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Merge branch 'master' into create_updating_figures
# Conflicts: # notebooks/user-guide.md
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‎.github/pull_request_template.md

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Doc upgrade checklist:
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- [ ] old boilerplate at top and bottom of file has been removed
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- [ ] Every example is independently runnable and is optimized for short line count
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- [ ] no more `plot()` or `iplot()`
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- [ ] `graph_objs` has been renamed to `graph_objects`
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- [ ] `fig = <something>` call is high up in each example
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- [ ] minimal creation of intermediate `trace` objects
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- [ ] liberal use of `add_trace` and `update_layout`
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- [ ] `fig.show()` at the end of each example
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- [ ] `px` example at the top if appropriate
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- [ ] `v4upgrade: true` metadata added
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- [ ] minimize usage of hex codes for colors in favour of those in https://github.com/plotly/plotly.py-docs/issues/14

‎notebooks/1d-correlation.md

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format_name: markdown
@@ -164,4 +165,4 @@ publisher.publish(
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```python
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```
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```

‎notebooks/2D-Histogram.md

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### 2D Histogram with Slider Control ###
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Add slider controls to 2d histograms with the [postMessage API](https://github.com/plotly/postMessage-API).
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See the [code on JSFiddle](https://jsfiddle.net/plotlygraphs/y9sdy76h/4/).
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Watch [the 5 second video](https://raw.githubusercontent.com/plotly/documentation/gh-pages/all_static/images
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/flight_conflicts.gif) of how it works.
48+
Add slider controls to 2d histograms with the [postMessage API](https://github.com/plotly/postMessage-API).
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See the [code on JSFiddle](https://jsfiddle.net/plotlygraphs/y9sdy76h/4/).
50+
Watch [the 5 second video](https://raw.githubusercontent.com/plotly/documentation/gh-pages/all_static/images
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/flight_conflicts.gif) of how it works.
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```python
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from IPython.core.display import display,HTML
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'How to make 2D Histograms in Python with Plotly.',
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title = 'Python 2D Histograms | plotly',
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name = '2D Histograms',
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has_thumbnail='true', thumbnail='thumbnail/histogram2d.jpg',
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has_thumbnail='true', thumbnail='thumbnail/histogram2d.jpg',
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language='python', display_as='statistical', order=6,
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ipynb= '~notebook_demo/24')
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ipynb= '~notebook_demo/24')
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```
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```python
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```
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```

‎notebooks/2d-histogram-contour.md

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@@ -108,7 +109,7 @@ trace = [go.Histogram2dContour(
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color = 'black'
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)
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)
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)]
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py.iplot(trace, filename = "Histogram2dContour Styled")
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'histogram2dcontour.ipynb', 'python/2d-histogram-contour/', '2D Histogram Contour',
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'How to make 2D Histogram Contour plots in Python with Plotly.',
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title = '2D Histogram Contour | Plotly',
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has_thumbnail='true', thumbnail='thumbnail/hist2dcontour.png',
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language='python',
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has_thumbnail='true', thumbnail='thumbnail/hist2dcontour.png',
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language='python',
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# page_type='example_index', // note this is only if you want the tutorial to appear on the main page: plot.ly/python
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display_as='statistical',
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order=30,
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display_as='statistical',
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order=30,
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ipynb='~notebook_demo/199',
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uses_plotly_offline=False)
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```
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```python
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```
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```

