Merge pull request #3079 from c-chaitanya/doc-prod

Doc prod

Author: nicolaskruchten

Diff for: CHANGELOG.md

@@ -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)
 
@@ -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
@@ -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
 
@@ -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
@@ -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
 
@@ -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`
  - Avoid crash in iframe renderers when running outside iPython ([#1723](https://github.com/plotly/plotly.py/pull/1723))
 
 ## [4.1.0] - 2019-08-06
@@ -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)).
@@ -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.
@@ -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.

Diff for: build_for_conda.md

@@ -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.

Diff for: doc/python/3d-mesh.md

@@ -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

Diff for: doc/python/linear-fits.md

@@ -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
       in Python.
     display_as: statistical
     language: python
@@ -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()
-```
+```

Diff for: doc/python/ml-regression.md

@@ -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

Diff for: doc/python/sliders.md

@@ -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

Diff for: doc/python/ternary-plots.md

@@ -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

Diff for: doc/unconverted/python/3d-parametric-plots.md

@@ -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
@@ -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

Diff for: doc/unconverted/python/amazon-redshift.md

@@ -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.
 

Diff for: doc/unconverted/python/anova.md

@@ -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!
 

Diff for: doc/unconverted/python/average_multiple_curves.md

@@ -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!
 

Diff for: doc/unconverted/python/baseline-subtraction.md

@@ -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)

Diff for: doc/unconverted/python/basic-statistics.md

@@ -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!
 

Diff for: doc/unconverted/python/chord-diagram.md

@@ -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 Bézier curve that will be the edge between two connected
+- In order to assign the control polygon to the Bézier 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]`.
 

Diff for: doc/unconverted/python/density-plots.md

@@ -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 -->

Diff for: doc/unconverted/python/discrete-frequency.md

@@ -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!
 
@@ -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)