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document corrections
c-chaitanya Feb 17, 2021
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document corrections
c-chaitanya Feb 18, 2021
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Update imshow.md
c-chaitanya Feb 18, 2021
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18 changes: 9 additions & 9 deletions CHANGELOG.md
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Expand Up @@ -135,7 +135,7 @@ This project adheres to [Semantic Versioning](http://semver.org/).
faster image rendering and smaller figure size. Additional optional arguments
`binary_backend`, `binary_format` and `binary_compression_level` control
how to generate the b64 string ([#2691](https://github.com/plotly/plotly.py/pull/2691)
- `px.imshow` has a new `constrast_rescaling` argument in order to choose how
- `px.imshow` has a new `contrast_rescaling` argument in order to choose how
to set data values corresponding to the bounds of the color range
([#2691](https://github.com/plotly/plotly.py/pull/2691)

Expand Down Expand Up @@ -239,7 +239,7 @@ This project adheres to [Semantic Versioning](http://semver.org/).

### Added

- The `hover_data` parameter of `px` functions can now be a dictionary. This makes it possible to skip hover information for some arguments or to change the formatting of hover informatiom [#2377](https://github.com/plotly/plotly.py/pull/2377).
- The `hover_data` parameter of `px` functions can now be a dictionary. This makes it possible to skip hover information for some arguments or to change the formatting of hover information [#2377](https://github.com/plotly/plotly.py/pull/2377).
- It's now possible to build a development version of Plotly.py against the build artifacts from a non-`master` branch of Plotly.js, which makes for faster QA and development cycles [#2349](https://github.com/plotly/plotly.py/pull/2349). Thanks [@zouhairm](https://github.com/zouhairm) for this Pull Request!

### Fixed
Expand All @@ -252,7 +252,7 @@ This version includes several performance improvements ([#2368](https://github.c

- Child graph objects (e.g. `figure.layout.xaxis`) are no longer created eagerly during graph object construction. Instead, they are created lazily the first time the property is accessed.
- Property validation is now disabled for select internal operations.
- When used with Python 3.7 and above, ploty.py now takes advantage of [PEP-562](https://www.python.org/dev/peps/pep-0562/) to perform submodule imports lazily. This dramatically improves import times.
- When used with Python 3.7 and above, plotly.py now takes advantage of [PEP-562](https://www.python.org/dev/peps/pep-0562/) to perform submodule imports lazily. This dramatically improves import times.

## [4.6.0] - 2020-03-31

Expand Down Expand Up @@ -290,7 +290,7 @@ This version includes several performance improvements ([#2368](https://github.c

- Jupyterlab extension now compatible with both Jupyterlab 1.2 and 2.0 [#2261](https://github.com/plotly/plotly.py/pull/2261) with thanks to [@consideRatio](https://github.com/consideRatio) for the contribution!
- Fixed a bug when using boolean values for the color argument of px functions [#2127](https://github.com/plotly/plotly.py/pull/2127)
- Corrected import bug which was occuring with old versions of ipywidgets [#2265](https://github.com/plotly/plotly.py/pull/2265)
- Corrected import bug which was occurring with old versions of ipywidgets [#2265](https://github.com/plotly/plotly.py/pull/2265)
- Fixed python 3.8 syntax warning [#2262](https://github.com/plotly/plotly.py/pull/2262), with thanks to [@sgn](https://github.com/sgn) for the contribution!

## [4.5.3] - 2020-03-05
Expand Down Expand Up @@ -365,7 +365,7 @@ This version includes several performance improvements ([#2368](https://github.c
for more information
- The tutorials of the [plotly.py documentation](https://plot.ly/python/) are
now in the main [plotly.py Github repository](https://github.com/plotly/plotly.py). Contributions in order to improve or extend the documentation are very welcome!
- `plotly.express` generated plots no longer have a default height of 600 pixels, instead they inherit the default height of regular figures [#1990](https://github.com/plotly/plotly.py/pull/1990). To restore the old behavior, set `px.defaults.height=600` once per session, or set the `height` keyword arguement to any `px.function()` to 600.
- `plotly.express` generated plots no longer have a default height of 600 pixels, instead they inherit the default height of regular figures [#1990](https://github.com/plotly/plotly.py/pull/1990). To restore the old behavior, set `px.defaults.height=600` once per session, or set the `height` keyword argument to any `px.function()` to 600.