‎notebooks/2d-projection-of-3d-surface.md

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```python
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axis = dict(
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showbackground=True,
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backgroundcolor="rgb(230, 230,230)",
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showgrid=False,
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zeroline=False,
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showbackground=True,
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backgroundcolor="rgb(230, 230,230)",
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showgrid=False,
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zeroline=False,
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showline=False)
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ztickvals=list(range(-6,4))
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layout = go.Layout(title="Projections of a surface onto coordinate planes" ,
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layout = go.Layout(title="Projections of a surface onto coordinate planes" ,
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autosize=False,
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width=700,
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height=600,
@@ -127,8 +128,8 @@ y_offset=np.min(yy)*np.ones(z.shape)
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```
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Define the color functions and the color numpy arrays, `C_z`, `C_x`, `C_y`, corresponding to each plane:<br>
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Define the 3-tuples of coordinates to be displayed at hovering the mouse over the projections.
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The first two coordinates give the position in the projection plane, whereas the third one is used
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Define the 3-tuples of coordinates to be displayed at hovering the mouse over the projections.
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The first two coordinates give the position in the projection plane, whereas the third one is used
132133
for assigning the color, just in the same way the coordinate z is used for the z-direction projection.
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```python
@@ -142,7 +143,7 @@ colorsurfy=proj_z(x,y,z)
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textx=[['y: '+'{:0.5f}'.format(y[i][j])+'<br>z: '+'{:0.5f}'.format(z[i][j])+
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'<br>x: '+'{:0.5f}'.format(x[i][j]) for j in range(z.shape[1])] for i in range(z.shape[0])]
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texty=[['x: '+'{:0.5f}'.format(x[i][j])+'<br>z: '+'{:0.5f}'.format(z[i][j]) +
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'<br>y: '+'{:0.5f}'.format(y[i][j]) for j in range(z.shape[1])] for i in range(z.shape[0])]
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'<br>y: '+'{:0.5f}'.format(y[i][j]) for j in range(z.shape[1])] for i in range(z.shape[0])]
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tracex = go.Surface(z=list(z),
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x=list(x_offset),
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'Plotly-project-3d-onto-a-plane.ipynb', 'python/2d-projection-of-3d-surface/', 'Projection of 3D Surface',
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'How to project 3D Surface plots in 2D with Plotly.',
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title = '2D Projection of 3D surface | plotly',
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has_thumbnail='true', thumbnail='thumbnail/projection-3d.jpg',
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has_thumbnail='true', thumbnail='thumbnail/projection-3d.jpg',
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language='python',
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display_as='3d_charts', order=19,
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ipynb= '~notebook_demo/79')
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```
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```
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```

‎notebooks/3d-bubble-charts.md

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sizeref = 750, # info on sizeref: https://plot.ly/python/reference/#scatter-marker-sizeref
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size = planet_diameter,
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color = planet_colors,
99-
)
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)
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data=[trace1]
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@@ -143,7 +144,7 @@ trace1 = go.Scatter3d(
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color = temperatures,
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colorbar = dict(title = 'Mean<br>Temperature'),
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colorscale=[[0, 'rgb(5, 10, 172)'], [.3, 'rgb(255, 255, 255)'], [1, 'rgb(178, 10, 28)']]
146-
)
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)
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)
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data=[trace1]
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! pip install git+https://github.com/plotly/publisher.git --upgrade
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import publisher
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publisher.publish(
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'3dbubble.ipynb', 'python/3d-bubble-charts/', 'Python 3D Bubble Charts',
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'How to make 3D Bubble Charts in Python with Plotly. '
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'Three examples of 3D Bubble Charts.',
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title = 'Python 3D Bubble Charts | plotly',
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name = '3D Bubble Charts',
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has_thumbnail='true', thumbnail='thumbnail/3dbubble.jpg',
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has_thumbnail='true', thumbnail='thumbnail/3dbubble.jpg',
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language='python', display_as='3d_charts', order=2,
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ipynb= '~notebook_demo/62')
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‎notebooks/3d-camera-controls.md

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The center vector determines the translation about the center of the scene. By default, there is no translation: the center vector is $(x=0, y=0, z=0)$.
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82-
The eye vector determines the camera view point about the origin. The default is $(x=1.25, y=1.25, z=1.25)$.
83+
The eye vector determines the camera view point about the origin. The default is $(x=1.25, y=1.25, z=1.25)$.
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<!-- #endregion -->
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```python deletable=true editable=true
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'How to Control the Camera in your 3D Charts in Python with Plotly.',
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language='python',
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‎notebooks/3d-filled-line-plots.md

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‎notebooks/3d-isosurface-plots.md

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'isosurfaces.ipynb', 'python/3d-isosurface-plots/', 'Iso Surface',
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'How to make 3D Isosurface Plots in Python with Plotly.',
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ipynb= '~notebook_demo/272')
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‎notebooks/3d-line-plots.md

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publisher.publish(
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'3d-line.ipynb', 'python/3d-line-plots/', 'Python 3D Line Plots | plotly',
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'How to make 3D Line Plots',
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‎notebooks/3d-network-graph.md

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92-
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93+
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9394
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`layt` is a list of three elements lists (the coordinates of nodes):
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for e in Edges:
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Xe+=[layt[e[0]][0],layt[e[1]][0], None]# x-coordinates of edge ends
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Ye+=[layt[e[0]][1],layt[e[1]][1], None]
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Ye+=[layt[e[0]][1],layt[e[1]][1], None]
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'How to make 3D Network Graphs in Python. ',
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title = '3D Network Graphs in Python | plotly',
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name = '3D Network Graphs',
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