Merge branch 'doc-prod' into update-production-docs

Author: LiamConnors

doc/python/animations.md

@@ -37,7 +37,7 @@ jupyter:
 
 Several [Plotly Express](/python/plotly-express/)  functions support the creation of animated figures through the `animation_frame` and `animation_group` arguments.
 
-Here is an example of an animated scatter plot creating using Plotly Express. Note that you should always fix the `x_range` and `y_range` to ensure that your data remains visible throughout the animation.
+Here is an example of an animated scatter plot created with Plotly Express. Note that you should always fix the `x_range` and `y_range` to ensure that your data remains visible throughout the animation.
 
 ```python
 import plotly.express as px

doc/python/interactive-html-export.md

@@ -46,7 +46,7 @@ Any figure can be saved as an HTML file using the `write_html` method. These HTM
 ```python
 import plotly.express as px
 
-fig =px.scatter(x=range(10), y=range(10))
+fig = px.scatter(x=range(10), y=range(10))
 fig.write_html("path/to/file.html")
 ```
 <!-- #endregion -->

doc/python/px-arguments.md

@@ -35,7 +35,7 @@ jupyter:
 
 ### Plotly Express works with Column-oriented, Matrix or Geographic Data
 
-[Plotly Express](/python/plotly-express/) is the easy-to-use, high-level interface to Plotly, which operates on a variety of types of data and produces [easy-to-style figures](/python/styling-plotly-express/).
+[Plotly Express](/python/plotly-express/) is the easy-to-use, high-level interface to Plotly, which [operates on a variety of types of data](/python/px-arguments/) and produces [easy-to-style figures](/python/styling-plotly-express/).
 
 Plotly Express provides functions to visualize a variety of types of data. Most functions such as `px.bar` or `px.scatter` expect to operate on column-oriented data of the type you might store in a `DataFrame` (in either "long" or "wide" format, see below). These functions use Pandas internally to process the data, but also accept other types of DataFrames as arguments. See the **Input Data as Non-Pandas DataFrames** section below for more details.