docs: updated 179 broken links

.github/ISSUE_TEMPLATE/bug_report_form.yaml

@@ -22,7 +22,7 @@ body:
     id: expected-behavior
     attributes:
       label: Expected Behaviour
-      description:  Tell us what should happen
+      description: Tell us what should happen
       placeholder: ex. the report contained B
     validations:
       required: true
@@ -84,12 +84,12 @@ body:
       label: Checklist
       description: |
         Please complete the checklist below to ensure the bug report is helpful and can be addressed effectively
-        
+
         Tips:
           - Help for writing better bug reports is available in the [documentation](https://pandas-profiling.ydata.ai/docs/master/pages/support_contrib/help_troubleshoot.html).
           - If the description consists of multiple non-related bugs, you are encouraged to create separate issues.
       options:
-        - label: There is not yet another bug report for this issue in the [issue tracker](https://github.com/ydataai/pandas-profiling/issues)
+        - label: There is not yet another bug report for this issue in the [issue tracker](https://github.com/ydataai/ydata-profiling/issues)
           required: true
         - label: The problem is reproducible from this bug report. [This guide](http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) can help to craft a minimal bug report.
           required: true

CONTRIBUTING.md

@@ -17,7 +17,7 @@ In line with our aim, we identify the following themes:
   time series analysis, 
   or even images (e.g. dimensions, EXIF).
 
-  _Related_: [#7][i7], [#129][i129], [#190][i190], [#204][i204] or [create one](https://github.com/ydataai/pandas-profiling/issues/new/choose).
+  _Related_: [#7][i7], [#129][i129], [#190][i190], [#204][i204] or [create one](https://github.com/ydataai/ydata-profiling/issues/new/choose).
 
 - **Stability, Performance and Restricted environment compatibility:** 
   Data exploration takes place in all kinds of conditions, on the latest machine learning platforms with enormous dataset to managed environments in large corporations.
@@ -28,9 +28,9 @@ In line with our aim, we identify the following themes:
   Perform concurrency analysis or profile execution times and leverage the gained insights for improved performance (e.g. multiprocessing, cython, numba) or test the performance of `pandas-profiling` with [big data sets](https://www.stats.govt.nz/large-datasets/csv-files-for-download/) and corresponding commonly used data formats (such as parquet). 
 
   _Suggestions for contribution (Stability)_: 
-  Either review the code and add tests or watch the [issues page](https://github.com/ydataai/pandas-profiling/issues) and [Stackoverflow tag](https://stackoverflow.com/questions/tagged/pandas-profiling) to find current issues.
+  Either review the code and add tests or watch the [issues page](https://github.com/ydataai/ydata-profiling/issues) and [Stackoverflow tag](https://stackoverflow.com/questions/tagged/pandas-profiling) to find current issues.
 
-  _Related_: [#98][i98], [#122][i122] or [create one](https://github.com/ydataai/pandas-profiling/issues/new/choose).
+  _Related_: [#98][i98], [#122][i122] or [create one](https://github.com/ydataai/ydata-profiling/issues/new/choose).
 
 - **Interaction, presentation and user experience**: 
   As `pandas-profiling` eases exploratory data analysis, working with the package should reflect that.
@@ -46,7 +46,7 @@ In line with our aim, we identify the following themes:
   Other forms of distribution than HTML (for example PDF or packaged as an GUI application via [PyQt](https://riverbankcomputing.com/software/pyqt/intro))
   Users should be able to share reports (improve size of labels in graph, add explanations to correlation matrices and allow for styling/branding).
 
-  _Related_: [#161][i161], [#175][i175], [#191][i191] or [create one](https://github.com/ydataai/pandas-profiling/issues/new/choose).
+  _Related_: [#161][i161], [#175][i175], [#191][i191] or [create one](https://github.com/ydataai/ydata-profiling/issues/new/choose).
 
 - **Community**: 
   The success of this package demonstrates the power of sharing and working together.
@@ -56,20 +56,20 @@ In line with our aim, we identify the following themes:
   Share with us if this package is of value to you, let us know [in our community](https://discord.com/invite/mw7xjJ7b7s).
   We are interested in how you use `pandas-profiling` in your work.
 
