docs(arrays): update blog post to include unnest examples

docs/posts/bigquery-arrays/index.qmd

@@ -26,20 +26,22 @@ First we'll connect to BigQuery and pluck out a table to work with.
 We'll start with `from ibis.interactive import *` for maximum convenience.
 
 ```{python}
-from ibis.interactive import *
+from ibis.interactive import *  # <1>
 
-con = ibis.connect("bigquery://ibis-gbq")  # <1>
-con.set_database("bigquery-public-data.imdb")  # <2>
+con = ibis.connect("bigquery://ibis-gbq")  # <2>
+con.set_database("bigquery-public-data.imdb")  # <3>
 ```
 
-1. Connect to the **billing** project. Compute (but not storage) is billed to
-   this project.
-2. Set the database to the project and dataset that we will use for analysis.
+1. `from ibis.interactive import *` imports Ibis APIs into the global namespace
+   and enables [interactive mode](../../how-to/configure/basics.qmd#interactive-mode).
+2. Connect to Google BigQuery. Compute (but not storage) is billed to the
+   project you connect to--`ibis-gbq` in this case.
+3. Set the database to the project and dataset that we will use for analysis.
 
 Let's look at the tables in this dataset:
 
 ```{python}
-con.list_tables()
+con.tables
 ```
 
 Let's pull out the `name_basics` table, which contains names and metadata about
@@ -136,7 +138,7 @@ non_actors
 We can remove elements from arrays too.
 
 ::: {.callout-note}
-## `remove()` does not mutate the underlying data
+## [`remove()`](../../reference/expression-collections.qmd#ibis.expr.types.arrays.ArrayValue.remove) does not mutate the underlying data
 :::
 
 Let's see who only has "actor" in the list of their primary professions:
@@ -169,7 +171,7 @@ and
 [`intersect`](../../reference/expression-collections.qmd#ibis.expr.types.arrays.ArrayValue.intersect)
 APIs.
 
-### Union
+Let's take a look at `intersect`:
 
 ### Intersection
 
@@ -197,35 +199,92 @@ shared_titles
 
 ## Advanced operations
 
-### `unnest`
+### Flatten arrays into rows
 
-As of version 7.0.0 Ibis does not support its native `unnest` API for BigQuery,
-but we plan to add it in the future.
+Thanks to the [tireless
+efforts](https://github.com/tobymao/sqlglot/commit/06e0869e7aa5714d77e6ec763da38d6a422965fa)
+of the [folks](https://github.com/tobymao/sqlglot/graphs/contributors) working
+on [`sqlglot`](https://github.com/tobymao/sqlglot), as of version 7.0.0 Ibis
+supports
+[`unnest`](../../reference/expression-collections.qmd#ibis.expr.types.arrays.ArrayValue.unnest)
+for BigQuery!
 
-For now, you can use `con.sql` to construct an Ibis expression from a BigQuery
-SQL string that contains `UNNEST` calls:
+You can use it standalone on a column expression:
 
-Despite lack of native `UNNEST` support, many use cases for `UNNEST` are met by
-the
-[`filter`](../../reference/expression-collections.qmd#ibis.expr.types.arrays.ArrayValue.filter)
-and
-[`map`](../../reference/expression-collections.qmd#ibis.expr.types.arrays.ArrayValue.map)
-operations on array expressions.
+```{python}
+ents.primary_profession.unnest()
+```
+
+You can also use it in `select`/`mutate` calls to expand the table accordingly:
+
+```{python}
+ents.mutate(primary_profession=_.primary_profession.unnest())
+```
+
+Unnesting can be useful when joining nested data.
+
+Here we use unnest to find people known for any of the godfather movies:
+
+```{python}
+basics = con.tables.title_basics.filter(  # <1>
+    [
+        _.title_type == "movie",
+        _.original_title.lower().startswith("the godfather"),
+        _.genres.lower().contains("crime"),
+    ]
+)  # <1>
+
+known_for_the_godfather = (
+    ents.mutate(tconst=_.known_for_titles.unnest())  # <2>
+    .join(basics, "tconst")  # <3>
+    .select("primary_title", "primary_name")  # <4>
+    .distinct()
+    .order_by(["primary_title", "primary_name"]) # <4>
+)
+known_for_the_godfather
+```
+
+1. Filter the `title_basics` data set to only the Godfather movies
+2. Unnest the `known_for_titles` array column
+3. Join with `basics` to get movie titles
+4. Ensure that each entity is only listed once and sort the results
+
+Let's summarize by showing how many people are known for each Godfather movie:
+
+```{python}
+known_for_the_godfather.primary_title.value_counts()
+```
 
 ### Filtering array elements
 
-Show all people who are neither editors nor actors:
+Filtering array elements can be done with the
+[`filter`](../../reference/expression-collections.qmd#ibis.expr.types.arrays.ArrayValue.filter)
+method, which applies a predicate to each array element and returns an array of
+elements for which the predicate returns `True`.
+
+This method is similar to Python's
+[`filter`](https://docs.python.org/3.7/library/functions.html#filter) function.
+
+Let's show all people who are neither editors nor actors:
 
 ```{python}
 ents.mutate(
-    primary_profession=_.primary_profession.filter(
-        lambda pp: pp.isin(("actor", "editor"))
+    primary_profession=_.primary_profession.filter(  # <1>
+        lambda pp: ~pp.isin(("actor", "editor"))
     )
-).filter(_.primary_profession.length() > 0)
+).filter(_.primary_profession.length() > 0)  # <2>
 ```
 
+1. This `filter` call is applied to each array element
+2. This `filter` call is applied to the table
+
 ### Applying a function to array elements
 
+You can apply a function to run an ibis expression on each element of an array
+using the
+[`map`](../../reference/expression-collections.qmd#ibis.expr.types.arrays.ArrayValue.map)
+method.
+
 Let's normalize the case of primary_profession to upper case:
 
 ```{python}