fix: update repository links (#1141)

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/pandas-profiling/pandas-profiling/issues/new/choose).
+  _Related_: [#7][i7], [#129][i129], [#190][i190], [#204][i204] or [create one](https://github.com/ydataai/pandas-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/pandas-profiling/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/pandas-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/pandas-profiling/pandas-profiling/issues/new/choose).
+  _Related_: [#98][i98], [#122][i122] or [create one](https://github.com/ydataai/pandas-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/pandas-profiling/pandas-profiling/issues/new/choose).
+  _Related_: [#161][i161], [#175][i175], [#191][i191] or [create one](https://github.com/ydataai/pandas-profiling/issues/new/choose).
 
 - **Community**: 
   The success of this package demonstrates the power of sharing and working together.
@@ -55,18 +55,18 @@ In line with our aim, we identify the following themes:
   _Suggestions for contribution_:
   Share with us if this package is of value to you, let us know [at this address](mailto:[email protected]).
   We are interested in how you use `pandas-profiling` in your work.
-  Furthermore, we are always looking for contributions to the documentation, issue templates and [discussions](https://github.com/pandas-profiling/pandas-profiling/issues?q=is%3Aissue+is%3Aopen+label%3Adiscussion).
+  Furthermore, we are always looking for contributions to the documentation, issue templates and [discussions](https://github.com/ydataai/pandas-profiling/issues?q=is%3Aissue+is%3Aopen+label%3Adiscussion).
   Advocate, ambassador, share
 
-  _Related_: [#87][i87] or [create one](https://github.com/pandas-profiling/pandas-profiling/issues/new/choose).
+  _Related_: [#87][i87] or [create one](https://github.com/ydataai/pandas-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.
   Future work might include an extension to `pandas-profiling`, specific for profiling of target variables and machine learning predictions.
 
-  _Related_: [#124][i124], [#173][i173], [#198][i198] or [create one](https://github.com/pandas-profiling/pandas-profiling/issues/new/choose).
+  _Related_: [#124][i124], [#173][i173], [#198][i198] or [create one](https://github.com/ydataai/pandas-profiling/issues/new/choose).
 
 #### Support
 Maintaining the package takes up quite some time, which is all donated voluntarily.
@@ -78,9 +78,9 @@ Another low-threshold way to support is to connect your company's logo to the pa
 
 #### **Did you find a bug?**
 
-* **Ensure the bug was not already reported** by searching on Github under [Issues](https://github.com/pandas-profiling/pandas-profiling/issues).
+* **Ensure the bug was not already reported** by searching on Github under [Issues](https://github.com/ydataai/pandas-profiling/issues).
 
-* If you're unable to find an open issue addressing the problem, [open a new one](https://github.com/pandas-profiling/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/pandas-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?**
@@ -95,19 +95,19 @@ 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/pandas-profiling/pandas-profiling/graphs/contributors)
-
-[i7]: https://github.com/pandas-profiling/pandas-profiling/issues/7
-[i129]: https://github.com/pandas-profiling/pandas-profiling/issues/129
-[i190]: https://github.com/pandas-profiling/pandas-profiling/issues/190
-[i204]: https://github.com/pandas-profiling/pandas-profiling/issues/204
-[i98]: https://github.com/pandas-profiling/pandas-profiling/issues/98
-[i122]: https://github.com/pandas-profiling/pandas-profiling/issues/122
-[i124]: https://github.com/pandas-profiling/pandas-profiling/issues/24
-[i173]: https://github.com/pandas-profiling/pandas-profiling/issues/173
-[i198]: https://github.com/pandas-profiling/pandas-profiling/issues/198
-[i87]: https://github.com/pandas-profiling/pandas-profiling/issues/87
-[i161]: https://github.com/pandas-profiling/pandas-profiling/issues/161
-[i175]: https://github.com/pandas-profiling/pandas-profiling/issues/175
-[i191]: https://github.com/pandas-profiling/pandas-profiling/issues/191
+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
 

docsrc/source/pages/advanced_usage/changing_settings.rst

@@ -50,8 +50,8 @@ Through a custom configuration file
 
 To control ``pandas-profiling`` through a custom file, you can start with one of the sample configuration files below:
 
