tweaks

nicolaskruchten · nicolaskruchten · commit d2e7667b78cf · 2020-07-20T10:18:29.000-04:00
diff --git a/doc/python/3d-surface-coloring.md b/doc/python/3d-surface-coloring.md
diff --git a/doc/python/3d-surface-plots.md b/doc/python/3d-surface-plots.md
@@ -30,6 +30,7 @@ jupyter:
     order: 3
     page_type: example_index
     permalink: python/3d-surface-plots/
+    redirect_from: python/3d-surface-coloring/
     thumbnail: thumbnail/3d-surface.jpg
 ---
 
@@ -54,7 +55,7 @@ fig.show()
 
 ### Passing x and y data to 3D Surface Plot
 
-If you do not specify `x` and `y` coordinates, integer indices are used for the `x` and `y` axis. You can also pass `x` and `y` values to `go.Surface`. 
+If you do not specify `x` and `y` coordinates, integer indices are used for the `x` and `y` axis. You can also pass `x` and `y` values to `go.Surface`.
 
 ```python
 import plotly.graph_objects as go
@@ -98,7 +99,7 @@ fig.update_layout(title='Mt Bruno Elevation', autosize=False,
 fig.show()
 ```
 #### Configure Surface Contour Levels
-This example shows how to slice the surface graph on the desired position for each of x, y and z axis. [contours.x.start](https://plotly.com/python/reference/#surface-contours-x-start) sets the starting contour level value, `end` sets the end of it, and `size` sets the step between each contour level. 
+This example shows how to slice the surface graph on the desired position for each of x, y and z axis. [contours.x.start](https://plotly.com/python/reference/#surface-contours-x-start) sets the starting contour level value, `end` sets the end of it, and `size` sets the step between each contour level.
 
 ```python
 import plotly.graph_objects as go
@@ -165,18 +166,34 @@ fig.show()
 
 ### Setting the Surface Color
 
-You can use the `surfacecolor` attribute to define the color of the surface of your figure. In this example, the surface color is drawn relation to the x-axis data. 
+You can use the `surfacecolor` attribute to define the color of the surface of your figure. In this example, the surface color represents the distance from the origin, rather than the default, which is the `z` value.
 
 ```python
 import plotly.graph_objects as go
+from plotly.subplots import make_subplots
+
+# Equation of ring cyclide
+# see https://en.wikipedia.org/wiki/Dupin_cyclide
 import numpy as np
-x, y = 4 * np.pi * np.mgrid[0:1:20j, 0:1:20j]
-z = np.sin(x)
-fig = go.Figure(go.Surface(x=x, y=y, z=z, surfacecolor=x))
+a, b, d = 1.32, 1., 0.8
+c = a**2 - b**2
+u, v = np.mgrid[0:2*np.pi:100j, 0:2*np.pi:100j]
+x = (d * (c - a * np.cos(u) * np.cos(v)) + b**2 * np.cos(u)) / (a - c * np.cos(u) * np.cos(v))
+y = b * np.sin(u) * (a - d*np.cos(v)) / (a - c * np.cos(u) * np.cos(v))
+z = b * np.sin(v) * (c*np.cos(u) - d) / (a - c * np.cos(u) * np.cos(v))
+
+fig = make_subplots(rows=1, cols=2,
+                    specs=[[{'is_3d': True}, {'is_3d': True}]],
+                    subplot_titles=['Color corresponds to z', 'Color corresponds to distance to origin'],
+                    )
+
+fig.add_trace(go.Surface(x=x, y=y, z=z, colorbar_x=-0.07), 1, 1)
+fig.add_trace(go.Surface(x=x, y=y, z=z, surfacecolor=x**2 + y**2 + z**2), 1, 2)
+fig.update_layout(title_text="Ring cyclide")
 fig.show()
 ```
 
 #### Reference
 
 
-See https://plotly.com/python/reference/#surface for more information!
+See https://plotly.com/python/reference/#surface for more information!
diff --git a/doc/python/box-plots.md b/doc/python/box-plots.md
@@ -491,6 +491,8 @@ fig.show()
 
 ### Box Plot With Only Points
 
+A [strip chart](/python/strip-charts/) is like a box plot with points showing, and no box:
+
 ```python
 import plotly.express as px
 df = px.data.tips()
@@ -500,4 +502,4 @@ fig.show()
 
 #### Reference
 
-See https://plotly.com/python/reference/#box for more information and chart attribute options!
+See https://plotly.com/python/reference/#box for more information and chart attribute options!
diff --git a/doc/python/line-and-scatter.md b/doc/python/line-and-scatter.md
@@ -274,25 +274,6 @@ fig = go.Figure(data=go.Scattergl(
 fig.show()
 ```
 
-### Sparklines With go.Scatter
-
-Sparklines are scatter plots inside subplots, with gridlines, axis lines, and ticks removed. 
-
-```python
-import plotly.express as px
-from plotly.subplots import make_subplots
-df = px.data.gapminder()
-fig = make_subplots(2, 1)
-df1 = df.query("country == 'Canada'")
-fig.add_trace(go.Scatter(x=df1['year'], y=df1['gdpPercap'], mode='lines', name='Canada'), 1, 1)
-df2 = df.query("country == 'France'")
-fig.add_trace(go.Scatter(x=df2['year'], y=df2['gdpPercap'], mode='lines', name='France'), 2, 1)
-fig.update_layout(template=None, height=400)
-fig.update_xaxes(showgrid=False)
-fig.update_yaxes(showgrid=False)
-fig.show()
-```
-
 ### Reference
 
 See https://plotly.com/python/reference/#scatter or https://plotly.com/python/reference/#scattergl for more information and chart attribute options!
diff --git a/doc/python/line-charts.md b/doc/python/line-charts.md
@@ -71,16 +71,29 @@ fig.show()
 
 ### Sparklines with Plotly Express
 
-Sparklines are scatter plots inside subplots, with gridlines, axis lines, and ticks removed. 
+Sparklines are scatter plots inside subplots, with gridlines, axis lines, and ticks removed.
 