-  _Related_: [#87][i87] or [create one](https://github.com/ydataai/pandas-profiling/issues/new/choose).
+  _Related_: [#87][i87] or [create one](https://github.com/ydataai/ydata-profiling/issues/new/choose).
 
 - **Machine learning:** 
   `pandas-profiling` is not a machine learning package, even though many of our users use EDA as a step prior to developing their models.
   Our focus lies in the exploratory data analysis.
   Any functionality that enables machine learning applications by more effective data profiling, is welcome.
 
-  _Related_: [#124][i124], [#173][i173], [#198][i198] or [create one](https://github.com/ydataai/pandas-profiling/issues/new/choose).
+  _Related_: [#124][i124], [#173][i173], [#198][i198] or [create one](https://github.com/ydataai/ydata-profiling/issues/new/choose).
 
 #### **Did you find a bug?**
 
-* **Ensure the bug was not already reported** by searching on Github under [Issues](https://github.com/ydataai/pandas-profiling/issues).
+* **Ensure the bug was not already reported** by searching on Github under [Issues](https://github.com/ydataai/ydata-profiling/issues).
 
-* If you're unable to find an open issue addressing the problem, [open a new one](https://github.com/ydataai/pandas-profiling/issues/new/choose). 
+* If you're unable to find an open issue addressing the problem, [open a new one](https://github.com/ydataai/ydata-profiling/issues/new/choose). 
 If possible, use the relevant bug report templates to create the issue. 
 
 #### **Did you write a patch that fixes a bug?**
@@ -84,19 +84,19 @@ Include the relevant issue number if applicable.
 
 We would like to thank everyone who has helped getting us to where we are now.
 
-See the [Contributor Graph](https://github.com/ydataai/pandas-profiling/graphs/contributors)
-
-[i7]: https://github.com/ydataai/pandas-profiling/issues/7
-[i129]: https://github.com/ydataai/pandas-profiling/issues/129
-[i190]: https://github.com/ydataai/pandas-profiling/issues/190
-[i204]: https://github.com/ydataai/pandas-profiling/issues/204
-[i98]: https://github.com/ydataai/pandas-profiling/issues/98
-[i122]: https://github.com/ydataai/pandas-profiling/issues/122
-[i124]: https://github.com/ydataai/pandas-profiling/issues/24
-[i173]: https://github.com/ydataai/pandas-profiling/issues/173
-[i198]: https://github.com/ydataai/pandas-profiling/issues/198
-[i87]: https://github.com/ydataai/pandas-profiling/issues/87
-[i161]: https://github.com/ydataai/pandas-profiling/issues/161
-[i175]: https://github.com/ydataai/pandas-profiling/issues/175
-[i191]: https://github.com/ydataai/pandas-profiling/issues/191
+See the [Contributor Graph](https://github.com/ydataai/ydata-profiling/graphs/contributors)
+
+[i7]: https://github.com/ydataai/ydata-profiling/issues/7
+[i129]: https://github.com/ydataai/ydata-profiling/issues/129
+[i190]: https://github.com/ydataai/ydata-profiling/issues/190
+[i204]: https://github.com/ydataai/ydata-profiling/issues/204
+[i98]: https://github.com/ydataai/ydata-profiling/issues/98
+[i122]: https://github.com/ydataai/ydata-profiling/issues/122
+[i124]: https://github.com/ydataai/ydata-profiling/issues/24
+[i173]: https://github.com/ydataai/ydata-profiling/issues/173
+[i198]: https://github.com/ydataai/ydata-profiling/issues/198
+[i87]: https://github.com/ydataai/ydata-profiling/issues/87
+[i161]: https://github.com/ydataai/ydata-profiling/issues/161
+[i175]: https://github.com/ydataai/ydata-profiling/issues/175
+[i191]: https://github.com/ydataai/ydata-profiling/issues/191
 

