diff --git a/doc/python/3d-scatter-plots.md b/doc/python/3d-scatter-plots.md
index 12b2de61f67..46e389b5654 100644
--- a/doc/python/3d-scatter-plots.md
+++ b/doc/python/3d-scatter-plots.md
@@ -70,6 +70,7 @@ fig = px.scatter_3d(df, x='sepal_length', y='sepal_width', z='petal_width',
 
 # tight layout
 fig.update_layout(margin=dict(l=0, r=0, b=0, t=0))
+fig.show()
 ```
 
 #### 3d scatter plots in Dash
diff --git a/doc/python/axes.md b/doc/python/axes.md
index b87e156aace..6b53230ad11 100644
--- a/doc/python/axes.md
+++ b/doc/python/axes.md
@@ -33,7 +33,7 @@ jupyter:
     thumbnail: thumbnail/axes.png
 ---
 
-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/).
+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/).
 
 Other kinds of subplots and axes are described in other tutorials:
 
@@ -154,7 +154,7 @@ fig.update_yaxes(ticklabelposition="inside top", title=None)
 fig.show()
 ```
 
-#### Specifying Label Aliases 
+#### Specifying Label Aliases
 
 *New in 5.14*
 
diff --git a/doc/python/colorscales.md b/doc/python/colorscales.md
index fe2ac574227..7e2aeb9ad73 100644
--- a/doc/python/colorscales.md
+++ b/doc/python/colorscales.md
@@ -6,7 +6,7 @@ jupyter:
       extension: .md
       format_name: markdown
       format_version: '1.3'
-      jupytext_version: 1.14.5
+      jupytext_version: 1.14.6
   kernelspec:
     display_name: Python 3 (ipykernel)
     language: python
@@ -20,7 +20,7 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.10.11
+    version: 3.10.8
   plotly:
     description: How to set, create and control continuous color scales and color
       bars in scatter, bar, map and heatmap figures.
@@ -307,11 +307,11 @@ Using `labelalias` you can replace some labels on the `colorbar` with alternativ
 ```python
 import plotly.graph_objects as go
 
-import urllib
+import urllib.request as request
 import json
 
 # Load heatmap data
-response = urllib.request.urlopen(
+response = request.urlopen(
     "https://raw.githubusercontent.com/plotly/datasets/master/custom_heatmap_colorscale.json")
 dataset = json.load(response)
 
diff --git a/doc/python/configuration-options.md b/doc/python/configuration-options.md
index f0590762fef..52dcc8764ec 100644
--- a/doc/python/configuration-options.md
+++ b/doc/python/configuration-options.md
@@ -53,7 +53,7 @@ import plotly.graph_objects as go
 
 fig = go.Figure()
 
-config = dict({'scrollZoom': True})
+config = {'scrollZoom': True}
 
 fig.add_trace(
     go.Scatter(
@@ -244,6 +244,8 @@ fig.add_trace(
         y=[1, 3, 1]))
 
 fig.update_layout(modebar_remove=['zoom', 'pan'])
+
+fig.show()
 ```
 
 ### Add optional shape-drawing buttons to modebar
@@ -253,16 +255,19 @@ fig.update_layout(modebar_remove=['zoom', 'pan'])
 Some modebar buttons of Cartesian plots are optional and have to be added explicitly, using the `modeBarButtonsToAdd` config attribute. These buttons are used for drawing or erasing shapes. See [the tutorial on shapes and shape drawing](python/shapes#drawing-shapes-on-cartesian-plots) for more details.
 
 ```python
-import plotly.graph_objects as go
 import plotly.express as px
+
 df = px.data.iris()
+
 fig = px.scatter(df, x='petal_width', y='sepal_length', color='species')
+
 fig.update_layout(
     dragmode='drawopenpath',
     newshape_line_color='cyan',
     title_text='Draw a path to separate versicolor and virginica'
 )
-fig.show(config={'modeBarButtonsToAdd':['drawline',
+
+fig.show(config={'modeBarButtonsToAdd': ['drawline',
                                         'drawopenpath',
                                         'drawclosedpath',
                                         'drawcircle',
@@ -276,10 +281,12 @@ fig.show(config={'modeBarButtonsToAdd':['drawline',
 The `layout.modebar.add` attribute can be used instead of the approach used above:
 
