feat: rename to data-profiling

.github/ISSUE_TEMPLATE/bug_report_form.yaml

@@ -41,7 +41,7 @@ body:
       description: A minimal standalone code sample that reproduces the bug
       placeholder: |
         import pandas as pd
-        from ydata_profiling import ProfileReport
+        from data_profiling import ProfileReport
 
         df = pd.read_parquet(r"<file>")
         report = ProfileReport(df, title="bug report")

.pre-commit-config.yaml

@@ -16,7 +16,7 @@ repos:
     hooks:
     - id: nbqa-black
     - id: nbqa-isort
-      args: [ --profile=black, --project=ydata_profiling ]
+      args: [ --profile=black, --project=data_profiling ]
     - id: nbqa-pyupgrade
       args: [ --py36-plus ]
 -   repo: https://github.com/asottile/pyupgrade
@@ -29,12 +29,12 @@ repos:
     hooks:
       - id: isort
         files: '.*'
-        args: [ --profile=black, --project=ydata_profiling ]
+        args: [ --profile=black, --project=data_profiling ]
 -   repo: https://github.com/mgedmin/check-manifest
     rev: "0.47"
     hooks:
     -   id: check-manifest
-        args: [ "--ignore=src/ydata_profiling/version.py" ]
+        args: [ "--ignore=src/data_profiling/version.py" ]
         stages: [manual]
 -   repo: https://github.com/PyCQA/flake8
     rev: "4.0.1"
@@ -60,8 +60,8 @@ repos:
           (?x)(
             ^tests/|
             ^docsrc/|
-            ^src/ydata_profiling/utils/common.py|
-            ^src/ydata_profiling/utils/imghdr_patch.py
+            ^src/data_profiling/utils/common.py|
+            ^src/data_profiling/utils/imghdr_patch.py
           )
 -   repo: https://github.com/asottile/blacken-docs
     rev: v1.12.1

CONTRIBUTING.md

@@ -1,8 +1,8 @@
-## How to contribute to YData-Profiling
+## How to contribute to Data-Profiling
 
-YData-profiling aims to ease exploratory data analysis for structured datasets, including time-series. 
+Data-profiling aims to ease exploratory data analysis for structured datasets, including time-series. 
 Our focus is to provide users with useful and robust statistics for such datasets encountered in industry, academia and elsewhere.
-YData-profiling is open-source and stimulates contributions from passionate community users.
+Data-profiling is open-source and stimulates contributions from passionate community users.
 
 
 #### Themes to contribute
@@ -17,23 +17,23 @@ 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/ydata-profiling/issues/new/choose).
+  _Related_: [#7][i7], [#129][i129], [#190][i190], [#204][i204] or [create one](https://github.com/Data-Centric-AI-Community/fg-data-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.
-  `ydata-profiling` helps analysts, researchers and engineers alike in these cases.
+  `fg-data-profiling` helps analysts, researchers and engineers alike in these cases.
   We do this by fixing bugs, improving performance on big datasets and adding environment compatibility.
 
   _Suggestions for contribution (Performance)_: 
-  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 `ydata-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). 
+  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 `fg-data-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/ydata-profiling/issues) and [Stackoverflow tag](https://stackoverflow.com/questions/tagged/ydata-profiling) to find current issues.
+  Either review the code and add tests or watch the [issues page](https://github.com/Data-Centric-AI-Community/fg-data-profiling/issues) and [Stackoverflow tag](https://stackoverflow.com/questions/tagged/ydata-profiling) to find current issues.
 
-  _Related_: [#98][i98], [#122][i122] or [create one](https://github.com/ydataai/ydata-profiling/issues/new/choose).
+  _Related_: [#98][i98], [#122][i122] or [create one](https://github.com/Data-Centric-AI-Community/fg-data-profiling/issues/new/choose).
 
 - **Interaction, presentation and user experience**: 
-  As `ydata-profiling` eases exploratory data analysis, working with the package should reflect that.
+  As `fg-data-profiling` eases exploratory data analysis, working with the package should reflect that.
   Interaction and user experience plays a central role in working with the package.
   Working on interactive and static features is possible through the modular nature of the package: the user can configure which features to use.
 
