fix: update logger version and update docs links

README.md

@@ -7,6 +7,7 @@
 [![Release Version](https://img.shields.io/github/release/ydataai/pandas-profiling.svg)](https://github.com/ydataai/pandas-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)
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=cb7e69df-af81-4352-809a-d4251756affc" />
 
 <p align="center"><img width="300" src="https://assets.ydata.ai/oss/ydata-profiling_black.png" alt="YData Profiling Logo"></p>
 

docs/advanced_settings/analytics.md

@@ -39,4 +39,4 @@ Open your terminal or command prompt and set the YDATA_PROFILING_NO_ANALYTICS en
     os.environ['YDATA_PROFILING_NO_ANALYTICS'] = 'True'
 ````
 
-
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=baa0e45f-0c03-4190-9646-9d8ea2640ba2" />

docs/advanced_settings/available_settings.md

@@ -121,3 +121,5 @@ Settings related with the interactions section.
 Settings related with the appearance and style of the report.
 
 {{ read_csv('./tables/config_html.csv') }}
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=baa0e45f-0c03-4190-9646-9d8ea2640ba2" />

docs/advanced_settings/caching.md

@@ -6,4 +6,6 @@ If you modify the configuration in-between runs, either a new ``ProfileReport``
 
 - *rendering* to invalidate previously rendered reports (HTML, JSON or widgets)
 - *report* to remove the caching of the report's structure
-- *None* (default) to invalidate all caches
+- *None* (default) to invalidate all caches
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=baa0e45f-0c03-4190-9646-9d8ea2640ba2" />

docs/advanced_settings/changing_settings.md

@@ -85,3 +85,5 @@ os.environ("PROFILE_TITLE")='My Custom Profiling Report'
 
 profile = ProfileReport(df)
 ```
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=baa0e45f-0c03-4190-9646-9d8ea2640ba2" />

docs/advanced_settings/collaborative_data_profiling.md

@@ -57,3 +57,5 @@ regulatory compliance by identifying any sensitive data.
 
 Try today the Catalog experience in with [Fabric Community
 version](http://ydata.ai/register?utm_source=ydata-profiling&utm_medium=documentation&utm_campaign=YData%20Fabric%20Community)!
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=2d9fcb48-0fa6-43d8-a0ba-fdad344050fd" />

docs/features/big_data.md

@@ -1,5 +1,7 @@
 # Profiling large datasets
 
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=baa0e45f-0c03-4190-9646-9d8ea2640ba2" />
+
 By default, `ydata-profiling` comprehensively summarizes the input
 dataset in a way that gives the most insights for data analysis. For
 small datasets, these computations can be performed in *quasi*

docs/features/collaborative_data_profiling.md

@@ -69,3 +69,5 @@ regulatory compliance by identifying any sensitive data.
 
 Try today the Catalog experience in with [Fabric Community
 version](http://ydata.ai/register?utm_source=ydata-profiling&utm_medium=documentation&utm_campaign=YData%20Fabric%20Community)!
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=2d9fcb48-0fa6-43d8-a0ba-fdad344050fd" />

docs/features/comparing_datasets.md

@@ -1,5 +1,6 @@
 # Dataset Comparison
 
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=baa0e45f-0c03-4190-9646-9d8ea2640ba2" />
 !!! note "Dataframes compare support"
 
     Profiling compare is supported from

docs/features/custom_reports.md

@@ -89,4 +89,6 @@ Similarly, the palette for *Missing values* can be changed using ``missing`` arg
 
 ``ydata-profiling`` accepts all ``cmap`` values (colormaps) accepted by ``matplotlib``.
 The list of available colour maps can [be accessed here](https://matplotlib.org/stable/tutorials/colors/colormaps.html>).
-Alternatively, it is possible to create [custom palettes](https://matplotlib.org/stable/gallery/color/custom_cmap.html>).
+Alternatively, it is possible to create [custom palettes](https://matplotlib.org/stable/gallery/color/custom_cmap.html>).
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=baa0e45f-0c03-4190-9646-9d8ea2640ba2" />

docs/features/metadata.md

@@ -112,3 +112,5 @@ report = ProfileReport(df, title="Titanic EDA", type_schema=type_schema)
 