 ```python
-import plotly.graph_objects as go
 import plotly.express as px
+
 df = px.data.iris()
+
 fig = px.scatter(df, x='petal_width', y='sepal_length', color='species')
+
 fig.update_layout(
     dragmode='drawopenpath',
     newshape_line_color='cyan',
@@ -292,6 +299,8 @@ fig.update_layout(
         'eraseshape'
        ]
 )
+
+fig.show()
 ```
 
 ### Double-Click Delay
@@ -304,12 +313,12 @@ import plotly.graph_objects as go
 config = {'doubleClickDelay': 1000}
 
 fig = go.Figure(go.Bar(
-    y = [3, 5, 3, 2],
-    x = ["2019-09-02", "2019-10-10", "2019-11-12", "2019-12-22"],
-    texttemplate = "%{label}",
-    textposition = "inside"))
+    y=[3, 5, 3, 2],
+    x=["2019-09-02", "2019-10-10", "2019-11-12", "2019-12-22"],
+    texttemplate="%{label}",
+    textposition="inside"))
 
-fig.update_layout(xaxis = {'type': 'date'})
+fig.update_layout(xaxis={'type': 'date'})
 
 fig.show(config=config)
 ```
@@ -320,4 +329,4 @@ The same configuration dictionary that you pass to the `config` parameter of the
 
 #### Reference
 
-See config options at https://github.com/plotly/plotly.js/blob/master/src/plot_api/plot_config.js#L6
+See config options at https://github.com/plotly/plotly.js/blob/master/src/plot_api/plot_config.js
diff --git a/doc/python/figure-factory-subplots.md b/doc/python/figure-factory-subplots.md
index eaaa55b797a..3a6c837692d 100644
--- a/doc/python/figure-factory-subplots.md
+++ b/doc/python/figure-factory-subplots.md
@@ -61,7 +61,7 @@ Y, X = np.meshgrid(x, y)
 u = -1 - X**2 + Y
 v = 1 + X - Y**2
 
-fig2 = ff.create_streamline(x, y, u, v, arrow_scale=.1, name='Steamline')
+fig2 = ff.create_streamline(x, y, u, v, arrow_scale=.1, name='Streamline')
 ```
 
 Edit the figures' x and y axes attributes to create subplots:
diff --git a/doc/python/legend.md b/doc/python/legend.md
index 9ca47748be1..49b989405b5 100644
--- a/doc/python/legend.md
+++ b/doc/python/legend.md
@@ -6,7 +6,7 @@ jupyter:
       extension: .md
       format_name: markdown
       format_version: '1.3'
-      jupytext_version: 1.14.5
+      jupytext_version: 1.14.6
   kernelspec:
     display_name: Python 3 (ipykernel)
     language: python
@@ -580,7 +580,7 @@ fig.show()
 
 By default, all traces appear on one legend. To have multiple legends, specify an alternative legend for a trace using the `legend` property. For a second legend, set `legend="legend2"`. Specify more legends with `legend="legend3"`, `legend="legend4"` and so on.
 
-In this example, the last two scatter traces display on the second legend, "legend2". On the figure's layout, we then position and style this legend to display on the right of the graph below the first legend.
+In this example, the last two scatter traces display on the second legend, "legend2". On the figure's layout, we then position and style each legend.
 
 
 ```python
@@ -622,20 +622,25 @@ fig = go.Figure(
     ],
     layout=dict(
         title="GDP Per Capita",
-        legend={"title": "By country", "bgcolor": "Orange",},
+        legend={
+            "title": "By country",
+            "xref": "container",
+            "yref": "container",
+            "y": 0.65,
+            "bgcolor": "Orange",
+        },
         legend2={
-            "x": 1.155,
-            "y": 0.55,
-            "xanchor": "right",
-            "yanchor": "middle",
+            "title": "By continent",
+            "xref": "container",
+            "yref": "container",
+            "y": 0.85,
             "bgcolor": "Gold",
-            "title": {"text": "By continent"},
+
         },
     ),
 )
 
