docs: update readme with advent of code (#1516)

fabclmnt · boris-kogan · renovate[bot] · web-flow · commit 8c6c3151697c · 2023-12-06T22:39:31.000-05:00
* Update duplicates_pandas.py (#1427) Fixing Bug Report #1384 Dataset with categorical features causes memory error even on tiny dataset. * chore(actions): update sonarsource/sonarqube-scan-action action to v2.0.1 * chore(actions): update actions/checkout action to v4 * docs: setup new docs with mkdocs (#1418) * chore(actions): update actions/checkout action to v4 * fix: remove the duplicated cardinality threshold under categorical and text settings * fix: fixate matplotlib upper version * docs: change from `zap` to `sparkles` (#1447) Co-authored-by: Fabiana <30911746+fabclmnt@users.noreply.github.com> * fix: template {{ file_name }} error in HTML wrapper (#1380) * Update javascript.html * Update style.html * feat: add density histogram (#1458) * feat: add histogram density option * test: add unit test * fix: discard weights if exceed max_bins * docs: update README.html (#1461) Update url of use cases, main integrations, and common issues. * fix: bug when creating a new report (#1440) * fix: gen wordcloud only for non-empty cols (#1459) * fix: table template ignoring text format (#1462) * fix: table template ignoring text format * fix: timeseries unit test * fix(linting): code formatting --------- Co-authored-by: Azory YData Bot <azory@ydata.ai> * fix: to_category misshandling pd.NA (#1464) * docs: add 📊 for Key features (#1451) See also #1445 (comment) * docs: fix hyperlink - related to package name change (#1457) Co-authored-by: Martin Mokry <martin-kokos@users.noreply.github.com> * chore(deps): increase numpy upper limit (#1467) * chore(deps): increase numpy upper limit * chore(deps): fixate numpy version for spark * chore(deps): fix numba package version, and filter warns (#1468) * chore: fix numba package version, and filter warns * fix: skip isort linter on init * chore(deps): update dependency typeguard to v4 (#1324) * chore(deps): update dependency typeguard to v4 --------- Co-authored-by: renovate[bot] <29139614+renovate[bot]@users.noreply.github.com> Co-authored-by: Maciej Bukczynski <maciej@darkhorseanalytics.com> * docs: update docs with advent of code * docs: update links for fabric --------- Co-authored-by: boris-kogan <139680785+boris-kogan@users.noreply.github.com> Co-authored-by: renovate[bot] <29139614+renovate[bot]@users.noreply.github.com> Co-authored-by: Vasco Ramos <vasco.ramos@ydata.ai> Co-authored-by: ricardodcpereira <ricardo.pereira@ydata.ai> Co-authored-by: Anselm Hahn <Anselm.Hahn@gmail.com> Co-authored-by: Joge <87136119+jogecodes@users.noreply.github.com> Co-authored-by: Alex Barros <alexbarros@users.noreply.github.com> Co-authored-by: Miriam Seoane Santos <68821478+miriamspsantos@users.noreply.github.com> Co-authored-by: Chris Mahoney <44449504+chrimaho@users.noreply.github.com> Co-authored-by: Azory YData Bot <azory@ydata.ai> Co-authored-by: martin-kokos <4807476+martin-kokos@users.noreply.github.com> Co-authored-by: Martin Mokry <martin-kokos@users.noreply.github.com> Co-authored-by: Maciej Bukczynski <maciej@darkhorseanalytics.com> Co-authored-by: Fabiana Clemente <fabianaclemente@Fabianas-MacBook-Air.local>
diff --git a/.github/workflows/docs.yaml b/.github/workflows/docs.yaml
@@ -64,7 +64,7 @@ jobs:
         git config core.autocrlf false
 
     - name: Setup Python
-      uses: actions/setup-python@v5
+      uses: actions/setup-python@v4
       with:
         python-version: "3.10"
 
diff --git a/.github/workflows/pull-request.yml b/.github/workflows/pull-request.yml
@@ -37,7 +37,7 @@ jobs:
         git config core.autocrlf false
 
     - name: Set up Python 3.8
-      uses: actions/setup-python@v5
+      uses: actions/setup-python@v4
       with:
         python-version: "3.10"
 
@@ -89,7 +89,7 @@ jobs:
     - uses: actions/checkout@v4
 
     - name: Setup Python
-      uses: actions/setup-python@v5
+      uses: actions/setup-python@v4
       with:
         python-version: "3.10"
 
diff --git a/.github/workflows/release-deprecated.yml b/.github/workflows/release-deprecated.yml
@@ -19,7 +19,7 @@ jobs:
     - uses: actions/checkout@v4
 
     - name: Setup Python 3.8
-      uses: actions/setup-python@v5
+      uses: actions/setup-python@v4
       with:
         python-version: "3.8"
       
diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml
@@ -20,7 +20,7 @@ jobs:
       run: echo "value=${GITHUB_REF#refs/*/}" >> $GITHUB_OUTPUT
 