### Fixed

Expand Down Expand Up @@ -439,7 +439,7 @@ section [#1969](https://github.com/plotly/plotly.py/pull/1969).
- The width of a figure produced by the `create_gantt` figure factory now resizes responsively ([#1724](https://github.com/plotly/plotly.py/pull/1724))

### Fixed
- The name of the steps property of `graph_objects.indicator.Guage` has been renamed from `stepss` to `steps`
- The name of the steps property of `graph_objects.indicator.Gauge` has been renamed from `stepss` to `steps`
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I'm very impressed that the spell-checking finds this mistake but ignores the stepss on the same line! How does this work? Are you manually reviewing the changes before submitting the PRs?

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@c-chaitanya c-chaitanya Feb 18, 2021 •
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Appreciate the comments @nicolaskruchten. No advanced NLP used here, but very basic NLP stuff. Firstly I have a corpus of english words with me. In my second step I create a corpus from all the documents in the project (lets call this plotly corpus). Then I count all the words in the plotly corpus. Then I add all words in plotly corpus having word count greater than a fixed threshold to the english ones. This step ensures that the programming jargon is not counted as a spelling error.

Now all words which don't exist in the final corpus are treated as errors. If any document contains error words, my script just prints out the filename and the errored word. I go through this and fix them manually.

maybe the document contained the word stepss a lot of times. Thus it isnt treated as an error

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Interesting! stepss is definitely not anywhere else, or shouldn't be. Its inclusion in this line of the changelog is specifically to point out that we made a mistake and had to fix it ;)

Either way, thanks again for the contribution :)

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There is lot of manual work involved. I go through the present sentence understand the context and then read the correction suggestion and take my call.

- Avoid crash in iframe renderers when running outside iPython ([#1723](https://github.com/plotly/plotly.py/pull/1723))

## [4.1.0] - 2019-08-06
Expand Down Expand Up @@ -491,7 +491,7 @@ This is a major release that includes many new features, and a few breaking chan
- Added support for all trace types in `make_subplots` ([#1528](https://github.com/plotly/plotly.py/pull/1528))
- Added support for secondary y-axes in `make_subplots` ([#1564](https://github.com/plotly/plotly.py/pull/1564))
- Support passing a scalar trace object (rather than a list or tuple of trace objects) as the `data` property to the `Figure` constructor ([#1614](https://github.com/plotly/plotly.py/pull/1614))
- Added dictionary-stule `.pop` method to graph object classes ([#1614](https://github.com/plotly/plotly.py/pull/1614))
- Added dictionary-style `.pop` method to graph object classes ([#1614](https://github.com/plotly/plotly.py/pull/1614))
- New `jupyterlab-plotly` JupyterLab extension for rendering figures in JupyterLab. Replaces the `@jupyterlab/plotly-extension` extension, and includes JupyterLab 1.0 support.
- Added new suite of built-in colorscales to the `plotly.colors` module, and support for specifying this wide range of colorscales by name. Also added support for specifying colorscales as a list of colors, in which case the color spacing is assumed to be uniform ([#1647](https://github.com/plotly/plotly.py/pull/1647)).
- Added `sphinx-gallery` renderer for embedding plotly figures in [Sphinx-Gallery](https://sphinx-gallery.github.io/) ([#1577](https://github.com/plotly/plotly.py/pull/1577), [plotly/plotly-sphinx-gallery](https://github.com/plotly/plotly-sphinx-gallery)).
Expand Down Expand Up @@ -1096,7 +1096,7 @@ must be installed:
properties are ignored rather than causing an exception.
- A `to_ordered_dict` method has been added to the `Figure` and `FigureWidget`
classes. This method returns a representation of the figure as a nested
structure of `OrdererdDict` and `list` instances where the keys in each
structure of `OrderedDict` and `list` instances where the keys in each
`OrderedDict` are sorted alphabetically. This method replaces the
`get_ordered` method that was available in version 2, and makes it possible
to traverse the nested structure of a figure in a deterministic order.
Expand Down Expand Up @@ -1517,7 +1517,7 @@ gone.
## [1.12.10] - 2016-11-28
### Updated
- `FF.create_violin` and `FF.create_scatterplotmatrix` now by default do not print subplot grid information in output
- Removed alert that occured when downloading plot images offline. Please note: for higher resolution images and more export options, consider making requests to our image servers. See: `help(py.image)` for more details.
- Removed alert that occurred when downloading plot images offline. Please note: for higher resolution images and more export options, consider making requests to our image servers. See: `help(py.image)` for more details.

