Remove deprecated attributes from docs

doc/python/3d-bubble-charts.md

@@ -5,10 +5,10 @@ jupyter:
     text_representation:
       extension: .md
       format_name: markdown
-      format_version: '1.1'
-      jupytext_version: 1.2.3
+      format_version: '1.3'
+      jupytext_version: 1.16.4
   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: 3.7.3
+    version: 3.11.10
   plotly:
     description: How to make 3D Bubble Charts in Python with Plotly. Three examples
       of 3D Bubble Charts.
@@ -113,12 +113,39 @@ fig = go.Figure(data=go.Scatter3d(
         )
 ))
 
-fig.update_layout(width=800, height=800, title = 'Planets!',
-                  scene = dict(xaxis=dict(title='Distance from Sun', titlefont_color='white'),
-                               yaxis=dict(title='Density', titlefont_color='white'),
-                               zaxis=dict(title='Gravity', titlefont_color='white'),
-                               bgcolor = 'rgb(20, 24, 54)'
-                           ))
+fig.update_layout(
+    width=800,
+    height=800,
+    title="Planets!",
+    scene=dict(
+        xaxis=dict(
+            title=dict(
+                text="Distance from Sun",
+                font=dict(
+                    color="white"
+                )
+            )
+        ),
+        yaxis=dict(
+            title=dict(
+                text="Density",
+                font=dict(
+                    color="white"
+                )
+            )
+        ),
+        zaxis=dict(
+            title=dict(
+                text="Gravity",
+                font=dict(
+                    color="white"
+                )
+            )
+        ),
+        bgcolor="rgb(20, 24, 54)"
+    )
+)
+
 
 fig.show()
 ```
@@ -154,16 +181,42 @@ fig = go.Figure(go.Scatter3d(
         )
 ))
 
-fig.update_layout(width=800, height=800, title = 'Planets!',
-                  scene = dict(xaxis=dict(title='Distance from Sun', titlefont_color='white'),
-                               yaxis=dict(title='Density', titlefont_color='white'),
-                               zaxis=dict(title='Gravity', titlefont_color='white'),
-                               bgcolor = 'rgb(20, 24, 54)'
-                           ))
+fig.update_layout(
+    width=800,
+    height=800,
+    title="Planets!",
+    scene=dict(
+        xaxis=dict(
+            title=dict(
+                text="Distance from Sun",
+                font=dict(
+                    color="white"
+                )
+            )
+        ),
+        yaxis=dict(
+            title=dict(
+                text="Density",
+                font=dict(
+                    color="white"
+                )
+            )
+        ),
+        zaxis=dict(
+            title=dict(
+                text="Gravity",
+                font=dict(
+                    color="white"
+                )
+            )
+        ),
+        bgcolor="rgb(20, 24, 54)"
+    )
+)
 
 fig.show()
 ```
 
 #### Reference
 
-See https://plotly.com/python/reference/scatter3d/ and https://plotly.com/python/reference/scatter/#scatter-marker-sizeref <br>for more information and chart attribute options!
+See https://plotly.com/python/reference/scatter3d/ and https://plotly.com/python/reference/scatter/#scatter-marker-sizeref <br>for more information and chart attribute options!

doc/python/bar-charts.md

@@ -37,7 +37,7 @@ 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/).
 
-With `px.bar`, **each row of the DataFrame is represented as a rectangular mark**. To aggregate multiple data points into the same rectangular mark, please refer to the [histogram documentation](/python/histograms). 
+With `px.bar`, **each row of the DataFrame is represented as a rectangular mark**. To aggregate multiple data points into the same rectangular mark, please refer to the [histogram documentation](/python/histograms).
 
 In the example below, there is only a single row of data per year, so a single bar is displayed per year.
 
@@ -152,7 +152,7 @@ fig.show()
 
 ### Aggregating into Single Colored Bars
 
-As noted above `px.bar()` will result in **one rectangle drawn per row of input**. This can sometimes result in a striped look as in the examples above. To combine these rectangles into one per color per position, you can use `px.histogram()`, which has [its own detailed documentation page](/python/histogram). 
+As noted above `px.bar()` will result in **one rectangle drawn per row of input**. This can sometimes result in a striped look as in the examples above. To combine these rectangles into one per color per position, you can use `px.histogram()`, which has [its own detailed documentation page](/python/histogram).
 
 > `px.bar` and `px.histogram` are designed  to be nearly interchangeable in their call signatures, so as to be able to switch between aggregated and disaggregated bar representations.
 