@@ -46,30 +46,30 @@ 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/ydata-profiling/issues/new/choose).
+  _Related_: [#161][i161], [#175][i175], [#191][i191] or [create one](https://github.com/Data-Centric-AI-Community/fg-data-profiling/issues/new/choose).
 
 - **Community**: 
   The success of this package demonstrates the power of sharing and working together.
   You are welcome as part of this community.
 
   _Suggestions for contribution_:
   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 `ydata-profiling` in your work.
+  We are interested in how you use `fg-data-profiling` in your work.
 
-  _Related_: [#87][i87] or [create one](https://github.com/ydataai/ydata-profiling/issues/new/choose).
+  _Related_: [#87][i87] or [create one](https://github.com/Data-Centric-AI-Community/fg-data-profiling/issues/new/choose).
 
 - **Machine learning:** 
-  `ydata-profiling` is not a machine learning package, even though many of our users use EDA as a step prior to developing their models.
+  `fg-data-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/ydata-profiling/issues/new/choose).
+  _Related_: [#124][i124], [#173][i173], [#198][i198] or [create one](https://github.com/Data-Centric-AI-Community/fg-data-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/ydata-profiling/issues).
+* **Ensure the bug was not already reported** by searching on Github under [Issues](https://github.com/Data-Centric-AI-Community/fg-data-profiling/issues).
 
-* 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 you're unable to find an open issue addressing the problem, [open a new one](https://github.com/Data-Centric-AI-Community/fg-data-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/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
+See the [Contributor Graph](https://github.com/Data-Centric-AI-Community/fg-data-profiling/graphs/contributors)
+
+[i7]: https://github.com/Data-Centric-AI-Community/fg-data-profiling/issues/7
+[i129]: https://github.com/Data-Centric-AI-Community/fg-data-profiling/issues/129
+[i190]: https://github.com/Data-Centric-AI-Community/fg-data-profiling/issues/190
+[i204]: https://github.com/Data-Centric-AI-Community/fg-data-profiling/issues/204
+[i98]: https://github.com/Data-Centric-AI-Community/fg-data-profiling/issues/98
+[i122]: https://github.com/Data-Centric-AI-Community/fg-data-profiling/issues/122
+[i124]: https://github.com/Data-Centric-AI-Community/fg-data-profiling/issues/24
+[i173]: https://github.com/Data-Centric-AI-Community/fg-data-profiling/issues/173
+[i198]: https://github.com/Data-Centric-AI-Community/fg-data-profiling/issues/198
+[i87]: https://github.com/Data-Centric-AI-Community/fg-data-profiling/issues/87
+[i161]: https://github.com/Data-Centric-AI-Community/fg-data-profiling/issues/161
+[i175]: https://github.com/Data-Centric-AI-Community/fg-data-profiling/issues/175
+[i191]: https://github.com/Data-Centric-AI-Community/fg-data-profiling/issues/191
 

MANIFEST.in

@@ -6,10 +6,10 @@ include LICENSE
 include *.md
 
 # Templates and static resources
-recursive-include src/ydata_profiling/report/presentation/flavours/html/templates *.html *.js *.css
+recursive-include src/data_profiling/report/presentation/flavours/html/templates *.html *.js *.css
 
 # Configuration
-include src/ydata_profiling/*.yaml
+include src/data_profiling/*.yaml
 
 # Spark Dev venv
 recursive-include venv *.yml

Makefile

@@ -7,17 +7,17 @@ test:
 	pytest tests/unit/
 	pytest tests/issues/
 	pytest --nbval tests/notebooks/
-	ydata_profiling -h
+	data_profiling -h
 
 test_spark:
 	pytest tests/backends/spark_backend/
-	ydata_profiling -h
+	data_profiling -h
 
 test_cov:
 	pytest --cov=. tests/unit/
 	pytest --cov=. --cov-append tests/issues/
 	pytest --cov=. --cov-append --nbval tests/notebooks/
-	ydata_profiling -h
+	data_profiling -h
 
 examples:
 	find ./examples -maxdepth 2 -type f -name "*.py" -execdir python {} \;