Chore: Apply suggestions by CodeRabbit

Author: amotl

docs/connect/df/index.md

@@ -4,7 +4,7 @@
 (dataframe-examples)=
 # CrateDB and DataFrame libraries
 
-How to use CrateDB together with popular open-source dataframe libraries.
+How to use CrateDB together with popular open-source DataFrame libraries.
 
 (dask)=
 ## Dask
@@ -83,7 +83,7 @@ and operations for manipulating numerical tables and time series.
 - [Guide to efficient data ingestion to CrateDB with pandas]
 - [Importing Parquet files into CrateDB using Apache Arrow and SQLAlchemy]
 - [pandas code examples]
-- [From data storage to data analysis\: Tutorial on CrateDB and pandas]
+- [From data storage to data analysis: Tutorial on CrateDB and pandas]
 
 
 
@@ -158,7 +158,7 @@ This allows you to easily integrate Polars into your existing data stack.
 
 [Dask code examples]: https://github.com/crate/cratedb-examples/tree/main/by-dataframe/dask
 [Efficient batch/bulk INSERT operations with pandas, Dask, and SQLAlchemy]: https://cratedb.com/docs/python/en/latest/by-example/sqlalchemy/dataframe.html
-[From data storage to data analysis\: Tutorial on CrateDB and pandas]: https://community.cratedb.com/t/from-data-storage-to-data-analysis-tutorial-on-cratedb-and-pandas/1440
+[From data storage to data analysis: Tutorial on CrateDB and pandas]: https://community.cratedb.com/t/from-data-storage-to-data-analysis-tutorial-on-cratedb-and-pandas/1440
 [Guide to efficient data ingestion to CrateDB with pandas]: https://community.cratedb.com/t/guide-to-efficient-data-ingestion-to-cratedb-with-pandas/1541
 [Guide to efficient data ingestion to CrateDB with pandas and Dask]: https://community.cratedb.com/t/guide-to-efficient-data-ingestion-to-cratedb-with-pandas-and-dask/1482
 [Import weather data using Dask]: https://github.com/crate/cratedb-examples/blob/main/topic/timeseries/dask-weather-data-import.ipynb

docs/connect/index.md

@@ -152,7 +152,7 @@ Python
 configure
 Drivers <drivers>
 CLI programs <cli>
-Dataframe libraries <df/index>
+DataFrame libraries <df/index>
 ORM libraries <orm>
 ```
 

docs/integrate/apache-kafka/index.md

@@ -18,8 +18,8 @@ data integration, and mission-critical applications.
 
 
 :::{dropdown} **Managed Kafka**
-A few companies are specializing in offering managed Kafka services. We can't list
-them all, see the [overview about more managed Kafka offerings].
+Several companies provide managed Kafka services (see the [overview of managed Kafka offerings]
+for a more complete list).
 
 - [Aiven for Apache Kafka]
 - [Amazon Managed Streaming for Apache Kafka (MSK)]
@@ -58,4 +58,4 @@ kafka-connect
 [Confluent Cloud]: https://www.confluent.io/confluent-cloud/
 [CrateDB and Apache Kafka]: https://cratedb.com/integrations/cratedb-and-kafka
 [DoubleCloud Managed Service for Apache Kafka]: https://double.cloud/services/managed-kafka/
-[Overview about more managed Kafka offerings]: https://keen.io/blog/managed-apache-kafka-vs-diy/
+[overview of managed Kafka offerings]: https://keen.io/blog/managed-apache-kafka-vs-diy/

docs/integrate/debezium/index.md

@@ -13,10 +13,9 @@
 ```
 
 [Debezium] is an open source distributed platform for change data capture. After
-pointing it at your databases, you are able to subscribe to the event stream of
+pointing it at your databases, you can subscribe to the event stream of
 all database update operations.
 
-
 Debezium is an open source distributed platform for change data capture (CDC).
 It is built on top of Apache Kafka, a distributed streaming platform. It allows
 to capture changes on a source database system, mostly OLTP, and replicate them

docs/integrate/gradio/index.md

@@ -24,3 +24,4 @@ _How to Build Machine Learning APIs Using Gradio._
 
 
 [Gradio]: https://www.gradio.app/
+[Hugging Face]: https://en.wikipedia.org/wiki/Hugging_Face

docs/integrate/metabase/index.md

@@ -6,7 +6,7 @@
 ```
 
 [Metabase] is the ultimate data analysis and visualization tool that unlocks the full
-potential of your data. Build for data and made for everyone, Metabase can be leveraged
+potential of your data. Built for data and made for everyone, Metabase can be leveraged
 with no SQL required.
 
 Fast analytics with the friendly UX and integrated tooling to let your company explore

docs/integrate/powerbi/index.md

@@ -14,12 +14,12 @@ data analytics and visualizations. Using Power BI Desktop, users can create repo
 and dashboards from large datasets.
 
 For connecting to CrateDB with Power BI, you can use the [Power Query PostgreSQL connector].
-Earlier versions used the [PostgreSQL ODBC driver]. [](inv:guide#powerbi-desktop) walks
+Earlier versions used the [PostgreSQL ODBC driver]. [](project:#powerbi-desktop) walks
 you through the process of configuring that correctly.
 
 [Power BI Service] is an online data analysis and visualization tool, making it
 possible to publish your dashboards, in order to share them with others.
-[](inv:guide#powerbi-service) has a corresponding tutorial.
+[](project:#powerbi-service) has a corresponding tutorial.
 
 ![](https://cratedb.com/docs/crate/howtos/en/latest/_images/powerbi-table-navigator.png){h=160px}
 ![](https://cratedb.com/docs/crate/howtos/en/latest/_images/powerbi-pie-chart.png){h=160px}

docs/integrate/streamlit/index.md

@@ -26,5 +26,4 @@ out Python data applications. It provides fast, interactive prototyping, and liv
 _Streamlit 101 - A faster way to build and share data applications._
 
 
-[Hugging Face]: https://en.wikipedia.org/wiki/Hugging_Face
 [Streamlit]: https://streamlit.io/

docs/integrate/tableau/index.md

@@ -19,7 +19,7 @@ data by translating drag-and-drop actions into data queries through an intuitive
 :::
 
 - [Connecting to CrateDB from Tableau with JDBC] and [Using CrateDB with Tableau]
-  will guide you through the process of setting it Tableau correctly with CrateDB.
+  will guide you through the process of setting up Tableau correctly with CrateDB.
 - The [CrateDB Tableau Connector] unlocks advanced SQL functionality and
   resolves compatibility issues beyond standard usage.