

Author: nicolaskruchten

doc/python/3d-scatter-plots.md

@@ -76,7 +76,7 @@ fig.update_layout(margin=dict(l=0, r=0, b=0, t=0))
 
 #### Basic 3D Scatter Plot
 
-If Plotly Express does not provide a good starting point, it is also possible to use the more generic `go.Scatter3D` from `plotly.graph_objs`.
+If Plotly Express does not provide a good starting point, it is also possible to use [the more generic `go.Scatter3D` class from `plotly.graph_objects`](/python/graph-objects/).
 Like the [2D scatter plot](https://plotly.com/python/line-and-scatter/) `go.Scatter`, `go.Scatter3d` plots individual data in three-dimensional space.
 
 ```python
@@ -122,4 +122,4 @@ fig.show()
 
 #### Reference
 
-See https://plotly.com/python/reference/#scatter3d for more information and chart attribute options!
+See https://plotly.com/python/reference/#scatter3d for more information and chart attribute options!

doc/python/bar-charts.md

@@ -99,7 +99,7 @@ To learn more, see the _link to px.bar reference page_.
 
 #### Basic Bar Chart with plotly.graph_objects
 
-If Plotly Express does not provide a good starting point, it is also possible to use the more generic `go.Bar` function from `plotly.graph_objects`.
+If Plotly Express does not provide a good starting point, it is also possible to use [the more generic `go.Bar` class from `plotly.graph_objects`](/python/graph-objects/).
 
 ```python
 import plotly.graph_objects as go
@@ -386,4 +386,4 @@ See examples of horizontal bar charts [here](https://plotly.com/python/horizonta
 
 ### Reference
 
-See https://plotly.com/python/reference/#bar for more information and chart attribute options!
+See https://plotly.com/python/reference/#bar for more information and chart attribute options!

doc/python/box-plots.md

@@ -134,7 +134,7 @@ fig.show()
 
 ## Box plot with go.Box
 
-If Plotly Express does not provide a good starting point, it is also possible to use the more generic `go.Box` function from `plotly.graph_objects`. All available options for `go.Box` are described in the reference page https://plotly.com/python/reference/#box.
+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.
 
 ### Basic Box Plot
 
@@ -491,4 +491,4 @@ fig.show()
 
 #### Reference
 
-See https://plotly.com/python/reference/#box for more information and chart attribute options!
+See https://plotly.com/python/reference/#box for more information and chart attribute options!

doc/python/bubble-charts.md

@@ -52,7 +52,7 @@ fig.show()
 
 ## Bubble Chart with plotly.graph_objects
 
-If Plotly Express does not provide a good starting point, it is also possible to use the more generic `go.Scatter` from `plotly.graph_objects`, and define the size of markers to create a bubble chart. All of the available options are described in the scatter section of the reference page: https://plotly.com/python/reference#scatter.
+If Plotly Express does not provide a good starting point, it is also possible to use [the more generic `go.Scatter` class from `plotly.graph_objects`](/python/graph-objects/), and define the size of markers to create a bubble chart. All of the available options are described in the scatter section of the reference page: https://plotly.com/python/reference#scatter.
 
 ### Simple Bubble Chart
 
@@ -222,4 +222,4 @@ fig.show()
 
 ### Reference
 
-See https://plotly.com/python/reference/#scatter for more information and chart attribute options!
+See https://plotly.com/python/reference/#scatter for more information and chart attribute options!

doc/python/funnel-charts.md

@@ -60,7 +60,7 @@ fig.show()
 
 ### Basic Funnel Chart with graph_objects trace go.Funnel
 
-If Plotly Express does not provide a good starting point, it is also possible to use the more generic `go.Funnel` function from `plotly.graph_objects`.
+If Plotly Express does not provide a good starting point, it is also possible to use [the more generic `go.Funnel` class from `plotly.graph_objects`](/python/graph-objects/).
 
 ```python
 from plotly import graph_objects as go
@@ -138,7 +138,7 @@ fig.show()
 
 ### Basic Area Funnel Plot with go.Funnelarea
 
-If Plotly Express does not provide a good starting point, it is also possible to use the more generic `go.Funnelarea` function from `plotly.graph_objects`.
+If Plotly Express does not provide a good starting point, it is also possible to use [the more generic `go.Funnelarea` class from `plotly.graph_objects`](/python/graph-objects/).
 
