Skip to content

change .ly to .com #2312

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 2 commits into from
Mar 26, 2020
Merged

change .ly to .com #2312

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
18f61ef
change .ly to .com
Mar 25, 2020
abda92c
Merge branch 'doc-prod' into ly-to-com
Mar 26, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 2 additions & 2 deletions doc/python/2D-Histogram.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -71,7 +71,7 @@ fig = go.Figure(go.Histogram2d(x=x, y=y, histnorm='probability',
fig.show()
```
### Sharing bin settings between 2D Histograms
This example shows how to use [bingroup](https://plot.ly/python/reference/#histogram-bingroup) attribute to have a compatible bin settings for both histograms. To define `start`, `end` and `size` value of x-axis and y-axis seperatly, set [ybins](https://plot.ly/python/reference/#histogram2dcontour-ybins) and `xbins`.
This example shows how to use [bingroup](https://plotly.com/python/reference/#histogram-bingroup) attribute to have a compatible bin settings for both histograms. To define `start`, `end` and `size` value of x-axis and y-axis seperatly, set [ybins](https://plotly.com/python/reference/#histogram2dcontour-ybins) and `xbins`.

```python
import plotly.graph_objects as go
Expand Down Expand Up @@ -170,4 +170,4 @@ fig.show()
```

#### Reference
See https://plot.ly/python/reference/#histogram2d for more information and chart attribute options!
See https://plotly.com/python/reference/#histogram2d for more information and chart attribute options!
2 changes: 1 addition & 1 deletion doc/python/2d-histogram-contour.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -185,4 +185,4 @@ fig.show()
```

#### Reference
See https://plot.ly/python/reference/#histogram2dcontour for more information and chart attribute options!
See https://plotly.com/python/reference/#histogram2dcontour for more information and chart attribute options!
2 changes: 1 addition & 1 deletion doc/python/3d-axes.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -39,7 +39,7 @@ jupyter:
attributes such as `xaxis`, `yaxis` and `zaxis` parameters, in order to
set the range, title, ticks, color etc. of the axes.

For creating 3D charts, see [this page](https://plot.ly/python/3d-charts/).
For creating 3D charts, see [this page](https://plotly.com/python/3d-charts/).

```python
import plotly.graph_objects as go
Expand Down
6 changes: 3 additions & 3 deletions doc/python/3d-bubble-charts.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -108,7 +108,7 @@ fig = go.Figure(data=go.Scatter3d(
mode = 'markers',
marker = dict(
sizemode = 'diameter',
sizeref = 750, # info on sizeref: https://plot.ly/python/reference/#scatter-marker-sizeref
sizeref = 750, # info on sizeref: https://plotly.com/python/reference/#scatter-marker-sizeref
size = planet_diameter,
color = planet_colors,
)
Expand Down Expand Up @@ -147,7 +147,7 @@ fig = go.Figure(go.Scatter3d(
mode = 'markers',
marker = dict(
sizemode = 'diameter',
sizeref = 750, # info on sizeref: https://plot.ly/python/reference/#scatter-marker-sizeref
sizeref = 750, # info on sizeref: https://plotly.com/python/reference/#scatter-marker-sizeref
size = planet_diameter,
color = temperatures,
colorbar_title = 'Mean<br>Temperature',
Expand All @@ -167,4 +167,4 @@ fig.show()

#### Reference

See https://plot.ly/python/reference/#scatter3d and https://plot.ly/python/reference/#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-marker-sizeref <br>for more information and chart attribute options!
2 changes: 1 addition & 1 deletion doc/python/3d-camera-controls.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -290,4 +290,4 @@ fig.show()
#### Reference


See https://plot.ly/python/reference/#layout-scene-camera for more information and chart attribute options!
See https://plotly.com/python/reference/#layout-scene-camera for more information and chart attribute options!
2 changes: 1 addition & 1 deletion doc/python/3d-isosurface-plots.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -235,5 +235,5 @@ fig.show()
```

#### Reference
See https://plot.ly/python/reference/#isosurface for more information and chart attribute options!
See https://plotly.com/python/reference/#isosurface for more information and chart attribute options!