 fig.show()
-
 ```
 
 ### Positioning Legends
@@ -666,7 +671,6 @@ fig = go.Figure(
             "xref": "container",
             "yref": "container",
             "bgcolor": "Gold",
-            "title": {"text": "By continent"},
         },
     ),
 )
diff --git a/doc/python/lines-on-mapbox.md b/doc/python/lines-on-mapbox.md
index 1a56296724f..3d7bc953175 100644
--- a/doc/python/lines-on-mapbox.md
+++ b/doc/python/lines-on-mapbox.md
@@ -37,7 +37,7 @@ jupyter:
 
 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.
 
-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.
+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.
 
 ### Lines on Mapbox maps using Plotly Express
 
@@ -132,5 +132,5 @@ fig.show()
 
 #### Reference
 
-See [function reference for `px.(line_mapbox)`](https://plotly.com/python-api-reference/generated/plotly.express.line_mapbox) or 
+See [function reference for `px.(line_mapbox)`](https://plotly.com/python-api-reference/generated/plotly.express.line_mapbox) or
 https://plotly.com/python/reference/scattermapbox/ for more information about mapbox and their attribute options.
diff --git a/doc/python/map-configuration.md b/doc/python/map-configuration.md
index 5a2f5a349f6..6e9f54e4d7e 100644
--- a/doc/python/map-configuration.md
+++ b/doc/python/map-configuration.md
@@ -5,10 +5,10 @@ jupyter:
     text_representation:
       extension: .md
       format_name: markdown
-      format_version: '1.2'
-      jupytext_version: 1.3.1
+      format_version: '1.3'
+      jupytext_version: 1.14.7
   kernelspec:
-    display_name: Python 3
+    display_name: Python 3 (ipykernel)
     language: python
     name: python3
   language_info:
@@ -20,7 +20,7 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.6.8
+    version: 3.10.4
   plotly:
     description: How to configure and style base maps for Choropleths and Bubble Maps.
     display_as: maps
@@ -119,9 +119,7 @@ fig.show()
 
 ### Map Projections
 
-Geo maps are drawn according to a given map [projection](https://en.wikipedia.org/wiki/Map_projection) that flattens the Earth's roughly-spherical surface into a 2-dimensional space.
-
-The available projections are `'equirectangular'`, `'mercator'`, `'orthographic'`, `'natural earth'`, `'kavrayskiy7'`, `'miller'`, `'robinson'`, `'eckert4'`, `'azimuthal equal area'`, `'azimuthal equidistant'`, `'conic equal area'`, `'conic conformal'`, `'conic equidistant'`, `'gnomonic'`, `'stereographic'`, `'mollweide'`, `'hammer'`, `'transverse mercator'`, `'albers usa'`, `'winkel tripel'`, `'aitoff'` and `'sinusoidal'`.
+Geo maps are drawn according to a given map [projection](https://en.wikipedia.org/wiki/Map_projection) that flattens the Earth's roughly-spherical surface into a 2-dimensional space. In the following examples, we show the `'orthographic'` and `'natural earth'` projections, two of the many projection types available. For a full list of available projection types, see the [layout.geo reference documentation](https://plotly.com/python/reference/layout/geo/#layout-geo-projection-type).
 