### Added
- Plot configuration options for offline plots. See the list of [configuration options](https://github.com/Rikorose/plotly.py/blob/master/plotly/offline/offline.py#L189) and [examples](https://plot.ly/javascript/configuration-options/) for more information.
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2 changes: 1 addition & 1 deletion build_for_conda.md
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Expand Up @@ -16,4 +16,4 @@ Finally, build and test the created version:

`conda build plotly`

Currently, the updated (version 1.12.4) conda package sits at https://anaconda.org/chohner/plotly. There seems to be an old offial package at https://anaconda.org/plotly/plotly.
Currently, the updated (version 1.12.4) conda package sits at https://anaconda.org/chohner/plotly. There seems to be an old official package at https://anaconda.org/plotly/plotly.
2 changes: 1 addition & 1 deletion doc/python/3d-mesh.md
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Expand Up @@ -83,7 +83,7 @@ IFrame(snippet_url + '3d-mesh', width='100%', height=630)

### Mesh Tetrahedron

In this example we use the `ì`, `j` and `k` parameters to specify manually the geometry of the triangles of the mesh.
In this example we use the `i`, `j` and `k` parameters to specify manually the geometry of the triangles of the mesh.

```python
import plotly.graph_objects as go
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4 changes: 2 additions & 2 deletions doc/python/linear-fits.md
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Expand Up @@ -23,7 +23,7 @@ jupyter:
version: 3.6.8
plotly:
description: Add linear Ordinary Least Squares (OLS) regression trendlines or
non-linear Locally Weighted Scatterplot Smoothing (LOEWSS) trendlines to scatterplots
non-linear Locally Weighted Scatterplot Smoothing (LOWESS) trendlines to scatterplots
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again, very impressive catch!

in Python.
display_as: statistical
language: python
Expand Down Expand Up @@ -76,4 +76,4 @@ import plotly.express as px
df = px.data.gapminder().query("year == 2007")
fig = px.scatter(df, x="gdpPercap", y="lifeExp", color="continent", trendline="lowess")
fig.show()
```
```
2 changes: 1 addition & 1 deletion doc/python/ml-regression.md
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Expand Up @@ -174,7 +174,7 @@ fig.show()
Notice how linear regression fits a straight line, but kNN can take non-linear shapes. Moreover, it is possible to extend linear regression to polynomial regression by using scikit-learn's `PolynomialFeatures`, which lets you fit a slope for your features raised to the power of `n`, where `n=1,2,3,4` in our example.


With Plotly, it's easy to diplay latex equations in legend and titles by simply adding `$` before and after your equation. This way, you can see the coefficients that our polynomial regression fitted.
With Plotly, it's easy to display latex equations in legend and titles by simply adding `$` before and after your equation. This way, you can see the coefficients that our polynomial regression fitted.
<!-- #endregion -->

```python
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2 changes: 1 addition & 1 deletion doc/python/sliders.md
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Expand Up @@ -90,7 +90,7 @@ The method determines which [plotly.js function](https://plot.ly/javascript/plot


### Sliders in Plotly Express
Plotly Express provide sliders, but with implicit animation using the `"animate"` method described above. The animation play button can be omited 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 omitted by removing `updatemenus` in the `layout`:

```python
import plotly.express as px
Expand Down
2 changes: 1 addition & 1 deletion doc/python/ternary-plots.md
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Expand Up @@ -41,7 +41,7 @@ A ternary plot depicts the ratios of three variables as positions in an equilate

[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/).

Here we use `px.scatter_ternary` to visualize thre three-way split between the three major candidates in a municipal election.
Here we use `px.scatter_ternary` to visualize the three-way split between the three major candidates in a municipal election.