2 changes: 1 addition & 1 deletion doc/python/3d-line-plots.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -120,4 +120,4 @@ fig.show()

#### Reference

See https://plot.ly/python/reference/#scatter3d-marker-line for more information and chart attribute options!
See https://plotly.com/python/reference/#scatter3d-marker-line for more information and chart attribute options!
2 changes: 1 addition & 1 deletion doc/python/3d-mesh.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -163,4 +163,4 @@ fig.show()
```

## Reference
See https://plot.ly/python/reference/#mesh3d for more information and chart attribute options!
See https://plotly.com/python/reference/#mesh3d for more information and chart attribute options!
8 changes: 4 additions & 4 deletions doc/python/3d-scatter-plots.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -37,7 +37,7 @@ jupyter:

[Plotly Express](/python/plotly-express/) is the easy-to-use, high-level interface to Plotly, which [operates on "tidy" data](/python/px-arguments/) and produces [easy-to-style figures](/python/styling-plotly-express/).

Like the [2D scatter plot](https://plot.ly/python/line-and-scatter/) `px.scatter`, the 3D function `px.scatter_3d` plots individual data in three-dimensional space.
Like the [2D scatter plot](https://plotly.com/python/line-and-scatter/) `px.scatter`, the 3D function `px.scatter_3d` plots individual data in three-dimensional space.

```python
import plotly.express as px
Expand Down Expand Up @@ -77,7 +77,7 @@ fig.update_layout(margin=dict(l=0, r=0, b=0, t=0))
#### Basic 3D Scatter Plot

If Plotly Express does not provide a good starting point, it is also possible to use the more generic `go.Scatter3D` from `plotly.graph_objs`.
Like the [2D scatter plot](https://plot.ly/python/line-and-scatter/) `go.Scatter`, `go.Scatter3d` plots individual data in three-dimensional space.
Like the [2D scatter plot](https://plotly.com/python/line-and-scatter/) `go.Scatter`, `go.Scatter3d` plots individual data in three-dimensional space.

```python
import plotly.graph_objects as go
Expand Down Expand Up @@ -122,7 +122,7 @@ fig.show()

### Dash App

[Dash](https://plot.ly/products/dash/) is an Open Source Python library which can help you convert plotly figures into a reactive, web-based application. Below is a simple example of a dashboard created using Dash. Its [source code](https://github.com/plotly/simple-example-chart-apps/tree/master/dash-3dscatterplot) can easily be deployed to a PaaS.
[Dash](https://plotly.com/products/dash/) is an Open Source Python library which can help you convert plotly figures into a reactive, web-based application. Below is a simple example of a dashboard created using Dash. Its [source code](https://github.com/plotly/simple-example-chart-apps/tree/master/dash-3dscatterplot) can easily be deployed to a PaaS.

```python
from IPython.display import IFrame
Expand All @@ -136,4 +136,4 @@ IFrame(src= "https://dash-simple-apps.plotly.host/dash-3dscatterplot/code", widt

#### Reference

See https://plot.ly/python/reference/#scatter3d for more information and chart attribute options!
See https://plotly.com/python/reference/#scatter3d for more information and chart attribute options!
2 changes: 1 addition & 1 deletion doc/python/3d-subplots.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -82,4 +82,4 @@ fig.show()
#### Reference


See https://plot.ly/python/subplots/ for more information regarding subplots!
See https://plotly.com/python/subplots/ for more information regarding subplots!
2 changes: 1 addition & 1 deletion doc/python/3d-surface-coloring.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -60,5 +60,5 @@ fig.show()
#### Reference


See https://plot.ly/python/reference/#surface-surfacecolor for more information!
See https://plotly.com/python/reference/#surface-surfacecolor for more information!

