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Merge pull request #4399 from plotly/master
Merge `master` to `doc-prod`
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CHANGELOG.md

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All notable changes to this project will be documented in this file.
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This project adheres to [Semantic Versioning](http://semver.org/).
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## [5.18.0] - 2023-10-25
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### Updated
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- Updated Plotly.js from version 2.26.0 to version 2.27.0. See the [plotly.js CHANGELOG](https://github.com/plotly/plotly.js/blob/master/CHANGELOG.md#2270----2023-10-20) for more information. These changes are reflected in the auto-generated `plotly.graph_objects` module. Notable changes include:
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- Add `insiderange` to cartesian axes to help avoid overlap between visible grid lines and tick labels of the counter axis when they are positioned inside [[#6735](https://github.com/plotly/plotly.js/pull/6735)], this feature was anonymously sponsored: thank you to our sponsor!
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- Fix column order changes on hover [[#6718](https://github.com/plotly/plotly.js/pull/6718)],
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with thanks to @bhavinpatel1109 for the contribution!
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- Fix hover at timestamp '1970-01-01 00:00:00' [[#6752](https://github.com/plotly/plotly.js/pull/6752)],
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with thanks to @adamjhawley for the contribution!
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- Fix clearing empty `candlestick` using react [[#6757](https://github.com/plotly/plotly.js/pull/6757)]
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### Fixed
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- Repair crash on Matplotlib 3.8 related to get_offset_position [[#4372](https://github.com/plotly/plotly.py/pull/4372)],
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- Handle deprecation of `pandas.Series.dt.to_pydatetime()` calls and suppress the `FutureWarning` they currently emit. [[#4379](https://github.com/plotly/plotly.py/pull/4379)]
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## [5.17.0] - 2023-09-15
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### Updated

README.md

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## Quickstart
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`pip install plotly==5.17.0`
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`pip install plotly==5.18.0`
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Inside [Jupyter](https://jupyter.org/install) (installable with `pip install "jupyterlab>=3" "ipywidgets>=7.6"`):
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plotly.py may be installed using pip...
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```
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pip install plotly==5.17.0
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pip install plotly==5.18.0
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```
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or conda.
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```
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conda install -c plotly plotly=5.17.0
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conda install -c plotly plotly=5.18.0
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```
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### JupyterLab Support
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```
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# JupyterLab 2.x renderer support
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jupyter labextension install jupyterlab-plotly@5.17.0 @jupyter-widgets/jupyterlab-manager
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jupyter labextension install jupyterlab-plotly@5.18.0 @jupyter-widgets/jupyterlab-manager
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```
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Please check out our [Troubleshooting guide](https://plotly.com/python/troubleshooting/) if you run into any problems with JupyterLab.

binder/requirements.txt

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jupytext
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plotly==5.17.0
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plotly==5.18.0
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jupyter
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notebook
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pandas==1.0.3

contributing.md

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Running tests with tox is much more powerful, but requires a bit more setup.
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You'll need to export an environment variable for *each* tox environment you wish to test with. For example, if you want to test with `Python 2.7` and
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You'll need to export an environment variable for *each* tox environment you wish to test with. For example, if you want to test with `Python 3.9` and
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`Python 3.6`, but only care to check the `core` specs, you would need to ensure that the following variables are exported:
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```
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export PLOTLY_TOX_PYTHON_27=<python binary>
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export PLOTLY_TOX_PYTHON_39=<python binary>
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export PLOTLY_TOX_PYTHON_36=<python binary>
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```
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# tox envs #
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############
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export PLOTLY_TOX_PYTHON_27=python2.7
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export PLOTLY_TOX_PYTHON_34=python3.4
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export TOXENV=py27-core,py34-core
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export PLOTLY_TOX_PYTHON_39=python3.9
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export PLOTLY_TOX_PYTHON_36=python3.6
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export TOXENV=py39-core,py36-core
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Where `TOXENV` is the environment list you want to use when invoking `tox` from the command line. Note that the `PLOTLY_TOX_*` pattern is used to pass in variables for use in the `tox.ini` file. Though this is a little setup, intensive, you'll get the following benefits:
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* `tox` will automatically manage a virtual env for each environment you want to test in.
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* You only have to run `tox` and know that the module is working in both `Python 2` and `Python 3`.
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* You only have to run `tox` and know that the module is working in all included Python versions.
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Finally, `tox` allows you to pass in additional command line arguments that are formatted in (by us) in the `tox.ini` file, see `{posargs}`. This is setup to help with our configuration of [pytest markers](http://doc.pytest.org/en/latest/example/markers.html), which are set up in `packages/python/plotly/pytest.ini`. To run only tests that are *not* tagged with `nodev`, you could use the following command:
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doc/apidoc/conf.py

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# -*- coding: utf-8 -*-
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#
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# Configuration file for the Sphinx documentation builder.
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#
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# This file does only contain a selection of the most common options. For a
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# The short X.Y version
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version = ""
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# The full version, including alpha/beta/rc tags
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release = "5.17.0"
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release = "5.18.0"
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# -- General configuration ---------------------------------------------------

doc/python/axes.md

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#### Exclude Inside Tick Labels from Range
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*New in 5.18*
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You can use `insiderange` instead of `range` on an axis if you have tick labels positioned on the inside of another axis and you don't want the range to overlap with those labels.
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In this example, we have a y axis with `ticklabelposition="inside"` and by setting `insiderange=['2018-10-01', '2019-01-01']` on the x axis, the data point of `2018-10-01` is displayed after the y axis labels.
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```python
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import plotly.express as px
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df = px.data.stocks(indexed=True)
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fig = px.line(df, df.index, y="GOOG")
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fig.update_yaxes(ticklabelposition="inside", title="Price")
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fig.update_xaxes(insiderange=['2018-10-01', '2019-01-01'], title="Date")
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fig.show()
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```
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*New in 5.17*

doc/python/getting-started.md

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`plotly` may be installed using `pip`:
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$ pip install plotly==5.18.0
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$ conda install -c plotly plotly=5.18.0
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This package contains everything you need to write figures to standalone HTML files.
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```
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# JupyterLab 2.x renderer support
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jupyter labextension install jupyterlab-plotly@5.18.0 @jupyter-widgets/jupyterlab-manager
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Please check out our [Troubleshooting guide](/python/troubleshooting/) if you run into any problems with JupyterLab, particularly if you are using multiple python environments inside Jupyter.

doc/requirements.txt

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doc/unconverted/python/amazon-redshift.md

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In this notebook we'll be using [Amazon's Sample Redshift Data](http://docs.aws.amazon.com/redshift/latest/gsg/rs-gsg-create-sample-db.html) for this notebook. Although we won't be connecting through a JDBC/ODBC connection we'll be using the [psycopg2 package](http://initd.org/psycopg/docs/index.html) with [SQLAlchemy](http://www.sqlalchemy.org/) and [pandas](http://pandas.pydata.org/) to make it simple to query and analyze our data.
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```python
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doc/unconverted/python/apache-spark.md

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