```python
import plotly.express as px
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4 changes: 2 additions & 2 deletions doc/unconverted/python/3d-parametric-plots.md
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Expand Up @@ -12,7 +12,7 @@ jupyter:
language: python
name: python2
plotly:
description: How to 3D Parameteric Plots in Python
description: How to 3D Parametric Plots in Python
display_as: 3d_charts
language: python
layout: base
Expand Down Expand Up @@ -80,7 +80,7 @@ py.iplot(fig, filename='Parametric_plot')
```

<!-- #region {"deletable": true, "editable": true} -->
#### Parameteric Plot with Colorscale
#### Parametric Plot with Colorscale
<!-- #endregion -->

```python deletable=true editable=true
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2 changes: 1 addition & 1 deletion doc/unconverted/python/amazon-redshift.md
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Expand Up @@ -68,7 +68,7 @@ port = 5439
dbname = 'dev'
```

As I mentioned there are numerous ways to connect to a Redshift databause and I've included two below. We can use either the SQLAlchemy package or we can use the psycopg2 package for a more direct access.
As I mentioned there are numerous ways to connect to a Redshift database and I've included two below. We can use either the SQLAlchemy package or we can use the psycopg2 package for a more direct access.

Both will allow us to execute SQL queries and get results however the SQLAlchemy engine makes it a bit easier to directly return our data as a dataframe using pandas. Plotly has a tight integration with pandas as well, making it extremely easy to make interactive graphs to share with your company.

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2 changes: 1 addition & 1 deletion doc/unconverted/python/anova.md
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Expand Up @@ -25,7 +25,7 @@ jupyter:
---

#### New to Plotly?
Plotly's Python library is free and open source! [Get started](https://plot.ly/python/getting-started/) by dowloading the client and [reading the primer](https://plot.ly/python/getting-started/).
Plotly's Python library is free and open source! [Get started](https://plot.ly/python/getting-started/) by downloading the client and [reading the primer](https://plot.ly/python/getting-started/).
<br>You can set up Plotly to work in [online](https://plot.ly/python/getting-started/#initialization-for-online-plotting) or [offline](https://plot.ly/python/getting-started/#initialization-for-offline-plotting) mode, or in [jupyter notebooks](https://plot.ly/python/getting-started/#start-plotting-online).
<br>We also have a quick-reference [cheatsheet](https://images.plot.ly/plotly-documentation/images/python_cheat_sheet.pdf) (new!) to help you get started!

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2 changes: 1 addition & 1 deletion doc/unconverted/python/average_multiple_curves.md
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Expand Up @@ -25,7 +25,7 @@ jupyter:
---

#### New to Plotly?
Plotly's Python library is free and open source! [Get started](https://plot.ly/python/getting-started/) by dowloading the client and [reading the primer](https://plot.ly/python/getting-started/).
Plotly's Python library is free and open source! [Get started](https://plot.ly/python/getting-started/) by downloading the client and [reading the primer](https://plot.ly/python/getting-started/).
<br>You can set up Plotly to work in [online](https://plot.ly/python/getting-started/#initialization-for-online-plotting) or [offline](https://plot.ly/python/getting-started/#initialization-for-offline-plotting) mode, or in [jupyter notebooks](https://plot.ly/python/getting-started/#start-plotting-online).
<br>We also have a quick-reference [cheatsheet](https://images.plot.ly/plotly-documentation/images/python_cheat_sheet.pdf) (new!) to help you get started!

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2 changes: 1 addition & 1 deletion doc/unconverted/python/baseline-subtraction.md
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Expand Up @@ -60,7 +60,7 @@ py.iplot(table, filename='milk-production-dataframe')
```