 ```python
 import plotly.express as px
-df = px.data.gapminder().query("continent == 'Oceania'")
-fig = px.line(df, x='year', y='gdpPercap', facet_row='country')
-fig.update_layout(template=None, height=400)
-fig.update_xaxes(showgrid=False)
-fig.update_yaxes(showgrid=False)
-fig.show()
+df = px.data.stocks(indexed=True)
+fig = px.line(df, facet_row="company", facet_row_spacing=0.01, height=200, width=200)
+
+# hide and lock down axes
+fig.update_xaxes(visible=False, fixedrange=True)
+fig.update_yaxes(visible=False, fixedrange=True)
+
+# remove facet/subplot labels
+fig.update_layout(annotations=[], overwrite=True)
+
+# strip down the rest of the plot
+fig.update_layout(
+    showlegend=False,
+    plot_bgcolor="white",
+    margin=dict(t=10,l=10,b=10,r=10)
+)
+
+# disable the modebar for such a small plot
+fig.show(config=dict(displayModeBar=False))
 ```
 
 ### Line Plot with go.Scatter
@@ -421,4 +434,4 @@ fig.show()
 
 #### Reference
 
-See https://plotly.com/python/reference/#scatter for more information and chart attribute options!
+See https://plotly.com/python/reference/#scatter for more information and chart attribute options!
diff --git a/doc/python/sliders.md b/doc/python/sliders.md
@@ -34,7 +34,7 @@ jupyter:
 ---
 
 ### Simple Slider Control
-Sliders can be used in Plotly to change the data displayed or style of a plot. 
+Sliders can be used in Plotly to change the data displayed or style of a plot.
 
 ```python
 import plotly.graph_objects as go
@@ -83,61 +83,14 @@ fig.show()
 
 #### Methods
 The method determines which [plotly.js function](https://plot.ly/javascript/plotlyjs-function-reference/) will be used to update the chart. Plotly can use several [updatemenu](https://plot.ly/python/reference/#layout-updatemenus-items-updatemenu-buttons-items-button-method) methods to add the slider:
+- `"update"`: modify **data and layout** attributes (as above)
 - `"restyle"`: modify **data** attributes
 - `"relayout"`: modify **layout** attributes
-- `"update"`: modify **data and layout** attributes
 - `"animate"`: start or pause an animation
 
-### Update Slider
-```python
-import plotly.graph_objects as go
-import numpy as np
-
-# Create figure
-fig = go.Figure()
-
-# Add traces, one for each slider step
-for step in np.arange(0, 5, 0.1):
-    fig.add_trace(
-        go.Scatter(
-            visible=False,
-            line=dict(color="#00CED1", width=6),
-            name="𝜈 = " + str(step),
-            x=np.arange(0, 10, 0.01),
-            y=np.sin(step * np.arange(0, 10, 0.01))))
-
-# Make 10th trace visible
-fig.data[10].visible = True
-
-# Create and add slider
-steps = []
-for i in range(len(fig.data)):
-    step = dict(
-        method="update",
-        args=[{"visible":[False] * len(fig.data)}, # update for traces
-               {"title":str(i)} # update for layout 
-             ],
-    )
-    step["args"][0]["visible"][i] = True  # Toggle i'th trace to "visible"
-    steps.append(step)
-
-sliders = [dict(
-    active=10,
-    currentvalue={"prefix": "Frequency: "},
-    pad={"t": 50},
-    steps=steps
-)]
-
-fig.update_layout(
-    sliders=sliders
-)
-
-fig.show()
-```
-
 
 ### Sliders in Plotly Express
-Plotly Express provide sliders, but with implicit animation. The animation can be ommited by removing `updatemenus` in the `layout`:
+Plotly Express provide sliders, but with implicit animation using the `"animate"` method described above. The animation play button can be ommited by removing `updatemenus` in the `layout`:
 
 ```python
 import plotly.express as px
diff --git a/doc/python/violin.md b/doc/python/violin.md
@@ -262,7 +262,14 @@ fig.show()
 
 ### Violin Plot With Only Points
 
-See https://plotly.com/python/box-plots/#box-plot-with-only-points.
+A [strip chart](/python/strip-charts/) is like a violin plot with points showing, and no violin:
+
+```python
+import plotly.express as px
+df = px.data.tips()
+fig = px.strip(df, x='day', y='tip')
+fig.show()
+```
 
 #### Reference
 