 report.to_file("report.html")
 ```
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=baa0e45f-0c03-4190-9646-9d8ea2640ba2" />

docs/features/pii_identification_management.md

@@ -56,4 +56,4 @@ Data governance involves establishing policies and processes to ensure high data
 A PII management solution enhances data governance efforts by providing a centralized hub for overseeing PII classifications,
 metadata, and related policies.
 
-
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=2d9fcb48-0fa6-43d8-a0ba-fdad344050fd" />

docs/features/sensitive_data.md

@@ -59,4 +59,6 @@ help developers solve these cases, was developed.
 
 ## Automated PII classification & management
 
-You can find more details about this feature [here](pii_identification_management.md).
+You can find more details about this feature [here](pii_identification_management.md).
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=baa0e45f-0c03-4190-9646-9d8ea2640ba2" />

docs/features/time_series_datasets.md

@@ -151,4 +151,6 @@ profile = ProfileReport(
 profile.to_file("report_timeseries.html")
 ```
 
-For more questions and suggestions around time-series analysis reach us out at the [Data-Centric AI community](https://datacentricai.community/).
+For more questions and suggestions around time-series analysis reach us out at the [Data-Centric AI community](https://datacentricai.community/).
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=baa0e45f-0c03-4190-9646-9d8ea2640ba2" />

docs/getting-started/concepts.md

@@ -1,4 +1,4 @@
-#Concepts
+# Concepts
 
 !!! question "Text/corpus data - your input is needed!"
 
@@ -106,3 +106,5 @@ For a quick overview of the data, ydata-profiling provides the following section
 - First n records of a given dataset
 - Last n records of a given dataset
 - A table containing observed duplicates (exact matches)
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=baa0e45f-0c03-4190-9646-9d8ea2640ba2" />

docs/getting-started/examples.md

@@ -46,3 +46,5 @@ across a wide range of dataset and data types:
 -   [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)
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=baa0e45f-0c03-4190-9646-9d8ea2640ba2" />

docs/getting-started/installation.md

@@ -78,3 +78,5 @@ Install these with e.g.
 ````console
   pip install -U ydata-profiling[notebook,unicode, pyspark]
 ````
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=baa0e45f-0c03-4190-9646-9d8ea2640ba2" />

docs/getting-started/quickstart.md

@@ -99,3 +99,5 @@ profile = ProfileReport(df, title="Profiling Report", explorative=True)
 On the CLI utility `ydata_profiling`, this mode can be activated with
 the `-e` flag. Learn more about configuring `ydata-profiling` on the
 `../advanced_usage/available_settings`{.interpreted-text role="doc"}.
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=baa0e45f-0c03-4190-9646-9d8ea2640ba2" />

docs/index.md

@@ -1,5 +1,6 @@
 # Welcome
 
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=baa0e45f-0c03-4190-9646-9d8ea2640ba2" />
 Data quality profiling and exploratory data analysis are crucial steps in the process of Data Science and Machine Learning development. 
 YData-profiling is a leading tool in the data understanding step of the data science workflow as a pioneering Python package. 
 

docs/integrations/bytewax.md

@@ -185,4 +185,6 @@ comparison_report.to_file("comparison_report.html")
 Now you're all set to start exploring your data streams! Bytewax takes
 care of all the processes necessary to handle and structure data streams
 into snapshots, which can then be summarized and compared with
-ydata-profiling through a comprehensive report of data characteristics.
+ydata-profiling through a comprehensive report of data characteristics.
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=baa0e45f-0c03-4190-9646-9d8ea2640ba2" />

docs/integrations/great_expectations.md

@@ -107,4 +107,6 @@ suite = profile.to_expectation_suite(
 
 See [the Great Expectations
 Examples](https://github.com/ydataai/ydata-profiling/blob/master/examples/features/great_expectations_example.py)
-for complete examples.
+for complete examples.
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=baa0e45f-0c03-4190-9646-9d8ea2640ba2" />

docs/integrations/ides.md

@@ -39,3 +39,5 @@ width="400px"}
 
 To use the PyCharm Integration, right click on any dataset file and
 *External Tools* \ *Data Profiling*.
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=baa0e45f-0c03-4190-9646-9d8ea2640ba2" />

docs/integrations/interactive_applications.md

@@ -127,3 +127,5 @@ in Panel, see \`this GitHub issue
 \<https://github.com/ydataai/ydata-profiling/issues/491\>]{.title-ref}\_
 and [this integration
 example](https://awesome-panel.org/pandas_profiling_app).
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=baa0e45f-0c03-4190-9646-9d8ea2640ba2" />

