semvec/pypi-packages huggingface dataset:
visaplan.js.urlsplit 1.1.0
Plone integration of urlSplit.js
License: MIT

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====================
visaplan.js.urlsplit
====================

This is a simple Zope_ / Plone_ integration of the `urlSplit.js`_ Javascript tool
which provides a ``urlSplit(url_string)`` function.

Features
--------

- Makes available both the compressed and uncompressed versions of ``urlSplit.js``
- Adds the compressed version to the Javascript registry


Documentation
-------------

For the Javascript functionality, please see urlSplit.js_.


Installation
------------

Install visaplan.js.urlsplit by adding it to your buildout::

    [buildout]

    ...

    eggs =
        visaplan.js.urlsplit


and then running ``bin/buildout``.

After restarting your Zope instance, install the extension using the ``/prefs_install_products_form``.


As a dependency
~~~~~~~~~~~~~~~

- Add the package to your package dependencies, e.g. in your ``setup.py``::

    ...
    install_requires=[
        'setuptools',
        'visaplan.js.urlsplit',
        ],
    ...

- Add the package to your profile dependencies, e.g. in your ``…/profiles/default/metadata.xml``::

    <version>1000</version>
    <dependencies>
      <dependency>profile-visaplan.js.urlsplit:default</dependency>
    </dependencies>

- Restart your Zope instance and re-install your package.


Contribute
----------

For the Javascript functionality, please contribute to `urlSplit.js`_.

For the Zope / Plone integration:

- Issue Tracker: https://github.com/visaplan/js.urlsplit/issues
- Source Code: https://github.com/visaplan/js.urlsplit


License
-------

The project is licensed under the MIT License.

.. _Zope: https://www.zope.org
.. _Plone: https://plone.org
.. _`urlSplit.js`: https://github.com/hans-sperling/urlSplit.js


============
Contributors
============

- Danny Grübl (urlSplit.js)
- Tobias Herp, tobias.herp@visaplan.com (Plone integration)


=========
Changelog
=========


1.1.0 (2021-11-29)
------------------

New Features:

- Added new script ``urlUnsplit.js``, containing a `urlUnsplit` function

Improvements:

- ``jsregistry.xml``: better attributes order (`id` first)

Profile changes:

- Registered new script (but disabled, by default)
- Incremented profile version to 1002

Requirements:

- depends on plone.resource_

[tobiasherp]


1.0.2 (2019-06-07)
------------------

- Corrected internet links; improved installation documentation.
  [tobiasherp]


1.0 (2019-06-07)
----------------

- Initial release, containing urlSplit.js_ v2.1.2.
  [tobiasherp]


.. _urlSplit.js: https://github.com/hans-sperling/urlSplit.js
.. _plone.resource: https://pypi.org/project/plone.resource
pandas-xlsx-tables 1.0.0
Read and write excel tables with pandas
License: MIT
Requires Python: >=3.8

# pandas-xlsx-tables

Even though you might not like it, Excel isn't going anywhere. And Excel with tables is [a lot better than without](https://www.ecosia.org/search?q=advantages+of+excel+tables). Some highlights are: better performance, reference columns by name (vs defining named ranges), sticky headers (vs freeze panes), stricter typing (vs random types) and sort/filter dropdowns.

Out of the box Pandas provides to and from excel functionality, but it cannot write native excel tables (the result is only formatted like one). This is where pandas-xlsx-tables comes in: convert excel tables to dataframes and vice versa, whilest mostly preserving data types. The api has been kept deliberatly  simple as to provide useful functionality out of the box.

!["Excel screenshot](https://raw.githubusercontent.com/VanOord/pandas-xlsx-tables/master/docs/_static/xlsx_table.png)

```python
>>> from pandas_xlsx_tables import xlsx_table_to_df
>>> df = xlsx_table_to_df("my_file.xlsx", "Table1")
>>> df
     col1 col2
Row
0       1    a
1       2    b
```
And the reverse process:

```python
>>> from pandas_xlsx_tables import df_to_xlsx_table
>>> df_to_xlsx_table(df, "my_table", header_orientation="diagonal", index=False)
```

!["Excel screenshot](https://raw.githubusercontent.com/VanOord/pandas-xlsx-tables/master/docs/_static/xlsx_table_2.png)


## Why not integretate this in Pandas directly?

Due to the complexity of Pandas and the large number of users it is very difficult to significantly change the current excel implementeation. Also the abstractions available to plug different engines are not that helpful. Basically I tried and [gave up](https://github.com/pandas-dev/pandas/issues/24862) (but of course I would prefer having this built into Pandas).