polars into-df struct fix (#13977)

# Description
This fixes an issue with converting to a dataframe when specifying a
struct in the schema. Things like the following now work correctly:
```nushell
 [[foo bar]; [{a: "a_0", b:"b_0"} 1] [{a: "a_1", b: "b_1" } 2]] | polars into-df -s {foo: {a: str, b: str}, bar: u8}
```

crates/nu_plugin_polars/src/dataframe/command/core/to_df.rs

@@ -6,6 +6,7 @@ use crate::{
 
 use crate::values::NuDataFrame;
 
+use log::debug;
 use nu_plugin::{EngineInterface, EvaluatedCall, PluginCommand};
 use nu_protocol::{
     Category, Example, LabeledError, PipelineData, Signature, Span, SyntaxShape, Type, Value,
@@ -159,7 +160,7 @@ impl PluginCommand for ToDataFrame {
             },
             Example {
                 description: "Convert to a dataframe and provide a schema",
-                example: "{a: 1, b: {a: [1 2 3]}, c: [a b c]}| polars into-df -s {a: u8, b: {a: list<u64>}, c: list<str>}",
+                example: "[[a b c]; [1 {d: [1 2 3]} [10 11 12] ]]| polars into-df -s {a: u8, b: {d: list<u64>}, c: list<u8>}",
                 result: Some(
                     NuDataFrame::try_from_series_vec(vec![
                         Series::new("a", &[1u8]),
@@ -172,7 +173,7 @@ impl PluginCommand for ToDataFrame {
                         },
                         {
                             let dtype = DataType::List(Box::new(DataType::String));
-                            let vals = vec![AnyValue::List(Series::new("c", &["a", "b", "c"]))];
+                            let vals = vec![AnyValue::List(Series::new("c", &[10, 11, 12]))];
                             Series::from_any_values_and_dtype("c", &vals, &dtype, false)
                                 .expect("List series should not fail")
                         }
@@ -208,6 +209,8 @@ impl PluginCommand for ToDataFrame {
             .map(|schema| NuSchema::try_from(&schema))
             .transpose()?;
 
+        debug!("schema: {:?}", maybe_schema);
+
         let maybe_as_columns = call.has_flag("as-columns")?;
 
         let df = if !maybe_as_columns {
@@ -230,14 +233,22 @@ impl PluginCommand for ToDataFrame {
                                 .collect::<Vec<Column>>();
                             NuDataFrame::try_from_columns(columns, maybe_schema)?
                         }
-                        Err(_) => NuDataFrame::try_from_iter(
+                        Err(e) => {
+                            debug!(
+                                "Failed to build with multiple columns, attempting as series. failure:{e}"
+                            );
+                            NuDataFrame::try_from_iter(
                                 plugin,
                                 input.into_iter(),
                                 maybe_schema.clone(),
-                        )?,
+                            )?
                         }
                     }
-                _ => NuDataFrame::try_from_iter(plugin, input.into_iter(), maybe_schema.clone())?,
+                }
+                _ => {
+                    debug!("Other input: {input:?}");
+                    NuDataFrame::try_from_iter(plugin, input.into_iter(), maybe_schema.clone())?
+                }
             }
         };
 

crates/nu_plugin_polars/src/dataframe/values/nu_dataframe/conversion.rs

@@ -1,3 +1,4 @@
+use std::collections::HashMap;
 use std::ops::{Deref, DerefMut};
 
 use chrono::{DateTime, Duration, FixedOffset, NaiveTime, TimeZone, Utc};
@@ -487,17 +488,44 @@ fn typed_column_to_series(name: &str, column: TypedColumn) -> Result<Series, She
             }
             DataType::Struct(fields) => {
                 let schema = Some(NuSchema::new(Schema::from_iter(fields.clone())));
-                let mut structs: Vec<Series> = Vec::new();
+                // let mut structs: Vec<Series> = Vec::new();
+                let mut structs: HashMap<String, Series> = HashMap::new();
 
                 for v in column.values.iter() {
                     let mut column_values: ColumnMap = IndexMap::new();
                     let record = v.as_record()?;
                     insert_record(&mut column_values, record.clone(), &schema)?;
                     let df = from_parsed_columns(column_values)?;
-                    structs.push(df.as_series(Span::unknown())?);
+                    for name in df.df.get_column_names() {
+                        let series = df.df.column(name).map_err(|e| ShellError::GenericError {
+                            error: format!(
+                                "Error creating struct, could not get column name {name}: {e}"
+                            ),
+                            msg: "".into(),
+                            span: None,
+                            help: None,
+                            inner: vec![],
+                        })?;
+
+                        if let Some(v) = structs.get_mut(name) {
+                            let _ = v.append(series)
+                                .map_err(|e| ShellError::GenericError {
+                                    error: format!("Error creating struct, could not append to series for col {name}: {e}"),
+                                    msg: "".into(),
+                                    span: None,
+                                    help: None,
+                                    inner: vec![],
+                                })?;
+                        } else {
+                            structs.insert(name.to_string(), series.to_owned());
+                        }
+                    }
                 }
 
-                let chunked = StructChunked::new(column.name(), structs.as_ref()).map_err(|e| {
+                let structs: Vec<Series> = structs.into_values().collect();
+
+                let chunked =
+                    StructChunked::new(column.name(), structs.as_slice()).map_err(|e| {
                         ShellError::GenericError {
                             error: format!("Error creating struct: {e}"),
                             msg: "".into(),