@@ -304,7 +304,7 @@ fig.update_layout(barmode='stack')
 fig.show()
 ```
 
-### Stacked Bar Chart From Aggregating a DataFrame 
+### Stacked Bar Chart From Aggregating a DataFrame
 
 Stacked bar charts are a powerful way to present results summarizing categories generated using the Pandas aggregate commands. `pandas.DataFrame.agg` produces a wide data set format incompatible with `px.bar`. Transposing and updating the indexes to achieve `px.bar` compatibility is a somewhat involved option. Here is one straightforward alternative, which presents the aggregated data as a stacked bar using plotly.graph_objects.
 
@@ -326,19 +326,19 @@ df_summarized["percent of world population"]=100*df_summarized["pop"]/df_summari
 df_summarized["percent of world GDP"]=100*df_summarized["gdp"]/df_summarized["gdp"].sum()
 
 
-df = df_summarized[["continent", 
+df = df_summarized[["continent",
 "percent of world population",
 "percent of world GDP",
 ]]
 
 # We now have a wide data frame, but it's in the opposite orientation from the one that px is designed to deal with.
-# Transposing it and rebuilding the indexes is an option, but iterating through the DF using graph objects is more succinct. 
+# Transposing it and rebuilding the indexes is an option, but iterating through the DF using graph objects is more succinct.
 
 fig=go.Figure()
 for category in df_summarized["continent"].values:
     fig.add_trace(go.Bar(
             x=df.columns[1:],
-            # We need to get a pandas series that contains just the values to graph; 
+            # We need to get a pandas series that contains just the values to graph;
             # We do so by selecting the right row, selecting the right columns
             # and then transposing and using iloc to convert to a series
             # Here, we assume that the bar element category variable is in column 0
@@ -619,8 +619,12 @@ fig.update_layout(
     title='US Export of Plastic Scrap',
     xaxis_tickfont_size=14,
     yaxis=dict(
-        title='USD (millions)',
-        titlefont_size=16,
+        title=dict(
+            text="USD (millions)",
+            font=dict(
+                size=16
+            )
+        ),
         tickfont_size=14,
     ),
     legend=dict(

doc/python/carpet-contour.md

@@ -159,9 +159,10 @@ fig.add_trace(go.Contourcarpet(
     colorbar = dict(
       y = 0,
       yanchor = "bottom",
-      titleside = "right",
       len = 0.75,
-      title = "Pressure coefficient, c<sub>p</sub>"
+      title = dict(
+        text="Pressure coefficient, c<sub>p</sub>",
+        side="right")
     ),
     contours = dict(
       start = -1,

doc/python/colorscales.md

@@ -321,8 +321,10 @@ fig = go.Figure()
 fig.add_trace(go.Heatmap(
     z=dataset["z"],
     colorbar=dict(
-        title="Surface Heat",
-        titleside="top",
+        title=dict(
+            text="Surface Heat",
+            side="top",
+        ),
         tickmode="array",
         tickvals=[2, 25, 50, 75, 100],
         labelalias={100: "Hot", 50: "Mild", 2: "Cold"},
@@ -545,8 +547,10 @@ fig = go.Figure()
 fig.add_trace(go.Heatmap(
     z=dataset["z"],
     colorbar=dict(
-        title="Surface Heat",
-        titleside="top",
+        title=dict(
+            text="Surface Heat",
+            side="top",
+        ),
         tickmode="array",
         tickvals=[2, 50, 100],
         ticktext=["Cool", "Mild", "Hot"],

doc/python/contour-plots.md

@@ -281,12 +281,15 @@ fig = go.Figure(data=
            [0.625, 1.25, 3.125, 6.25, 10.625],
            [0, 0.625, 2.5, 5.625, 10]],
         colorbar=dict(
-            title='Color bar title', # title here
-            titleside='right',
-            titlefont=dict(
-                size=14,
-                family='Arial, sans-serif')
-        )))
+            title=dict(
+                text='Color bar title', # title here
+                side='right',
+                font=dict(
+                    size=14,
+                    family='Arial, sans-serif')
+                )
+            ),
+        ))
 
 fig.show()
 ```

doc/python/multiple-axes.md

@@ -192,18 +192,22 @@ fig.update_layout(
         domain=[0.3, 0.7]
     ),
     yaxis=dict(
-        title="yaxis title",
-        titlefont=dict(
-            color="#1f77b4"
+        title=dict(
+            text="yaxis title",
+            font=dict(
+                color="#1f77b4"
+            )
         ),
         tickfont=dict(
             color="#1f77b4"
         )
     ),
     yaxis2=dict(
-        title="yaxis2 title",
-        titlefont=dict(
-            color="#ff7f0e"
+        title=dict(
+            text="yaxis2 title",
+            font=dict(
+                color="#ff7f0e"
+            )
         ),
         tickfont=dict(
             color="#ff7f0e"
@@ -214,9 +218,11 @@ fig.update_layout(
         position=0.15
     ),
     yaxis3=dict(
-        title="yaxis3 title",
-        titlefont=dict(
-            color="#d62728"
+        title=dict(
+            text="yaxis3 title",
+            font=dict(
+                color="#d62728"
+            )
         ),
         tickfont=dict(
             color="#d62728"
@@ -226,9 +232,11 @@ fig.update_layout(
         side="right"
     ),
     yaxis4=dict(
-        title="yaxis4 title",
-        titlefont=dict(
-            color="#9467bd"
+        title=dict(
+            text="yaxis4 title",
+            font=dict(
+                color="#9467bd"
+            )
         ),
         tickfont=dict(
             color="#9467bd"

doc/python/network-graphs.md

@@ -98,9 +98,11 @@ node_trace = go.Scatter(
         size=10,
         colorbar=dict(
             thickness=15,
-            title='Node Connections',
+            title=dict(
+              text='Node Connections',
+              side='right'
+            ),
             xanchor='left',
-            titleside='right'
         ),
         line_width=2))
 
@@ -128,8 +130,12 @@ node_trace.text = node_text
 ```python
 fig = go.Figure(data=[edge_trace, node_trace],
              layout=go.Layout(
-                title='<br>Network graph made with Python',
-                titlefont_size=16,
+                title=dict(
+                    text="<br>Network graph made with Python",
+                    font=dict(
+                        size=16
+                    )
+                ),
                 showlegend=False,
                 hovermode='closest',
                 margin=dict(b=20,l=5,r=5,t=40),