README.md

@@ -1,10 +1,10 @@
 # ydata-profiling
 
-[![Build Status](https://github.com/ydataai/pandas-profiling/actions/workflows/tests.yml/badge.svg?branch=master)](https://github.com/ydataai/pandas-profiling/actions/workflows/tests.yml)
+[![Build Status](https://github.com/ydataai/ydata-profiling/actions/workflows/tests.yml/badge.svg?branch=master)](https://github.com/ydataai/ydata-profiling/actions/workflows/tests.yml)
 [![PyPI download month](https://img.shields.io/pypi/dm/ydata-profiling.svg)](https://pypi.python.org/pypi/ydata-profiling/)
 [![](https://pepy.tech/badge/pandas-profiling)](https://pypi.org/project/ydata-profiling/)
 [![Code Coverage](https://codecov.io/gh/ydataai/pandas-profiling/branch/master/graph/badge.svg?token=gMptB4YUnF)](https://codecov.io/gh/ydataai/pandas-profiling)
-[![Release Version](https://img.shields.io/github/release/ydataai/pandas-profiling.svg)](https://github.com/ydataai/pandas-profiling/releases)
+[![Release Version](https://img.shields.io/github/release/ydataai/pandas-profiling.svg)](https://github.com/ydataai/ydata-profiling/releases)
 [![Python Version](https://img.shields.io/pypi/pyversions/ydata-profiling)](https://pypi.org/project/ydata-profiling/)
 [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/python/black)
 
@@ -161,8 +161,8 @@ The following example reports showcase the potentialities of the package across
 * [Website Inaccessibility](https://ydata-profiling.ydata.ai/examples/master/features/website_inaccessibility_report.html) (website accessibility analysis, showcasing support for URL data)
 * [Orange prices](https://ydata-profiling.ydata.ai/examples/master/features/united_report.html) and 
 * [Coal prices](https://ydata-profiling.ydata.ai/examples/master/features/flatly_report.html) (simple pricing evolution datasets, showcasing the theming options)
-* [USA Air Quality](https://github.com/ydataai/pandas-profiling/tree/master/examples/usaairquality) (Time-series air quality dataset EDA example)
-* [HCC](https://github.com/ydataai/pandas-profiling/tree/master/examples/hcc) (Open dataset from healthcare, showcasing compare between two sets of data, before and after preprocessing)
+* [USA Air Quality](https://github.com/ydataai/ydata-profiling/tree/master/examples/usaairquality) (Time-series air quality dataset EDA example)
+* [HCC](https://github.com/ydataai/ydata-profiling/tree/master/examples/hcc) (Open dataset from healthcare, showcasing compare between two sets of data, before and after preprocessing)
 
 ## 🛠️ Installation
 Additional details, including information about widget support, are available [on the documentation](https://ydata-profiling.ydata.ai/docs/master/pages/getting_started/installation.html).
@@ -206,7 +206,7 @@ conda install -c conda-forge ydata-profiling
 
 ### From source (development)
 
-Download the source code by cloning the repository or click on [Download ZIP](https://github.com/ydataai/pandas-profiling/archive/master.zip) to download the latest stable version.
+Download the source code by cloning the repository or click on [Download ZIP](https://github.com/ydataai/ydata-profiling/archive/master.zip) to download the latest stable version.
 
 Install it by navigating to the proper directory and running:
 
@@ -220,10 +220,10 @@ You need [Python 3](https://python3statement.org/) to run the package. Other dep
 
 | Filename | Requirements|
 |----------|-------------|
-| [requirements.txt](https://github.com/ydataai/pandas-profiling/blob/master/requirements.txt) | Package requirements|
-| [requirements-dev.txt](https://github.com/ydataai/pandas-profiling/blob/master/requirements-dev.txt)  |  Requirements for development|
-| [requirements-test.txt](https://github.com/ydataai/pandas-profiling/blob/master/requirements-test.txt) | Requirements for testing|
-| [setup.py](https://github.com/ydataai/pandas-profiling/blob/master/setup.py) | Requirements for widgets etc. |
+| [requirements.txt](https://github.com/ydataai/ydata-profiling/blob/master/requirements.txt) | Package requirements|
+| [requirements-dev.txt](https://github.com/ydataai/ydata-profiling/blob/master/requirements-dev.txt)  |  Requirements for development|
+| [requirements-test.txt](https://github.com/ydataai/ydata-profiling/blob/master/requirements-test.txt) | Requirements for testing|
+| [setup.py](https://github.com/ydataai/ydata-profiling/blob/master/setup.py) | Requirements for widgets etc. |
 
