alamb commented on code in PR #11290:
URL: https://github.com/apache/datafusion/pull/11290#discussion_r1667770413
##########
docs/source/library-user-guide/using-the-dataframe-api.md:
##########
@@ -19,129 +19,268 @@
# Using the DataFrame API
-## What is a DataFrame
+The [Users Guide] introduces the [`DataFrame`] API and this section describes
+that API in more depth.
-`DataFrame` in `DataFrame` is modeled after the Pandas DataFrame interface,
and is a thin wrapper over LogicalPlan that adds functionality for building and
executing those plans.
+## What is a DataFrame?
-```rust
-pub struct DataFrame {
- session_state: SessionState,
- plan: LogicalPlan,
-}
-```
-
-You can build up `DataFrame`s using its methods, similarly to building
`LogicalPlan`s using `LogicalPlanBuilder`:
-
-```rust
-let df = ctx.table("users").await?;
+As described in the [Users Guide], DataFusion [`DataFrame`]s are modeled after
+the [Pandas DataFrame] interface, and are implemented as thin wrapper over a
+[`LogicalPlan`] that adds functionality for building and executing those plans.
-// Create a new DataFrame sorted by `id`, `bank_account`
-let new_df = df.select(vec![col("id"), col("bank_account")])?
- .sort(vec![col("id")])?;
-
-// Build the same plan using the LogicalPlanBuilder
-let plan = LogicalPlanBuilder::from(&df.to_logical_plan())
- .project(vec![col("id"), col("bank_account")])?
- .sort(vec![col("id")])?
- .build()?;
-```
-
-You can use `collect` or `execute_stream` to execute the query.
+The simplest possible dataframe is one that scans a table and that table can be
+in a file or in memory. I think this might be worth including in the
+introduction.
Review Comment:
🤦
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