 ```python
 from plotly import graph_objects as go
@@ -202,4 +202,4 @@ fig.show()
 
 #### Reference
 
-See https://plotly.com/python/reference/#funnel and https://plotly.com/python/reference/#funnelarea for more information and chart attribute options!
+See https://plotly.com/python/reference/#funnel and https://plotly.com/python/reference/#funnelarea for more information and chart attribute options!

doc/python/graph-objects.md

@@ -60,9 +60,9 @@ Graph objects have several benefits compared to plain Python dictionaries:
 
 The recommended way to create figures is using the [functions in the plotly.express module](https://plotly.com/python-api-reference/), [collectively known as Plotly Express](/python/plotly-express/), which all return instances of `plotly.graph_objects.Figure`, so every figure produced with the plotly library, actually uses graph objects under the hood, unless manually constructed out of dictionaries.
 
-That said, certain kinds of figures are not yet possible to create with Plotly Express, such as figures that use certain 3D trace-types like [`mesh`](/python/3d-mesh/) or [`isosurface`](/python/3d-isosurface-plots/). In addition, certain figures are cumbersome to create by starting from a figure created with Plotly Express, for example figures with [subplots of different types](/python/mixed-subplots/), [dual-axis plots](/python/multiple-axes/), or [faceted plots](/python/facet-plots/) with multiple different types of traces. To construct such figures, it can be easier to start from an empty `plotly.graph_objects.Figure` object (or one configured with subplots via the [make_subplots() function](/python/subplots/)) and progressively add traces and update attributes as above.
+That said, certain kinds of figures are not yet possible to create with Plotly Express, such as figures that use certain 3D trace-types like [`mesh`](/python/3d-mesh/) or [`isosurface`](/python/3d-isosurface-plots/). In addition, certain figures are cumbersome to create by starting from a figure created with Plotly Express, for example figures with [subplots of different types](/python/mixed-subplots/), [dual-axis plots](/python/multiple-axes/), or [faceted plots](/python/facet-plots/) with multiple different types of traces. To construct such figures, it can be easier to start from an empty `plotly.graph_objects.Figure` object (or one configured with subplots via the [make_subplots() function](/python/subplots/)) and progressively add traces and update attributes as above. Every `plotly` documentation page lists the Plotly Express option at the top if a Plotly Express function exists to make the kind of chart in question, and then the graph objects version below.
 
-Note that the figures produced by Plotly Express **in a single function-call** are [easy to customize at creation-time](/python/styling-plotly-express/), and to [manipulate after creation](/python/creating-and-updating-figures/) using the `update_*` and `add_*` methods. The figures produced by Plotly Express can always be built from the ground up using graph objects, but this approach typically takes **5-100 lines of code rather than 1**. Here is a simple example of how to produce the same figure object from the same data, once with Plotly Express and once without. The data in this example is in "long form" but [Plotly Express also accepts data in "wide form"](/python/wide-form/) and the line-count savings from Plotly Express over graph objects are comparable. More complex figures such as [parallel coordinates](/python/parallel-coordinates-plot/), [facet plots](/python/facet-plots/) or [animations](/python/animations/) require many more lines of figure-specific graph objects code, whereas switching from one representation to another with Plotly Express usually involves changing just a few characters.
+Note that the figures produced by Plotly Express **in a single function-call** are [easy to customize at creation-time](/python/styling-plotly-express/), and to [manipulate after creation](/python/creating-and-updating-figures/) using the `update_*` and `add_*` methods. The figures produced by Plotly Express can always be built from the ground up using graph objects, but this approach typically takes **5-100 lines of code rather than 1**. Here is a simple example of how to produce the same figure object from the same data, once with Plotly Express and once without. The data in this example is in "long form" but [Plotly Express also accepts data in "wide form"](/python/wide-form/) and the line-count savings from Plotly Express over graph objects are comparable. More complex figures such as [sunbursts](/python/sunburst-charts/), [parallel coordinates](/python/parallel-coordinates-plot/), [facet plots](/python/facet-plots/) or [animations](/python/animations/) require many more lines of figure-specific graph objects code, whereas switching from one representation to another with Plotly Express usually involves changing just a few characters.
 
 ```python
 import pandas as pd

doc/python/heatmaps.md

@@ -67,7 +67,7 @@ fig.show()
 
 ### Basic Heatmap with `plotly.graph_objects`
 
-If Plotly Express does not provide a good starting point, it is also possible to use the more generic `go.Heatmap` function from `plotly.graph_objects`.
+If Plotly Express does not provide a good starting point, it is also possible to use [the more generic `go.Heatmap` class from `plotly.graph_objects`](/python/graph-objects/).
 