6 changes: 3 additions & 3 deletions doc/python/3d-surface-plots.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -76,7 +76,7 @@ fig.show()
#### Surface Plot With Contours


Display and customize contour data for each axis using the `contours` attribute ([reference](plot.ly/python/reference/#surface-contours)).
Display and customize contour data for each axis using the `contours` attribute ([reference](plotly.com/python/reference/#surface-contours)).

```python
import plotly.graph_objects as go
Expand All @@ -98,7 +98,7 @@ 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://plot.ly/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
Expand Down Expand Up @@ -166,4 +166,4 @@ fig.show()
#### Reference


See https://plot.ly/python/reference/#surface for more information!
See https://plotly.com/python/reference/#surface for more information!
4 changes: 2 additions & 2 deletions doc/python/3d-volume.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -190,7 +190,7 @@ fig = go.Figure(data=go.Volume(
))

# Change camera view for a better view of the sides, XZ plane
# (see https://plot.ly/python/v3/3d-camera-controls/)
# (see https://plotly.com/python/v3/3d-camera-controls/)
fig.update_layout(scene_camera = dict(
up=dict(x=0, y=0, z=1),
center=dict(x=0, y=0, z=0),
Expand Down Expand Up @@ -254,7 +254,7 @@ fig.show()
```

#### Reference
See https://plot.ly/python/reference/#volume for more information and chart attribute options!
See https://plotly.com/python/reference/#volume for more information and chart attribute options!

#### See also
[3D isosurface documentation](/python/3d-isosurface-plots/)
4 changes: 2 additions & 2 deletions doc/python/aggregations.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -142,7 +142,7 @@ import plotly.io as pio

import pandas as pd

df = pd.read_csv("https://plot.ly/~public.health/17.csv")
df = pd.read_csv("https://plotly.com/~public.health/17.csv")

data = [dict(
x = df['date'],
Expand Down Expand Up @@ -270,4 +270,4 @@ pio.show(fig_dict, validate=False)
```

#### Reference
See https://plot.ly/python/reference/ for more information and chart attribute options!
See https://plotly.com/python/reference/ for more information and chart attribute options!
6 changes: 3 additions & 3 deletions doc/python/animations.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -63,7 +63,7 @@ Along with `data` and `layout`, `frames` can be added as a key in a figure objec

#### Adding Control Buttons to Animations

You can add play and pause buttons to control your animated charts by adding an `updatemenus` array to the `layout` of your `figure`. More information on style and placement of the buttons is available in Plotly's [`updatemenus` reference](https://plot.ly/python/reference/#layout-updatemenus).
You can add play and pause buttons to control your animated charts by adding an `updatemenus` array to the `layout` of your `figure`. More information on style and placement of the buttons is available in Plotly's [`updatemenus` reference](https://plotly.com/python/reference/#layout-updatemenus).
<br>
The buttons are defined as follows:

Expand Down Expand Up @@ -389,5 +389,5 @@ fig.show()

#### Reference

For additional information and attributes for creating bubble charts in Plotly see: https://plot.ly/python/bubble-charts/.
For more documentation on creating animations with Plotly, see https://plot.ly/python/#animations.
For additional information and attributes for creating bubble charts in Plotly see: https://plotly.com/python/bubble-charts/.
For more documentation on creating animations with Plotly, see https://plotly.com/python/#animations.
2 changes: 1 addition & 1 deletion doc/python/annotated-heatmap.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -202,7 +202,7 @@ fig.show()
```

#### Reference
For more info on Plotly heatmaps, see: https://plot.ly/python/reference/#heatmap.<br> For more info on using colorscales with Plotly see: https://plot.ly/python/heatmap-and-contour-colorscales/ <br>For more info on annotated_heatmaps, see:
For more info on Plotly heatmaps, see: https://plotly.com/python/reference/#heatmap.<br> For more info on using colorscales with Plotly see: https://plotly.com/python/heatmap-and-contour-colorscales/ <br>For more info on annotated_heatmaps, see:

```python
help(ff.create_annotated_heatmap)
Expand Down
6 changes: 3 additions & 3 deletions doc/python/axes.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -477,7 +477,7 @@ fig.show()

### Set axis title position

This example sets `standoff` attribute to cartesian axes to determine the distance between the tick labels and the axis title. Note that the axis title position is always constrained within the margins, so the actual standoff distance is always less than the set or default value. By default [automargin](https://plot.ly/python/setting-graph-size/#automatically-adjust-margins) is `True` in Plotly template for the cartesian axis, so the margins will be pushed to fit the axis title at given standoff distance.
This example sets `standoff` attribute to cartesian axes to determine the distance between the tick labels and the axis title. Note that the axis title position is always constrained within the margins, so the actual standoff distance is always less than the set or default value. By default [automargin](https://plotly.com/python/setting-graph-size/#automatically-adjust-margins) is `True` in Plotly template for the cartesian axis, so the margins will be pushed to fit the axis title at given standoff distance.