     - name: Setup Python 3.10
-      uses: actions/setup-python@v5
+      uses: actions/setup-python@v4
       with:
         python-version: "3.10"
       
diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml
@@ -53,7 +53,7 @@ jobs:
     - uses: actions/checkout@v4
     
     - name: Setup python
-      uses: actions/setup-python@v5
+      uses: actions/setup-python@v4
       with:
         python-version: ${{ matrix.python-version }}
         architecture: x64
@@ -101,7 +101,7 @@ jobs:
     - uses: actions/checkout@v4
 
     - name: Setup python
-      uses: actions/setup-python@v5
+      uses: actions/setup-python@v4
       with:
         python-version: ${{ matrix.python-version }}
         architecture: x64
@@ -185,7 +185,7 @@ jobs:
     steps:
       - uses: actions/checkout@v4
       - name: Setup python
-        uses: actions/setup-python@v5
+        uses: actions/setup-python@v4
         with:
           python-version: ${{ matrix.python-version }}
           architecture: x64
diff --git a/README.md b/README.md
@@ -30,7 +30,7 @@
 The package outputs a simple and digested analysis of a dataset, including **time-series** and **text**.
 
 > **Looking for a scalable solution that can fully integrate with your database systems?**<br>
-> Leverage YData Fabric Data Catalog to connect to different databases and storages (Oracle, snowflake, PostGreSQL, GCS, S3, etc.) and leverage an interactive and guided profiling experience in Fabric. Check out the [Community Version](https://ydata.ai/ydata-fabric-free-trial).
+> Leverage YData Fabric Data Catalog to connect to different databases and storages (Oracle, snowflake, PostGreSQL, GCS, S3, etc.) and leverage an interactive and guided profiling experience in Fabric. Check out the [Community Version](http://ydata.ai/register?utm_source=ydata-profiling&utm_medium=documentation&utm_campaign=YData%20Fabric%20Community).
 
 ## ▶️ Quickstart
 
diff --git a/docs/advanced_settings/collaborative_data_profiling.md b/docs/advanced_settings/collaborative_data_profiling.md
@@ -56,4 +56,4 @@ users and per project. YData Fabric Data Catalog helps in maintinaing
 regulatory compliance by identifying any sensitive data.
 
 Try today the Catalog experience in with [Fabric Community
-version](https://ydata.ai/ydata-fabric-free-trial)!
+version](http://ydata.ai/register?utm_source=ydata-profiling&utm_medium=documentation&utm_campaign=YData%20Fabric%20Community)!
diff --git a/docs/features/big_data.md b/docs/features/big_data.md
@@ -13,7 +13,7 @@ computation time of the profiling becomes a bottleneck,
 !!! info "Scale in a fully managed system"
     
     Looking for an fully managed system that is able to scale the profiling
-    for large datasets? [Sign up Fabric](https://ydata.ai/ydata-fabric-free-trial)
+    for large datasets? [Sign up Fabric](http://ydata.ai/register?utm_source=ydata-profiling&utm_medium=documentation&utm_campaign=YData%20Fabric%20Community)
     community for distributed data profiling.
 
 ## Pyspark
diff --git a/docs/features/collaborative_data_profiling.md b/docs/features/collaborative_data_profiling.md
@@ -1,9 +1,9 @@
-# Data quality Profiling with a Collaborative experience
+# Data Catalog - A collaborative experience to profile datasets & relational databases
 
-!!! note
+!!! note "Data Catalog with data quality profiling"
 
-    [Sign-up Fabric community](https://ydata.ai/ydata-fabric-free-trial) to try the **data catalog**
-    and **collaborative** experience for data profiling at scale!
+    [Sign-up Fabric community](http://ydata.ai/register?utm_source=ydata-profiling&utm_medium=documentation&utm_campaign=YData%20Fabric%20Community) to try the **data catalog**
+    and **collaborative** experience for datasets and database profiling at scale!
 
 [YData Fabric](https://ydata.ai/products/fabric) is a Data-Centric AI
 development platform. YData Fabric provides all capabilities of
@@ -42,6 +42,10 @@ An interactive experience that allows to drill-down in a comprehensive data prof
 and relationship analysis, providing deep insights into data structure,
 distributions and interactions for improved data preparation.
 
+<p style="text-align:center;">
+<iframe width="560" height="315" src="https://www.youtube.com/embed/9EupCg5YQLE?si=Tuu68p6sj_RzxTBn&amp;clip=UgkxGNvIAcxUiqBSepTZzP2-4evffzjU7aHX&amp;clipt=EJbiBxinoAg" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
+</p>
+
 ### Data quality indexes 
 
 Access and navigate indicators and data quality statistics, such as completeness, uniqueness
@@ -61,4 +65,4 @@ users and per project. YData Fabric Data Catalog helps in maintaining
 regulatory compliance by identifying any sensitive data.
 