 ```python
 import plotly.graph_objects as go
@@ -182,4 +182,4 @@ Arrays of rasterized values build by datashader can be visualized using
 plotly's heatmaps, as shown in the [plotly and datashader tutorial](/python/datashader/).
 
 #### Reference
-See https://plotly.com/python/reference/#heatmap for more information and chart attribute options!
+See https://plotly.com/python/reference/#heatmap for more information and chart attribute options!

doc/python/histograms.md

@@ -146,7 +146,7 @@ fig.show()
 
 ## Histograms with go.Histogram
 
-If Plotly Express does not provide a good starting point, it is also possible to use the more generic `go.Histogram` from `plotly.graph_objects`. All of the available histogram options are described in the histogram section of the reference page: https://plotly.com/python/reference#histogram.
+If Plotly Express does not provide a good starting point, it is also possible to use [the more generic `go.Histogram` class from `plotly.graph_objects`](/python/graph-objects/). All of the available histogram options are described in the histogram section of the reference page: https://plotly.com/python/reference#histogram.
 
 ### Basic Histogram
 
@@ -392,4 +392,4 @@ fig.show()
 
 #### Reference
 
-See https://plotly.com/python/reference/#histogram for more information and chart attribute options!
+See https://plotly.com/python/reference/#histogram for more information and chart attribute options!

doc/python/horizontal-bar-charts.md

@@ -64,7 +64,7 @@ fig.show()
 
 ### Horizontal Bar Chart with go.Bar
 
-You can also use the more generic function `go.Bar` from `plotly.graph_objects`. All the options of `go.Bar` are documented in the reference https://plotly.com/python/reference/#bar
+You can also use [the more generic `go.Bar` class from `plotly.graph_objects`](/python/graph-objects/). All the options of `go.Bar` are documented in the reference https://plotly.com/python/reference/#bar
 
 #### Basic Horizontal Bar Chart
 
@@ -335,4 +335,4 @@ fig.show()
 
 ### Reference
 
-See more examples of bar charts and styling options [here](https://plotly.com/python/bar-charts/).<br> See https://plotly.com/python/reference/#bar for more information and chart attribute options!
+See more examples of bar charts and styling options [here](https://plotly.com/python/bar-charts/).<br> See https://plotly.com/python/reference/#bar for more information and chart attribute options!

doc/python/line-and-scatter.md

@@ -88,7 +88,7 @@ fig.show()
 
 ## Scatter and line plot with go.Scatter
 
-If Plotly Express does not provide a good starting point, it is possible to use the more generic `go.Scatter` function from `plotly.graph_objects`. Whereas `plotly.express` has two functions `scatter` and `line`, `go.Scatter` can be used both for plotting points (makers) or lines, depending on the value of `mode`. The different options of `go.Scatter` are documented in its [reference page](https://plotly.com/python/reference/#scatter).
+If Plotly Express does not provide a good starting point, it is possible to use [the more generic `go.Scatter` class from `plotly.graph_objects`](/python/graph-objects/). Whereas `plotly.express` has two functions `scatter` and `line`, `go.Scatter` can be used both for plotting points (makers) or lines, depending on the value of `mode`. The different options of `go.Scatter` are documented in its [reference page](https://plotly.com/python/reference/#scatter).
 
 #### Simple Scatter Plot
 
@@ -276,4 +276,4 @@ fig.show()
 
 ### Reference
 
-See https://plotly.com/python/reference/#scatter or https://plotly.com/python/reference/#scattergl for more information and chart attribute options!
+See https://plotly.com/python/reference/#scatter or https://plotly.com/python/reference/#scattergl for more information and chart attribute options!

doc/python/line-charts.md

@@ -71,7 +71,7 @@ fig.show()
 
 ### Line Plot with go.Scatter
 
-If Plotly Express does not provide a good starting point, it is possible to use the more generic `go.Scatter` function from `plotly.graph_objects`. Whereas `plotly.express` has two functions `scatter` and `line`, `go.Scatter` can be used both for plotting points (makers) or lines, depending on the value of `mode`. The different options of `go.Scatter` are documented in its [reference page](https://plotly.com/python/reference/#scatter).
+If Plotly Express does not provide a good starting point, it is possible to use [the more generic `go.Scatter` class from `plotly.graph_objects`](/python/graph-objects/). Whereas `plotly.express` has two functions `scatter` and `line`, `go.Scatter` can be used both for plotting points (makers) or lines, depending on the value of `mode`. The different options of `go.Scatter` are documented in its [reference page](https://plotly.com/python/reference/#scatter).
 