docs/integrations/other_dataframe_libraries.md

@@ -32,3 +32,5 @@ df = df.to_pandas_df()
 # Convert modin DataFrame to pandas DataFrame
 df = df._to_pandas()
 ```
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=baa0e45f-0c03-4190-9646-9d8ea2640ba2" />

docs/integrations/pipelines.md

@@ -100,3 +100,5 @@ profiling_task2 = PythonOperator(
 
 There is a community created [Kedro
 plugin](https://github.com/BrickFrog/kedro-pandas-profiling) available.
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=2d9fcb48-0fa6-43d8-a0ba-fdad344050fd" />

docs/integrations/pyspark.md

@@ -128,3 +128,5 @@ The notebook example can be found
 [here](https://github.com/ydataai/ydata-profiling/tree/master/examples/integrations/databricks_example.ipynb).
 
 Stay tuned - we are going to update the documentation soon!
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=c3c3ddfc-4c47-4192-9105-5dac1ffa3a49" />

docs/reference/history.md

@@ -85,3 +85,5 @@ New features are expected, and it will be important to learn from you
 your needs and expectations so the future can be even brighter. Join the
 :fontawesome-brands-discord: [DCAI community](https://datacentricai.community/) and let us know your
 thoughts.
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=baa0e45f-0c03-4190-9646-9d8ea2640ba2" />

docs/reference/resources.md

@@ -112,3 +112,5 @@ Feel free to contribute it via a pull request on GitHub.
     (PMLB)](https://epistasislab.github.io/pmlb/)
     ([description](https://arxiv.org/ftp/arxiv/papers/2012/2012.00058.pdf))
 -   [dabl package](https://github.com/dabl/dabl)
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=baa0e45f-0c03-4190-9646-9d8ea2640ba2" />

docs/support-contribution/common_issues.md

@@ -42,3 +42,5 @@ computation.
 Related StackOverflow questions:
 -   [MemoryError when using ydata_profiling
     profile_report](https://stackoverflow.com/questions/67342168/memoryerror-when-using-pandas-profiling-profile-report)
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=baa0e45f-0c03-4190-9646-9d8ea2640ba2" />

docs/support-contribution/contribution_guidelines.md

@@ -85,3 +85,5 @@ community](https://discord.com/invite/mw7xjJ7b7s).
 
 Read more on getting involved in the [Contribution Guide available on
 GitHub](https://github.com/ydataai/ydata-profiling/blob/master/CONTRIBUTING.md).
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=baa0e45f-0c03-4190-9646-9d8ea2640ba2" />

docs/support-contribution/help_troubleshoot.md

@@ -83,3 +83,5 @@ for questions about `ydata-profiling` older versions.
 connect with both other users and developers that might be able to
 answer your questions. The **#ydata-profiling** and **#need-help**
 channels are recommended for questions and issues.
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=baa0e45f-0c03-4190-9646-9d8ea2640ba2" />

src/ydata_profiling/utils/common.py

@@ -98,12 +98,14 @@ def convert_timestamp_to_datetime(timestamp: int) -> datetime:
         return datetime(1970, 1, 1) + timedelta(seconds=int(timestamp))
 
 
-def analytics_features(dataframe, datatype: str, report_type: str):
+def analytics_features(dataframe: str, datatype: str, report_type: str) -> None:
     endpoint = "https://packages.ydata.ai/ydata-profiling?"
+    package_version = __version__
 
-    if os.getenv("YDATA_PROFILING_NO_ANALYTICS") != True:
-        package_version = __version__
-
+    if (
+        bool(os.getenv("YDATA_PROFILING_NO_ANALYTICS")) is not True
+        and package_version != "0.0.dev0"
+    ):
         try:
             subprocess.check_output("nvidia-smi")
             gpu_present = True

src/ydata_profiling/utils/logger.py

@@ -14,10 +14,10 @@ def __init__(self, name, level=logging.INFO):
         super().__init__(name, level)
 
     def info_def_report(self, dataframe, timeseries: bool):
-        if dataframe == pd.DataFrame:
+        if dataframe is pd.DataFrame:
             dataframe = "pandas"
             report_type = "regular"
-        elif dataframe == type(None):
+        elif dataframe is type(None):
             dataframe = "pandas"
             report_type = "compare"
         else:

src/ydata_profiling/visualisation/plot.py

@@ -743,7 +743,7 @@ def _plot_acf_pacf(
 
     for ax in axes:
         for item in ax.collections:
-            if type(item) == PolyCollection:
+            if type(item) is PolyCollection:
                 item.set_facecolor(color)
 
     return plot_360_n0sc0pe(config)