diff --git a/python/polar-chart.md b/python/polar-chart.md
index 4df95d166..077fb6ea7 100644
--- a/python/polar-chart.md
+++ b/python/polar-chart.md
@@ -136,47 +136,28 @@ fig.update_layout(
 fig.show()
 ```
 
-#### Area Polar Chart
+#### Polar Bar Chart
 
 a.k.a matplotlib logo in a few lines of code
 
 ```python
 import plotly.graph_objects as go
 
-fig = go.Figure()
-
-fig.add_trace(go.Scatterpolar(
-        r = [0, 1.5, 1.5, 0, 2.5, 2.5, 0],
-        theta = [0, 10, 25, 0, 205, 215, 0],
-        fillcolor = '#709BFF',
-    ))
-fig.add_trace(go.Scatterpolar(
-        r = [0, 3.5, 3.5, 0],
-        theta = [0, 55, 75, 0],
-        fillcolor = '#E4FF87',
-    ))
-fig.add_trace(go.Scatterpolar(
-        r = [0, 4.5, 4.5, 0, 4.5, 4.5, 0],
-        theta = [0, 100, 120, 0, 305, 320, 0],
-        fillcolor = '#FFAA70',
-    ))
-fig.add_trace(go.Scatterpolar(
-        r = [0, 4, 4, 0],
-        theta = [0, 165, 195, 0],
-        fillcolor = '#FFDF70',
-    ))
-fig.add_trace(go.Scatterpolar(
-        r = [0, 3, 3, 0],
-        theta = [0, 262.5, 277.5, 0],
-        fillcolor = '#B6FFB4',
-    ))
+fig = go.Figure(go.Barpolar(
+    r=[3.5, 1.5, 2.5, 4.5, 4.5, 4, 3],
+    theta=[65, 15, 210, 110, 312.5, 180, 270],
+    width=[20,15,10,20,15,30,15,],
+    marker_color=["#E4FF87", '#709BFF', '#709BFF', '#FFAA70', '#FFAA70', '#FFDF70', '#B6FFB4'],
+    marker_line_color="black",
+    marker_line_width=2,
+))
 
-fig.update_traces(mode='lines', fill='toself', line_color='black')
 fig.update_layout(
+    template=None,
     polar = dict(
-        radialaxis = dict(visible=True, range=[0, 5])
-    ),
-    showlegend = False,
+        radialaxis = dict(range=[0, 5], showticklabels=False, ticks=''),
+        angularaxis = dict(showticklabels=False, ticks='')
+    )
 )
 
 fig.show()
diff --git a/python/wind-rose-charts.md b/python/wind-rose-charts.md
index ca2f0b765..6edf7c320 100644
--- a/python/wind-rose-charts.md
+++ b/python/wind-rose-charts.md
@@ -29,7 +29,7 @@ jupyter:
     ipynb: ~notebook_demo/38
     language: python
     layout: user-guide
-    name: Wind Rose Charts
+    name: Wind Rose and Polar Bar Charts
     order: 8
     page_type: example_index
     permalink: python/wind-rose-charts/
@@ -40,12 +40,12 @@ jupyter:
 
 ### Wind Rose Chart with plotly express
 
-A [wind rose chart](https://en.wikipedia.org/wiki/Wind_rose) is a graphical tool used to visualize how wind speed and direction are typically distributed at a given location. For data stored in a tidy pandas dataframe, use the `px.bar_polar` function from plotly express as below, otherwise use `go.Barpolar` as explained in the next section.
+A [wind rose chart](https://en.wikipedia.org/wiki/Wind_rose) (also known as a polar bar chart) is a graphical tool used to visualize how wind speed and direction are typically distributed at a given location. For data stored in a tidy pandas dataframe, use the `px.bar_polar` function from plotly express as below, otherwise use `go.Barpolar` as explained in the next section.
 
 ```python
 import plotly.express as px
 wind = px.data.wind()
-fig = px.bar_polar(wind, r="frequency", theta="direction", 
+fig = px.bar_polar(wind, r="frequency", theta="direction",
                    color="strength", template="plotly_dark",
                    color_discrete_sequence= px.colors.sequential.Plasma[-2::-1])
 fig.show()
@@ -86,11 +86,11 @@ fig.update_layout(
     legend_font_size=16,
     polar_radialaxis_ticksuffix='%',
     polar_angularaxis_rotation=90,
-    
+
 )
 fig.show()
 ```
 
 #### Reference
 
-See https://plot.ly/python/reference/#barpolar for more information and chart attribute options!
\ No newline at end of file
+See https://plot.ly/python/reference/#barpolar for more information and chart attribute options!