 ```python
 import plotly.graph_objects as go
@@ -221,7 +219,3 @@ fig.show()
 ### Reference
 
 See https://plotly.com/python/reference/layout/geo/ for more information and chart attribute options!
-
-```python
-
-```
\ No newline at end of file
diff --git a/doc/python/marker-style.md b/doc/python/marker-style.md
index 128b22d04c5..21b0a2ac052 100644
--- a/doc/python/marker-style.md
+++ b/doc/python/marker-style.md
@@ -326,7 +326,7 @@ fig.show()
 
 The `marker_symbol` attribute allows you to choose from a wide array of symbols to represent markers in your figures.
 
-The basic symbols are: `circle`, `square`, `diamond`, `cross`, `x`, `triangle`, `pentagon`, `hexagram`, `star`, `diamond`, `hourglass`, `bowtie`, `asterisk`, `hash`, `y`, and `line`.
+The basic symbols are: `circle`, `square`, `diamond`, `cross`, `x`, `triangle`, `pentagon`, `hexagram`, `star`, `hourglass`, `bowtie`, `asterisk`, `hash`, `y`, and `line`.
 
 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.
 
diff --git a/doc/python/parallel-categories-diagram.md b/doc/python/parallel-categories-diagram.md
index 11ac1f3e410..51ecd4168bb 100644
--- a/doc/python/parallel-categories-diagram.md
+++ b/doc/python/parallel-categories-diagram.md
@@ -45,7 +45,7 @@ For other representations of multivariate data, also see [parallel coordinates](
 
 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.
 
-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. 
+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.
 
 ```python
 import plotly.express as px
@@ -58,7 +58,7 @@ fig.show()
 
 #### Style Diagram
 
-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.
+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.
 
 ```python
 import plotly.express as px
diff --git a/doc/python/shapes.md b/doc/python/shapes.md
index f44c6050c48..ca28a81bbb9 100644
--- a/doc/python/shapes.md
+++ b/doc/python/shapes.md
@@ -6,7 +6,7 @@ jupyter:
       extension: .md
       format_name: markdown
       format_version: '1.3'
-      jupytext_version: 1.14.5
+      jupytext_version: 1.14.6
   kernelspec:
     display_name: Python 3 (ipykernel)
     language: python
@@ -20,7 +20,7 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.8.8
+    version: 3.10.10
   plotly:
     description: How to make SVG shapes in python. Examples of lines, circle, rectangle,
       and path.
@@ -917,18 +917,27 @@ fig.show()
 
 *New in 5.15*
 
-Use `texttemplate` to add text with variables to shapes. `texttemplate` uses d3 number and date formatting and supports raw variables, which use the raw data from the shape definition, and some calculated variables. Add a variable with "%{variable}".
+Use `texttemplate` to add text with variables to shapes. You have access to raw variables (`x0`, `x1`, `y0`, `y1`), which use raw data values from the shape definition, and the following calculated variables:
 
-This example adds the raw variables `x0` and `y0` to a rectangle and shows the calculated variables `height`, `slope`, and `width` on three other shapes. 
+- `xcenter`: (x0 + x1) / 2
+- `ycenter`: (y0 + y1) / 2
+- `dx`: x1 - x0
+- `dy`: y1 - y0
+- `width`: abs(x1 - x0)
+- `height`: abs(y1 - y0)
+- `length` (for lines only): sqrt(dx^2 + dy^2)
+- `slope`: (y1 - y0) / (x1 - x0)
 
-For a complete list of available variables, see the [Shape Reference Docs](https://plotly.com/python/reference/layout/shapes/).
+`texttemplate` supports d3 number and date formatting.
 