```python
import plotly.graph_objects as go
Expand Down Expand Up @@ -743,7 +743,7 @@ fig.show()

#### Synchronizing axes in subplots with `matches`

Using `facet_col` from `plotly.express` let [zoom](https://help.plot.ly/zoom-pan-hover-controls/#step-3-zoom-in-and-zoom-out-autoscale-the-plot) and [pan](https://help.plot.ly/zoom-pan-hover-controls/#step-6-pan-along-axes) each facet to the same range implicitly. However, if the subplots are created with `make_subplots`, the axis needs to be updated with `matches` parameter to update all the subplots accordingly.
Using `facet_col` from `plotly.express` let [zoom](https://help.plotly.com/zoom-pan-hover-controls/#step-3-zoom-in-and-zoom-out-autoscale-the-plot) and [pan](https://help.plotly.com/zoom-pan-hover-controls/#step-6-pan-along-axes) each facet to the same range implicitly. However, if the subplots are created with `make_subplots`, the axis needs to be updated with `matches` parameter to update all the subplots accordingly.

Zoom in one trace below, to see the other subplots zoomed to the same x-axis range. To pan all the subplots, click and drag from the center of x-axis to the side:

Expand All @@ -764,4 +764,4 @@ fig.show()

#### Reference

See https://plot.ly/python/reference/#layout-xaxis and https://plot.ly/python/reference/#layout-yaxis for more information and chart attribute options!
See https://plotly.com/python/reference/#layout-xaxis and https://plotly.com/python/reference/#layout-yaxis for more information and chart attribute options!
6 changes: 3 additions & 3 deletions doc/python/bar-charts.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -336,7 +336,7 @@ fig.show()

### Bar Chart with Sorted or Ordered Categories

Set `categoryorder` to `"category ascending"` or `"category descending"` for the alphanumerical order of the category names or `"total ascending"` or `"total descending"` for numerical order of values. [categoryorder](https://plot.ly/python/reference/#layout-xaxis-categoryorder) for more information. Note that sorting the bars by a particular trace isn't possible right now - it's only possible to sort by the total values. Of course, you can always sort your data _before_ plotting it if you need more customization.
Set `categoryorder` to `"category ascending"` or `"category descending"` for the alphanumerical order of the category names or `"total ascending"` or `"total descending"` for numerical order of values. [categoryorder](https://plotly.com/python/reference/#layout-xaxis-categoryorder) for more information. Note that sorting the bars by a particular trace isn't possible right now - it's only possible to sort by the total values. Of course, you can always sort your data _before_ plotting it if you need more customization.

This example orders the bar chart alphabetically with `categoryorder: 'category ascending'`

Expand Down Expand Up @@ -382,8 +382,8 @@ fig.show()

### Horizontal Bar Charts

See examples of horizontal bar charts [here](https://plot.ly/python/horizontal-bar-charts/).
See examples of horizontal bar charts [here](https://plotly.com/python/horizontal-bar-charts/).

### Reference

See https://plot.ly/python/reference/#bar for more information and chart attribute options!
See https://plotly.com/python/reference/#bar for more information and chart attribute options!
6 changes: 3 additions & 3 deletions doc/python/box-plots.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -36,7 +36,7 @@ jupyter:
thumbnail: thumbnail/box.jpg
---

A [box plot](https://en.wikipedia.org/wiki/Box_plot) is a statistical representation of numerical data through their quartiles. The ends of the box represent the lower and upper quartiles, while the median (second quartile) is marked by a line inside the box. For other statistical representations of numerical data, see [other statistical charts](https://plot.ly/python/statistical-charts/).
A [box plot](https://en.wikipedia.org/wiki/Box_plot) is a statistical representation of numerical data through their quartiles. The ends of the box represent the lower and upper quartiles, while the median (second quartile) is marked by a line inside the box. For other statistical representations of numerical data, see [other statistical charts](https://plotly.com/python/statistical-charts/).