-- `default configuration file <https://github.com/pandas-profiling/pandas-profiling/blob/master/src/pandas_profiling/config_default.yaml>`_ (default)
-- `minimal configuration file <https://github.com/pandas-profiling/pandas-profiling/blob/master/src/pandas_profiling/config_minimal.yaml>`_ (minimal computation, optimized for performance)
+- `default configuration file <https://github.com/ydataai/pandas-profiling/blob/master/src/pandas_profiling/config_default.yaml>`_ (default)
+- `minimal configuration file <https://github.com/ydataai/pandas-profiling/blob/master/src/pandas_profiling/config_minimal.yaml>`_ (minimal computation, optimized for performance)
 
 Change the configuration to your liking and point towards that configuration file when computing the report:  
 

docsrc/source/pages/integrations/data_apps.rst

@@ -114,4 +114,4 @@ When running ``python app.py``, a Dash app with the report embedded will be avai
 Panel
 -----
 
-For more information on how to use ``pandas-profiling`` in Panel, see `this GitHub issue <https://github.com/pandas-profiling/pandas-profiling/issues/491>`_ and `this integration example <https://awesome-panel.org/pandas_profiling_app>`_.
+For more information on how to use ``pandas-profiling`` in Panel, see `this GitHub issue <https://github.com/ydataai/pandas-profiling/issues/491>`_ and `this integration example <https://awesome-panel.org/pandas_profiling_app>`_.

docsrc/source/pages/integrations/great_expectations.rst

@@ -69,7 +69,7 @@ You can also configure each feature individually in the function call:
         handler=handler,
     )
 
-See `the Great Expectations Examples <https://github.com/pandas-profiling/pandas-profiling/blob/master/examples/features/great_expectations_example.py>`_ for complete examples.
+See `the Great Expectations Examples <https://github.com/ydataai/pandas-profiling/blob/master/examples/features/great_expectations_example.py>`_ for complete examples.
 
 
 Included Expectation types
@@ -102,7 +102,7 @@ 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/pandas-profiling/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/pandas-profiling/blob/master/src/pandas_profiling/model/expectation_algorithms.py>`_.
 
 Rolling your own Expectation Generation Logic
 ---------------------------------------------

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/pandas-profiling/pandas-profiling/releases/tag/v2.6.0>`_
+- `Read the release notes v2.6.0 <https://github.com/ydataai/pandas-profiling/releases/tag/v2.6.0>`_
 
 April 14, 2020 💘

docsrc/source/pages/reference/changelog/v2_10_1.rst

@@ -3,13 +3,13 @@ Changelog v2.10.1
 
 🐛 Bug fixes
 ^^^^^^^^^^^^
-- Fixed recursion error for NaN values `[683] <https://github.com/pandas-profiling/pandas-profiling/issues/683>`_ and `[671] <https://github.com/pandas-profiling/pandas-profiling/issues/671>`_
-- Fixed error for empty dataframe `[664] <https://github.com/pandas-profiling/pandas-profiling/issues/664>`_
-- Fixed Jupyter notebook widget string rendering issue `[668] <https://github.com/pandas-profiling/pandas-profiling/issues/668>`_
-- Fixed histogram of string length with NaNs `[642] <https://github.com/pandas-profiling/pandas-profiling/issues/642>`_ and `[613] <https://github.com/pandas-profiling/pandas-profiling/issues/613>`_
-- Fixed slugify logic for interaction columns `[663] <https://github.com/pandas-profiling/pandas-profiling/issues/663>`_
+- Fixed recursion error for NaN values `[683] <https://github.com/ydataai/pandas-profiling/issues/683>`_ and `[671] <https://github.com/ydataai/pandas-profiling/issues/671>`_
+- Fixed error for empty dataframe `[664] <https://github.com/ydataai/pandas-profiling/issues/664>`_
+- Fixed Jupyter notebook widget string rendering issue `[668] <https://github.com/ydataai/pandas-profiling/issues/668>`_
+- Fixed histogram of string length with NaNs `[642] <https://github.com/ydataai/pandas-profiling/issues/642>`_ and `[613] <https://github.com/ydataai/pandas-profiling/issues/613>`_
+- Fixed slugify logic for interaction columns `[663] <https://github.com/ydataai/pandas-profiling/issues/663>`_
 