 #### Simple Line Plot
 
@@ -407,4 +407,4 @@ fig.show()
 
 #### Reference
 
-See https://plotly.com/python/reference/#scatter for more information and chart attribute options!
+See https://plotly.com/python/reference/#scatter for more information and chart attribute options!

doc/python/mapbox-county-choropleth.md

@@ -159,7 +159,7 @@ fig.show()
 
 ### Choropleth map using plotly.graph_objects and carto base map (no token needed)
 
-If Plotly Express does not provide a good starting point, it is also possible to use the more generic `go.Choroplethmapbox` function from `plotly.graph_objects`.
+If Plotly Express does not provide a good starting point, it is also possible to use [the more generic `go.Choroplethmapbox` class from `plotly.graph_objects`](/python/graph-objects/).
 
 ```python
 from urllib.request import urlopen
@@ -209,4 +209,4 @@ fig.show()
 
 #### Reference
 
-See https://plotly.com/python/reference/#choroplethmapbox for more information about mapbox and their attribute options.
+See https://plotly.com/python/reference/#choroplethmapbox for more information about mapbox and their attribute options.

doc/python/mapbox-density-heatmaps.md

@@ -56,7 +56,7 @@ fig.show()
 
 ### Stamen Terrain base map (no token needed): density mapbox with `plotly.graph_objects`
 
-If Plotly Express does not provide a good starting point, it is also possible to use the more generic `go.Densitymapbox` function from `plotly.graph_objects`.
+If Plotly Express does not provide a good starting point, it is also possible to use [the more generic `go.Densitymapbox` class from `plotly.graph_objects`](/python/graph-objects/).
 
 ```python
 import pandas as pd
@@ -72,4 +72,4 @@ fig.show()
 
 #### Reference
 
-See https://plotly.com/python/reference/#densitymapbox for more information about mapbox and their attribute options.
+See https://plotly.com/python/reference/#densitymapbox for more information about mapbox and their attribute options.

doc/python/pie-charts.md

@@ -104,7 +104,7 @@ fig.show()
 
 ### Basic Pie Chart with go.Pie
 
-If Plotly Express does not provide a good starting point, it is also possible to use the more generic `go.Pie` function from `plotly.graph_objects`.
+If Plotly Express does not provide a good starting point, it is also possible to use [the more generic `go.Pie` class from `plotly.graph_objects`](/python/graph-objects/).
 
 In `go.Pie`, data visualized by the sectors of the pie is set in `values`. The sector labels are set in `labels`. The sector colors are set in `marker.colors`.
 
@@ -304,4 +304,4 @@ fig.show()
 
 #### Reference
 
-See https://plotly.com/python/reference/#pie for more information and chart attribute options!
+See https://plotly.com/python/reference/#pie for more information and chart attribute options!

doc/python/polar-chart.md

@@ -85,7 +85,7 @@ fig.show()
 
 ## Polar Scatter Plot with go.Scatterpolar
 
-If Plotly Express does not provide a good starting point, you can use the more generic `go.Scatterpolar`. All the options are documented in the [reference page](https://plotly.com/python/reference/#scatterpolar).
+If Plotly Express does not provide a good starting point, you can use [the more generic `go.Scatterpolar` class from `plotly.graph_objects`](/python/graph-objects/). All the options are documented in the [reference page](https://plotly.com/python/reference/#scatterpolar).
 
 #### Basic Polar Chart
 
@@ -438,4 +438,4 @@ fig.show()
 
 #### Reference
 
-See https://plotly.com/python/reference/#scatterpolar for more information and chart attribute options!
+See https://plotly.com/python/reference/#scatterpolar for more information and chart attribute options!

doc/python/splom.md

@@ -81,7 +81,7 @@ fig.show()
 
 ### Scatter matrix (splom) with go.Splom
 
-If Plotly Express does not provide a good starting point, it is possible to use the more generic `go.Splom` function. All its parameters are documented in the reference page https://plotly.com/python/reference/#splom.
+If Plotly Express does not provide a good starting point, it is possible to use [the more generic `go.Splom` class from `plotly.graph_objects`](/python/graph-objects/). All its parameters are documented in the reference page https://plotly.com/python/reference/#splom.
 
 The Plotly splom trace implementation for the scatterplot matrix does not require to set $x=Xi$ , and $y=Xj$, for each scatter plot. All arrays, $X_1,X_2,…,X_n$ , are passed once, through a list of dicts called dimensions, i.e. each array/variable represents a dimension.
 
@@ -289,4 +289,4 @@ fig.update_layout(title=title,
                   hovermode='closest')
 
 fig.show()
-```
+```