document corrections

Author: c-chaitanya

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.

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.

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

doc/python/imshow.md

@@ -231,7 +231,7 @@ fig.show()
 
 ### Automatic contrast rescaling in `px.imshow`
 
-When `zmin` and `zmax` are not specified, the `contrast_rescaling` arguments determines how `zmin` and `zmax` are computed. For `contrast_rescaling='minmax'`, the extrema of the data range are used. For `contrast_rescaling='infer'`, a heuristic based on the data type is used:
+When `zmin` and `zmax` are not specified, the `contrast_rescaling` arguments determines how `zmin` and `zmax` are computed. For `contrast_rescaling='minmax'`, the extreme of the data range are used. For `contrast_rescaling='infer'`, a heuristic based on the data type is used:
 - for integer data types, `zmin` and `zmax` correspond to the extreme values of the data type, for example 0 and 255 for `uint8`, 0 and 65535 for `uint16`, etc.
 - for float numbers, the maximum value of the data is computed, and zmax is 1 if the max is smaller than 1, 255 if the max is smaller than 255, etc. (with higher thresholds 2**16 - 1 and 2**32 -1).
 

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()
-```
+```

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

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

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.
 

doc/unconverted/python/filled-chord-diagram.md

@@ -28,7 +28,7 @@ jupyter:
 
 Circular layout or [Chord diagram](https://en.wikipedia.org/wiki/Chord_diagram) is a method of visualizing  data that describe relationships. It was intensively promoted  through [Circos](http://circos.ca/), a software package in Perl that  was initially designed for displaying genomic data.
 
-M Bostock developed reusable charts  for [chord diagrams](http://bl.ocks.org/mbostock/4062006) in d3.js. Two years ago on [stackoverflow](http://stackoverflow.com/questions/19105801/chord-diagram-in-python), the exsistence of a Python package for plotting chord diagrams was adressed, but the question was closed due to being *off topic*.<br> Here we show that a chord diagram can be generated in Python with Plotly. We illustrate the method of generating a chord diagram from data recorded in a square matrix. The rows and columns represent the same entities.
+M Bostock developed reusable charts  for [chord diagrams](http://bl.ocks.org/mbostock/4062006) in d3.js. Two years ago on [stackoverflow](http://stackoverflow.com/questions/19105801/chord-diagram-in-python), the existence of a Python package for plotting chord diagrams was addressed, but the question was closed due to being *off topic*.<br> Here we show that a chord diagram can be generated in Python with Plotly. We illustrate the method of generating a chord diagram from data recorded in a square matrix. The rows and columns represent the same entities.
 
 This example considers a community of 5 friends on Facebook. We record the number of comments posted by each member on the other friends' walls. The data table is given in the next cell:
 

doc/unconverted/python/gapminder-example.md

@@ -62,7 +62,7 @@ py.iplot(table, filename='animations-gapminder-data-preview')
 #### Make the Grid
 Since we are using the v2 api for animations in Plotly, we need to first make a `grid`. You can learn more in the [introduction to animation doc](https://plot.ly/python/animations/).
 
-We will first define a list of _string_ years which will represent the values that our `slider` will take on. Going through the dataset, we will take out all the unique continents from the column `continent` and store them as well. Finally, we make a grid with each column representing a slice of the dataframe by _year_, _continent_ and _column name_, making sure to name each column uniquly by these variables:
+We will first define a list of _string_ years which will represent the values that our `slider` will take on. Going through the dataset, we will take out all the unique continents from the column `continent` and store them as well. Finally, we make a grid with each column representing a slice of the dataframe by _year_, _continent_ and _column name_, making sure to name each column uniquely by these variables:
 
 ```python
 years_from_col = set(dataset['year'])
@@ -259,7 +259,7 @@ Finally we make our `frames`. Here we are running again through the years and co
 ```
 frame = {'data': [], 'name': value-name}
 ```
-We add a dictionary of data to this list and at the end of each loop, we ensure to add the `steps` dictionary to the steps list. At the end, we attatch the `sliders` dictionary to the figure via:
+We add a dictionary of data to this list and at the end of each loop, we ensure to add the `steps` dictionary to the steps list. At the end, we attach the `sliders` dictionary to the figure via:
 
 ```
 figure['layout']['sliders'] = [sliders_dict]