 ## 🔗 Integrations
 

docsrc/source/pages/getting_started/overview.rst

@@ -5,17 +5,17 @@ Overview
 .. image:: https://ydataai.github.io/pandas-profiling/docs/assets/logo_header.png
   :alt: Pandas Profiling Logo Header
 
-.. image:: https://github.com/ydataai/pandas-profiling/actions/workflows/tests.yml/badge.svg?branch=master
+.. image:: https://github.com/ydataai/ydata-profiling/actions/workflows/tests.yml/badge.svg?branch=master
   :alt: Build Status
-  :target: https://github.com/ydataai/pandas-profiling/actions/workflows/tests.yml
+  :target: https://github.com/ydataai/ydata-profiling/actions/workflows/tests.yml
 
 .. image:: https://codecov.io/gh/ydataai/pandas-profiling/branch/master/graph/badge.svg?token=gMptB4YUnF
   :alt: Code Coverage
   :target: https://codecov.io/gh/ydataai/pandas-profiling
 
 .. image:: https://img.shields.io/github/release/pandas-profiling/pandas-profiling.svg
   :alt: Release Version
-  :target: https://github.com/ydataai/pandas-profiling/releases
+  :target: https://github.com/ydataai/ydata-profiling/releases
 
 .. image:: https://img.shields.io/pypi/pyversions/pandas-profiling
   :alt: Python Version

docsrc/source/pages/getting_started/quickstart.rst

@@ -87,7 +87,7 @@ Information about all available options and arguments can be viewed through the
 Deeper profiling
 ----------------
 
-The contents, behaviour and appearance of the report are easily customizable. The example code below loads the `explorative configuration file <https://github.com/ydataai/pandas-profiling/blob/master/src/ydata_profiling/config_explorative.yaml>`_, 
+The contents, behaviour and appearance of the report are easily customizable. The example code below loads the `explorative configuration file <https://github.com/ydataai/ydata-profiling/blob/master/src/ydata_profiling/config_explorative.yaml>`_, 
 which includes many features for text analysis (length distribution, word distribution and character/unicode information), files (file size, creation time) and images (dimensions, EXIF information). 
 The exact settings used in this explorative configuration file can be compared with the `default configuration file <https://github.com/ydataai/ydata-profiling/blob/master/src/ydata_profiling/config_default.yaml>`_.
 

docsrc/source/pages/integrations/cloud_services.rst

@@ -21,4 +21,4 @@ The Google Cloud Platform documentation features an article that uses ``ydata-pr
 Kaggle
 ------
 
-``ydata-profiling`` is available in `Kaggle notebooks <https://www.kaggle.com/notebooks>`_ by default, as it is included in the `standard Kaggle image <https://github.com/Kaggle/docker-python/blob/master/Dockerfile>`_.
+``ydata-profiling`` is available in `Kaggle notebooks <https://www.kaggle.com/notebooks>`_ by default, as it is included in the `standard Kaggle image <https://github.com/benhamner/docker-python-1/blob/master/Dockerfile>`_.

docsrc/source/pages/integrations/data_apps.rst

@@ -39,7 +39,7 @@ You can install the `pandas-profiling component <https://github.com/Ghasel/strea
 Dash
 ----
 
-`Dash <hhttps://github.com/plotly/dash>`_ is a Python framework for building machine learning & data science web apps, built on top of Plotly.js, React and Flask. It is commonly used for interactive data exploration, precisely where ``ydata-profiling`` also focuses. Inline access to the insights provided by ``pandas-profiling`` can help guide the exploratory work allowed by Dash. To integrate a Profiling Report inside a Dash app, two options exist:
+`Dash <https://github.com/plotly/dash>`_ is a Python framework for building machine learning & data science web apps, built on top of Plotly.js, React and Flask. It is commonly used for interactive data exploration, precisely where ``ydata-profiling`` also focuses. Inline access to the insights provided by ``pandas-profiling`` can help guide the exploratory work allowed by Dash. To integrate a Profiling Report inside a Dash app, two options exist:
 
 Load HTML version of report as an asset 
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

docsrc/source/pages/integrations/great_expectations.rst

@@ -75,7 +75,7 @@ You can also configure each feature individually in the function call:
         handler=handler,
     )
 
-See `the Great Expectations Examples <https://github.com/ydataai/pandas-profiling/blob/master/examples/features/great_expectations_example.py>`_ for complete examples.
+See `the Great Expectations Examples <https://github.com/ydataai/ydata-profiling/blob/master/examples/features/great_expectations_example.py>`_ for complete examples.
 