#### Plot with Baseline
To subtact a baseline estimate from our data, it is a good idea to first we must first calculate the baseline values then plot the data with the baseline drawn in.
To subtract a baseline estimate from our data, it is a good idea to first we must first calculate the baseline values then plot the data with the baseline drawn in.

```python
baseline_values = peakutils.baseline(time_series)
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2 changes: 1 addition & 1 deletion doc/unconverted/python/basic-statistics.md
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Expand Up @@ -25,7 +25,7 @@ jupyter:
---

#### New to Plotly?
Plotly's Python library is free and open source! [Get started](https://plot.ly/python/getting-started/) by dowloading the client and [reading the primer](https://plot.ly/python/getting-started/).
Plotly's Python library is free and open source! [Get started](https://plot.ly/python/getting-started/) by downloading the client and [reading the primer](https://plot.ly/python/getting-started/).
<br>You can set up Plotly to work in [online](https://plot.ly/python/getting-started/#initialization-for-online-plotting) or [offline](https://plot.ly/python/getting-started/#initialization-for-offline-plotting) mode, or in [jupyter notebooks](https://plot.ly/python/getting-started/#start-plotting-online).
<br>We also have a quick-reference [cheatsheet](https://images.plot.ly/plotly-documentation/images/python_cheat_sheet.pdf) (new!) to help you get started!

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4 changes: 2 additions & 2 deletions doc/unconverted/python/chord-diagram.md
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Expand Up @@ -45,10 +45,10 @@ To avoid cluttered edges we adopted the following procedure in choosing the inte
- define a list, `Dist`, having as elements the distances between the following pairs of points:
$$(P_1, P_1), \:(P_1, P_2), \: (P_1, P_3),\: (P_1, P_4),\: (P_1, P_5)$$

- In order to assign the control poligon to the B&eacute;zier curve that will be the edge between two connected
- In order to assign the control polygon to the B&eacute;zier curve that will be the edge between two connected
nodes, `V[i], V[j]`, we compute the distance between these nodes, and deduce the interval $k$, of two consecutive values in `Dist`, this distance belongs to.

- Since there are four such intervals indexed $k=0,1,2,3$, we define the control poligon as follows: $${\bf b}_0=V[i],\:\: {\bf b}_1=V[i]/param,\:\: {\bf b}_2=V[j]/param, \:\:{\bf b}_3=V[j],$$ where `param` is chosen from the list: `params=[1.2, 1.5, 1.8, 2.1]`.
- Since there are four such intervals indexed $k=0,1,2,3$, we define the control polygon as follows: $${\bf b}_0=V[i],\:\: {\bf b}_1=V[i]/param,\:\: {\bf b}_2=V[j]/param, \:\:{\bf b}_3=V[j],$$ where `param` is chosen from the list: `params=[1.2, 1.5, 1.8, 2.1]`.

Namely, if the distance(`V[i], V[j]`), belongs to the $K^{th}$ interval associated to `Dist`, then we choose `param= params[K]`.

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2 changes: 1 addition & 1 deletion doc/unconverted/python/density-plots.md
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Expand Up @@ -26,7 +26,7 @@ jupyter:

<!-- #region {"deletable": true, "editable": true} -->
#### New to Plotly?
Plotly's Python library is free and open source! [Get started](https://plot.ly/python/getting-started/) by dowloading the client and [reading the primer](https://plot.ly/python/getting-started/).
Plotly's Python library is free and open source! [Get started](https://plot.ly/python/getting-started/) by downloading the client and [reading the primer](https://plot.ly/python/getting-started/).
<br>You can set up Plotly to work in [online](https://plot.ly/python/getting-started/#initialization-for-online-plotting) or [offline](https://plot.ly/python/getting-started/#initialization-for-offline-plotting) mode, or in [jupyter notebooks](https://plot.ly/python/getting-started/#start-plotting-online).
<br>We also have a quick-reference [cheatsheet](https://images.plot.ly/plotly-documentation/images/python_cheat_sheet.pdf) (new!) to help you get started!
<!-- #endregion -->
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4 changes: 2 additions & 2 deletions doc/unconverted/python/discrete-frequency.md
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Expand Up @@ -25,7 +25,7 @@ jupyter:
---

#### New to Plotly?
Plotly's Python library is free and open source! [Get started](https://plot.ly/python/getting-started/) by dowloading the client and [reading the primer](https://plot.ly/python/getting-started/).
Plotly's Python library is free and open source! [Get started](https://plot.ly/python/getting-started/) by downloading the client and [reading the primer](https://plot.ly/python/getting-started/).
<br>You can set up Plotly to work in [online](https://plot.ly/python/getting-started/#initialization-for-online-plotting) or [offline](https://plot.ly/python/getting-started/#initialization-for-offline-plotting) mode, or in [jupyter notebooks](https://plot.ly/python/getting-started/#start-plotting-online).
<br>We also have a quick-reference [cheatsheet](https://images.plot.ly/plotly-documentation/images/python_cheat_sheet.pdf) (new!) to help you get started!

Expand Down Expand Up @@ -115,7 +115,7 @@ py.iplot(fig, filename='histogram-percentage')
#### Cumulative Density Function


We can also take the cumulatve sum of our dataset and then plot the cumulative density function, or `CDF`, as a scatter plot
We can also take the cumulative sum of our dataset and then plot the cumulative density function, or `CDF`, as a scatter plot

```python
cumsum = np.cumsum(x)
Expand Down
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