 📖 Documentation
 ^^^^^^^^^^^^^^^^
-- Update Slack community link on readme `[673] <https://github.com/pandas-profiling/pandas-profiling/issues/673>`_
+- Update Slack community link on readme `[673] <https://github.com/ydataai/pandas-profiling/issues/673>`_
 - Include recent contributions to the "Resources" page.

docsrc/source/pages/reference/changelog/v2_11_0.rst

@@ -3,8 +3,8 @@ Changelog v2.11.0
 
 🎉 Features
 ^^^^^^^^^^^
-- Great Expectations integration `[430] <https://github.com/pandas-profiling/pandas-profiling/issues/430>`_ `docs <https://pandas-profiling.github.io/pandas-profiling/docs/master/pages/great_expectations_integration.html>`_ (thanks @spbail, @talagluck and the Great Expectations team).
-- Introduced the ``infer_dtypes`` parameter to control automatic inference of data types `[676] <https://github.com/pandas-profiling/pandas-profiling/issues/676>`_ (thanks @mohith7548 and @ieaves).
+- Great Expectations integration `[430] <https://github.com/ydataai/pandas-profiling/issues/430>`_ `docs <https://pandas-profiling.github.io/pandas-profiling/docs/master/pages/great_expectations_integration.html>`_ (thanks @spbail, @talagluck and the Great Expectations team).
+- Introduced the ``infer_dtypes`` parameter to control automatic inference of data types `[676] <https://github.com/ydataai/pandas-profiling/issues/676>`_ (thanks @mohith7548 and @ieaves).
 - Improved JSON representation for pd.Series, pd.DataFrame, numpy data and Samples.
 
 🚨 Breaking changes

docsrc/source/pages/reference/changelog/v2_12_0.rst

@@ -3,14 +3,14 @@ Changelog v2.12.0
 
 🎉 Features
 ^^^^^^^^^^^
-- Add the number and the percentage of negative values for numerical variables `[695] <https://github.com/pandas-profiling/pandas-profiling/issues/695>`_ (contributed by @gverbock)
+- Add the number and the percentage of negative values for numerical variables `[695] <https://github.com/ydataai/pandas-profiling/issues/695>`_ (contributed by @gverbock)
 - Enable setting of typeset/summarizer (contributed by @ieaves)
-- Allow empty data frames `[678] <https://github.com/pandas-profiling/pandas-profiling/issues/678>`_ (contributed by @spbail, @fwd2020-c)
+- Allow empty data frames `[678] <https://github.com/ydataai/pandas-profiling/issues/678>`_ (contributed by @spbail, @fwd2020-c)
 
 🐛 Bug fixes
 ^^^^^^^^^^^^
-- Patch args for great_expectations datetime profiler `[727] <https://github.com/pandas-profiling/pandas-profiling/issues/727>`_ (contributed by @jstammers)
-- Negative exponent formatting `[723]  <https://github.com/pandas-profiling/pandas-profiling/issues/723>`_ (reported by @rdpapworth)
+- Patch args for great_expectations datetime profiler `[727] <https://github.com/ydataai/pandas-profiling/issues/727>`_ (contributed by @jstammers)
+- Negative exponent formatting `[723]  <https://github.com/ydataai/pandas-profiling/issues/723>`_ (reported by @rdpapworth)
 
 📖 Documentation
 ^^^^^^^^^^^^^^^^