 
 Included Expectation types
@@ -108,7 +108,7 @@ The ``to_expectation_suite`` method returns a default set of Expectations if ``p
 * ``expect_file_to_exist``
 
 
-The default logic is straight forward and can be found in `expectation_algorithms.py <https://github.com/ydataai/pandas-profiling/blob/master/src/pandas_profiling/model/expectation_algorithms.py>`_.
+The default logic is straight forward and can be found in `expectation_algorithms.py <https://github.com/ydataai/ydata-profiling/blob/master/src/pandas_profiling/model/expectation_algorithms.py>`_.
 
 Rolling your own Expectation Generation Logic
 ---------------------------------------------

docsrc/source/pages/integrations/pipelines.rst

@@ -7,7 +7,7 @@ With Python, command-line and Jupyter interfaces, ``pandas-profiling`` integrate
 Airflow
 -------
 
-Integration with Airflow can be easily achieved through the `BashOperator <https://airflow.apache.org/docs/stable/_api/airflow/operators/bash_operator/index.html>`_ or the `PythonOperator <https://airflow.apache.org/docs/stable/_api/airflow/operators/python_operator/index.html#airflow.operators.python_operator.PythonOperator>`_.
+Integration with Airflow can be easily achieved through the `BashOperator <https://airflow.apache.org/docs/apache-airflow/stable/_api/airflow/operators/bash/index.html>`_ or the `PythonOperator <https://airflow.apache.org/docs/apache-airflow/stable/_api/airflow/operators/python/index.html#airflow.operators.python_operator.PythonOperator>`_.
 
 .. code-block:: python
 

docsrc/source/pages/integrations/pyspark.rst

@@ -91,6 +91,6 @@ ydata-profiling in Databricks
 
 Yes! We have fantastic new coming with a full tutorial on how you can use ydata-profiling in Databricks Notebooks.
 
-The notebook example can be found `here <https://github.com/ydataai/ydata-profiling/tree/master/examples/integrations/databricks_example.ipynb>`_.
+The notebook example can be found `here <https://github.com/ydataai/ydata-profiling/blob/master/examples/integrations/databricks/ydata-profiling%20in%20Databricks.ipynb>`_.
 
 Stay tuned - we are going to update the documentation soon!

docsrc/source/pages/reference/announcements/2020-04-14-release-v2-6-0.rst

@@ -32,6 +32,6 @@ Therefore, we welcome you to support the project through GitHub!
 Find more information here:
 
 - `Sponsor the project on GitHub <https://github.com/sponsors/sbrugman>`_
-- `Read the release notes v2.6.0 <https://github.com/ydataai/pandas-profiling/releases/tag/v2.6.0>`_
+- `Read the release notes v2.6.0 <https://github.com/ydataai/ydata-profiling/releases/tag/v2.6.0>`_
 
 April 14, 2020 💘

docsrc/source/pages/reference/changelog.rst

@@ -2,9 +2,9 @@
 Changelog
 =========
 
-.. include:: changelog/v4_1_0.md
-   :parser: myst_parser.sphinx_
-
+.. include:: changelog/v4_1_0.md
+   :parser: myst_parser.sphinx_
+
 .. include:: changelog/v4_0_0.md
    :parser: myst_parser.sphinx_
 
@@ -61,4 +61,4 @@ Changelog
 Prior to v2.7.0
 ---------------
 
-Previously, there was no explicit changelog. However, changes were included in the release description on GitHub, which you can find `in this page <https://github.com/ydataai/pandas-profiling/releases>`_.
+Previously, there was no explicit changelog. However, changes were included in the release description on GitHub, which you can find `in this page <https://github.com/ydataai/ydata-profiling/releases>`_.