add sql console section

.gitignore

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 node_modules/
+__pycache__/
 .vscode/
 .idea/
 

docs/hub/datasets-viewer-sql-console.md

@@ -20,5 +20,111 @@ Through the SQL Console, you can:
 - Embed the results of the query in your own webpage using an iframe 
 
 <Tip>
-You can also use a local DuckDB CLI to query the dataset via the `hf://` protocol. See the <a href="https://huggingface.co/docs/hub/en/datasets-duckdb" target="_blank" rel="noopener noreferrer">DuckDB CLI documentation</a> for more information.
-</Tip>
+You can also use the DuckDB CLI to query the dataset via the `hf://` protocol. See the <a href="https://huggingface.co/docs/hub/en/datasets-duckdb" target="_blank" rel="noopener noreferrer">DuckDB CLI documentation</a> for more information. The SQL Console provides a convenient `Copy to DuckDB CLI` button that generates the SQL query for creating views and executing your query in the DuckDB CLI.
+</Tip>
+
+
+# Examples
+
+## Leakage Detection
+
+Leakage detection is the process of identifying whether data in a dataset is present in multiple splits, for example, whether the test set is present in the training set.
+
+<div class="flex justify-center">
+    <img class="block dark:hidden" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/sql_console/leakage-detection.png"/>
+    <img class="hidden dark:block" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/sql_console/leakage-detection-dark.png"/>
+</div>
+
+<p class="text-sm text-center italic">
+    Learn more about leakage detection <a href="https://huggingface.co/blog/lbourdois/lle">here</a>.
+</p>
+
+```sql
+WITH
+    overlapping_rows AS (
+        SELECT COALESCE(
+            (SELECT COUNT(*) AS overlap_count
+             FROM train
+             INTERSECT
+             SELECT COUNT(*) AS overlap_count
+             FROM test),
+            0
+        ) AS overlap_count
+    ),
+    total_unique_rows AS (
+        SELECT COUNT(*) AS total_count
+        FROM (
+            SELECT * FROM train
+            UNION
+            SELECT * FROM test
+        ) combined
+    )
+SELECT
+    overlap_count,
+    total_count,
+    CASE 
+        WHEN total_count > 0 THEN (overlap_count * 100.0 / total_count)
+        ELSE 0
+    END AS overlap_percentage
+FROM overlapping_rows, total_unique_rows;
+```
+
+## Filtering
+
+The SQL Console makes filtering datasets really easily. For example, if you want to filter the `SkunkworksAI/reasoning-0.01` dataset for instructions and responses with a reasoning length of at least 10, you can use the following query:
+
+<div class="flex justify-center">
+    <img class="block dark:hidden" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/sql_console/bar-struct-length.png"/>
+    <img class="hidden dark:block" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/sql_console/bar-struct-length-dark.png"/>
+</div>
+
+In the query, we can use the `len` function to get the length of the `reasoning_chains` column and the `bar` function to create a bar chart of the reasoning lengths.
+
+```sql
+select len(reasoning_chains) as reason_len, bar(reason_len, 0, 100), * 
+from train
+where reason_len > 10
+order by reason_len desc
+```
+
+The [bar](https://duckdb.org/docs/sql/functions/char.html#barx-min-max-width) function is a neat built-in DuckDB function that creates a bar chart of the reasoning lengths.
+
+## Histogram
+
+Many dataset authors choose to include statistics about the distribution of the data in the dataset. Using the DuckDB `histogram` function, we can plot a histogram of a column's values.
+
+For example, to plot a histogram of the `reason_len` column in the `SkunkworksAI/reasoning-0.01` dataset, you can use the following query:
+
+<div class="flex justify-center">
+    <img class="block dark:hidden" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/sql_console/histogram-simple.png"/>
+    <img class="hidden dark:block" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/sql_console/histogram-simple-dark.png"/>
+</div>
+<p class="text-sm text-center italic">
+    Learn more about the `histogram` function and parameters <a href="https://cfahlgren1-sql-snippets.hf.space/histogram" target="_blank" rel="noopener noreferrer">here</a>.
+</p>
+
+```sql
+from histogram(train, len(reasoning_chains))
+```
+
+## Regex Matching
+
+One of the most powerful features of DuckDB is the deep support for regular expressions. You can use the `regexp` function to match patterns in your data.
+
+ Using the [regexp_matches](https://duckdb.org/docs/sql/functions/char.html#regexp_matchesstring-pattern) function, we can filter the `SkunkworksAI/reasoning-0.01` dataset for instructions that contain markdown code blocks.
+
+ <div class="flex justify-center">
+    <img class="block dark:hidden" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/sql_console/regex-matching-markdown-code.png"/>
+    <img class="hidden dark:block" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/sql_console/regex-matching-markdown-code-dark.png"/>
+</div>
+<p class="text-sm text-center italic">
+    Learn more about the DuckDB regex functions <a href="https://duckdb.org/docs/sql/functions/regular_expressions.html" target="_blank" rel="noopener noreferrer">here</a>.
+</p>
+
+
+```sql
+SELECT * 
+FROM train
+WHERE regexp_matches(instruction, '```[a-z]*\n')
+limit 100
+```