 Try today the Catalog experience in with [Fabric Community
-version](https://ydata.ai/ydata-fabric-free-trial)!
+version](http://ydata.ai/register?utm_source=ydata-profiling&utm_medium=documentation&utm_campaign=YData%20Fabric%20Community)!
diff --git a/docs/getting-started/concepts.md b/docs/getting-started/concepts.md
@@ -99,7 +99,7 @@ This section provides a comprehensive profiling over the potential dataset outli
 based on observed variance. 
 The identification of outliers allows the data analyst or scientist to assess whether they are genuine data anomalies or erroneous entries, allowing for informed decisions on whether to retain, transform, or exclude these points in further analyses.
 
-Feature limited to user of the [cloud hosted solution](https://ydata.ai/ydata-fabric-free-trial).
+Feature limited to user of the [cloud hosted solution](http://ydata.ai/register?utm_source=ydata-profiling&utm_medium=documentation&utm_campaign=YData%20Fabric%20Community).
 
 ## Preview data 
 For a quick overview of the data, ydata-profiling provides the following sections that can be easily configure by the user:
diff --git a/docs/index.md b/docs/index.md
@@ -7,12 +7,17 @@ YData-profiling is a leading tool in the data understanding step of the data sci
 complete with statistics and visualizations. The significance of the package lies in how it streamlines the process of
 understanding and preparing data for analysis in a single line of code! If you're ready to get started see the [quickstart](getting-started/quickstart.md)!
 
-!!! question "Scalable solution to integrate with database systems?"
+!!! tip "Advent of Code - Get featured on ydata-profiling"
 
-    Leverage YData Fabric Data Catalog to connect to different databases and storages **(Oracle, snowflake, PostGreSQL, GCS, S3, etc.)**
-    and leverage an interactive and guided profiling experience in [Fabric](https://ydata.ai/products/fabric). 
+    *“I want to get into open source, but I don’t know how.”* - Does this sound familiar to you? Have you been wanting to get more involved with open-source software, but no one’s given you an entry point?
+    
+    That's why we joined [The Advent of code this year](https://zilliz.com/advent-of-code). Contribute to ydata-profiling and win some 🐼🐼 swag!
 
-    Check out the [Community Version](https://ydata.ai/ydata-fabric-free-trial).
+    How can you be part of it?
+    
+    - Give us some love with a Github ⭐
+    - Write an article or create a tutorial like other [members the communit already did.](https://medium.com/@seckindinc/data-profiling-with-python-36497d3a1261)
+    - Feeling adventurous? Contribute with a PR. We have a list of [great issues to get you started.](https://github.com/ydataai/ydata-profiling/issues?q=label%3A%22getting+started+%E2%98%9D%22+)
 
 ![ydata-profiling report](_static/img/ydata-profiling.gif)
 
@@ -42,6 +47,14 @@ To learn more about the package check out [concepts overview](getting-started/co
 ## 📝 Features, functionalities & integrations
 YData-profiling can be used to deliver a variety of different applications. The documentation includes guides, tips and tricks for tackling them:
 
+!!! question "Data Catalog with data profiling for databases & storages"
+
+    Need to profile directly from databases and data storages **(Oracle, snowflake, PostGreSQL, GCS, S3, etc.)**?
+    
+    Try [YData Fabric Data Catalog](https://ydata.ai/products/data_catalog) for interactive and scalable data profiling
+
+    Check out the [free Community Version](http://ydata.ai/register?utm_source=ydata-profiling&utm_medium=documentation&utm_campaign=YData%20Fabric%20Community).
+
 | Features & functionalities                                                   | Description                                                                                 |
 |------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------|
 | [Comparing datasets](features/comparing_datasets.md)                         | Comparing multiple version of the same dataset                                              |
@@ -54,7 +67,7 @@ YData-profiling can be used to deliver a variety of different applications. The
 
 ### Tutorials
 
-Looking for how to use certain features or how to intgrate `ydata-profiling` in your currect stack and workflows,
+Looking for how to use certain features or how to integrate `ydata-profiling` in your currect stack and workflows,
 check our step-by-step tutorials. 
 
 - **How to master exploratory data analysis with ydata-profiling?** Check this [step-by-step tutorial](https://medium.com/ydata-ai/auditing-data-quality-with-pandas-profiling-b1bf1919f856).
diff --git a/docs/integrations/pipelines.md b/docs/integrations/pipelines.md
@@ -13,7 +13,7 @@ similar way as with Airflow.
 !!! tip "Fabric Community version"
     
     [YData Fabric](https://ydata.ai/products/fabric) has a community version that you can start using today to create data workflows with pipelines. 
-    [Sign up here](https://ydata.ai/ydata-fabric-free-trial) and start building your pipelines. ydata-profiling is installed by default in all YData images.
+    [Sign up here](http://ydata.ai/register?utm_source=ydata-profiling&utm_medium=documentation&utm_campaign=YData%20Fabric%20Community) and start building your pipelines. ydata-profiling is installed by default in all YData images.
 
 ![ydata-profiling in a pipeline](../_static/img/profiling_pipelines.png)
 
diff --git a/docsrc/source/pages/reference/changelog/v4_5_1.md b/docsrc/source/pages/reference/changelog/v4_5_1.md