## Box Plot with `plotly.express`

Expand Down Expand Up @@ -134,7 +134,7 @@ fig.show()

## Box plot with go.Box

If Plotly Express does not provide a good starting point, it is also possible to use the more generic `go.Box` function from `plotly.graph_objects`. All available options for `go.Box` are described in the reference page https://plot.ly/python/reference/#box.
If Plotly Express does not provide a good starting point, it is also possible to use the more generic `go.Box` function from `plotly.graph_objects`. All available options for `go.Box` are described in the reference page https://plotly.com/python/reference/#box.

### Basic Box Plot

Expand Down Expand Up @@ -491,4 +491,4 @@ fig.show()

#### Reference

See https://plot.ly/python/reference/#box for more information and chart attribute options!
See https://plotly.com/python/reference/#box for more information and chart attribute options!
10 changes: 5 additions & 5 deletions doc/python/bubble-charts.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -36,7 +36,7 @@ jupyter:

## Bubble chart with plotly.express

A [bubble chart](https://en.wikipedia.org/wiki/Bubble_chart) is a scatter plot in which a third dimension of the data is shown through the size of markers. For other types of scatter plot, see the [line and scatter page](https://plot.ly/python/line-and-scatter/).
A [bubble chart](https://en.wikipedia.org/wiki/Bubble_chart) is a scatter plot in which a third dimension of the data is shown through the size of markers. For other types of scatter plot, see the [line and scatter page](https://plotly.com/python/line-and-scatter/).

We first show a bubble chart example using Plotly Express. [Plotly Express](/python/plotly-express/) is the easy-to-use, high-level interface to Plotly, which [operates on "tidy" data](/python/px-arguments/) and produces [easy-to-style figures](/python/styling-plotly-express/). The size of markers is set from the dataframe column given as the `size` parameter.

Expand All @@ -52,7 +52,7 @@ fig.show()

## Bubble Chart with plotly.graph_objects

If Plotly Express does not provide a good starting point, it is also possible to use the more generic `go.Scatter` from `plotly.graph_objects`, and define the size of markers to create a bubble chart. All of the available options are described in the scatter section of the reference page: https://plot.ly/python/reference#scatter.
If Plotly Express does not provide a good starting point, it is also possible to use the more generic `go.Scatter` from `plotly.graph_objects`, and define the size of markers to create a bubble chart. All of the available options are described in the scatter section of the reference page: https://plotly.com/python/reference#scatter.

### Simple Bubble Chart

Expand Down Expand Up @@ -91,8 +91,8 @@ fig.show()

To scale the bubble size, use the attribute `sizeref`. We recommend using the following formula to calculate a `sizeref` value:<br>
`sizeref = 2. * max(array of size values) / (desired maximum marker size ** 2)`<br>
Note that setting 'sizeref' to a value greater than 1, decreases the rendered marker sizes, while setting 'sizeref' to less than 1, increases the rendered marker sizes. See https://plot.ly/python/reference/#scatter-marker-sizeref for more information.
Additionally, we recommend setting the sizemode attribute: https://plot.ly/python/reference/#scatter-marker-sizemode to area.
Note that setting 'sizeref' to a value greater than 1, decreases the rendered marker sizes, while setting 'sizeref' to less than 1, increases the rendered marker sizes. See https://plotly.com/python/reference/#scatter-marker-sizeref for more information.
Additionally, we recommend setting the sizemode attribute: https://plotly.com/python/reference/#scatter-marker-sizemode to area.

```python
import plotly.graph_objects as go
Expand Down Expand Up @@ -222,4 +222,4 @@ fig.show()

### Reference

See https://plot.ly/python/reference/#scatter for more information and chart attribute options!
See https://plotly.com/python/reference/#scatter for more information and chart attribute options!
Loading