+Add a variable with "%{variable}". This example adds the raw variables `x0` and `y0` to a rectangle and shows the calculated variables `height`, `slope`, `length`, and `width` on three other shapes. 
 
 ```python
 import plotly.graph_objects as go
 
 fig = go.Figure()
 
+
 fig.add_shape(
     type="rect",
     fillcolor="MediumSlateBlue",
@@ -955,9 +964,12 @@ fig.add_shape(
     x0=3,
     y0=0.5,
     x1=5,
-    y1=0.8,
+    y1=1.5,
     line_width=3,
-    label=dict(texttemplate="Slope: %{slope:.3f}", font=dict(size=20)),
+    label=dict(
+        texttemplate="Slope of %{slope:.3f} and length of %{length:.3f}",
+        font=dict(size=20),
+    ),
 )
 fig.add_shape(
     type="rect",
@@ -980,15 +992,31 @@ fig.show()
 
 *New in 5.15*
 
-Use `texttemplate` to add text with variables to new shapes drawn on the graph. This example figure is configured to allow the user to draw lines and automatically labels each line with its slope. Select **Draw line** in the modebar to try it out.
+You can also use `texttemplate` to add text with variables to new shapes drawn on the graph.
+
+In this example, we enable drawing lines on the figure by adding `drawline` to `modeBarButtonsToAdd` in `config`. We then define a `texttemplate` for shapes that shows the calculated variable `dy`. Select **Draw line** in the modebar to try it out.
 
 ```python
 import plotly.graph_objects as go
+from plotly import data
+
+df = data.stocks()
 
 fig = go.Figure(
-    layout=go.Layout(newshape=dict(label=dict(texttemplate="Slope: %{slope:.3f}")))
+    data=go.Scatter(
+        x=df.date,
+        y=df.GOOG,
+    ),
+    layout=go.Layout(
+        yaxis=dict(title="Price in USD"),
+        newshape=dict(
+            label=dict(texttemplate="Change: %{dy:.2f}")
+        ),
+        title="Google Share Price 2018/2019",
+    ),
 )
 
+
 fig.show(
     config={
         "modeBarButtonsToAdd": [
@@ -996,7 +1024,6 @@ fig.show(
         ]
     }
 )
-
 ```
 
 ### Reference
diff --git a/doc/python/treemaps.md b/doc/python/treemaps.md
index b86636e01df..98fbeadcd40 100644
--- a/doc/python/treemaps.md
+++ b/doc/python/treemaps.md
@@ -186,7 +186,7 @@ This example uses the following attributes:
 1.  [values](https://plotly.com/python/reference/treemap/#treemap-values): sets the values associated with each of the sectors.
 2.  [textinfo](https://plotly.com/python/reference/treemap/#treemap-textinfo): determines which trace information appear on the graph that can be 'text', 'value', 'current path', 'percent root', 'percent entry', and 'percent parent', or any combination of them.
 3.  [pathbar](https://plotly.com/python/reference/treemap/#treemap-pathbar): a main extra feature of treemap to display the current path of the visible portion of the hierarchical map. It may also be useful for zooming out of the graph.
-4.  [branchvalues](https://plotly.com/python/reference/treemap/#treemap-branchvalues): determines how the items in `values` are summed. When set to "total", items in `values` are taken to be value of all its descendants. In the example below Eva = 65, which is equal to 14 + 12 + 10 + 2 + 6 + 6 + 1 + 4.
+4.  [branchvalues](https://plotly.com/python/reference/treemap/#treemap-branchvalues): determines how the items in `values` are summed. When set to "total", items in `values` are taken to be value of all its descendants. In the example below Eve = 65, which is equal to 14 + 12 + 10 + 2 + 6 + 6 + 1 + 4.
     When set to "remainder", items in `values` corresponding to the root and the branches sectors are taken to be the extra part not part of the sum of the values at their leaves.
 
 ```python
diff --git a/doc/what_about_dash.md b/doc/what_about_dash.md
index bef6ac916dd..696aa93a632 100644
--- a/doc/what_about_dash.md
+++ b/doc/what_about_dash.md
@@ -15,11 +15,9 @@ fig = go.Figure() # or any Plotly Express function e.g. px.bar(...)
 # fig.add_trace( ... )
 # fig.update_layout( ... )
 
-import dash
-import dash_core_components as dcc
-import dash_html_components as html
+from dash import Dash, dcc, html
 
-app = dash.Dash()
+app = Dash()
 app.layout = html.Div([
     dcc.Graph(figure=fig)
 ])