Update px-arguments.md

Author: LiamConnors

doc/python/px-arguments.md

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   plotly:
     description: Input data arguments accepted by Plotly Express functions
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@@ -37,7 +37,9 @@ jupyter:
 
 [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 Pandas `DataFrame` (in either "long" or "wide" format, see below). [`px.imshow` operates on matrix-like data](/python/imshow/) you might store in a `numpy` or `xarray` array and functions like [`px.choropleth` and `px.choropleth_mapbox` can operate on geographic data](/python/maps/) of the kind you might store in a GeoPandas `GeoDataFrame`. This page details how to provide column-oriented data to most Plotly Express functions.
+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.
+
+[`px.imshow` operates on matrix-like data](/python/imshow/) you might store in a `numpy` or `xarray` array and functions like [`px.choropleth` and `px.choropleth_mapbox` can operate on geographic data](/python/maps/) of the kind you might store in a GeoPandas `GeoDataFrame`. This page details how to provide column-oriented data to most Plotly Express functions.
 
 
 
@@ -166,6 +168,38 @@ fig = px.bar(df, x='year', y=gdp, color='continent', labels={'y':'gdp'},
 fig.show()
 ```
 
+### Input Data as Non-Pandas `DataFrame`s
+
+**New in 5.16**
+
+In the examples above, we've used Pandas DataFrames. You can also provide another type of DataFrame to the `data_frame` argument if that DataFrame has a `to_pandas` method or supports the [Python dataframe interchange protocol](https://data-apis.org/dataframe-protocol/latest/index.html), for example, a [Polars](https://www.pola.rs/) DataFrame.
+
+Plotly Express uses Pandas internally to process the data. When you provide a Non-Pandas DataFrame to the `data_frame` argument of a Plotly Express function, the entire DataFrame is converted to a Pandas DataFrame.
+
+If you are using a type of DataFrame that doesn't have a `to_pandas` method, but supports the Python dataframe interchange protocol, you'll need to have Pandas version 2.0.3 or later installed. 
+
+If you are using Polars, you'll need to install `pyarrow`, which is used by its [`to_pandas` method](
+https://pola-rs.github.io/polars/py-polars/html/reference/dataframe/api/polars.DataFrame.to_pandas.html)
+
+In this example, we use a Polars DataFrame.
+
+```python
+import polars as pl
+import plotly.express as px
+
+wide_df = pl.DataFrame(
+    {
+        "nation": ["South Korea", "China", "Canada"],
+        "gold": [24, 10, 9],
+        "silver": [13, 15, 12],
+        "bronze": [9, 12, 12],
+    }
+)
+
+fig = px.bar(wide_df, x="nation", y=["gold", "silver", "bronze"], title="Wide-Form Input")
+fig.show()
+```
+
 ### Input Data as array-like columns: NumPy arrays, lists...
 
 `px` arguments can also be array-like objects such as lists, NumPy arrays, in both long-form or wide-form (for certain functions).
@@ -243,4 +277,4 @@ fig = px.bar(df, x='year', y=gdp, color='continent', labels={'y':'log gdp'},
              hover_data=['country'],
              title='Evolution of world GDP')
 fig.show()
-```
+```