Reduced LOC by replacing several instances of Value::Int {}, Value::Float{}, Value::Bool {}, and Value::String {} with Value::int(), Value::float(), Value::boolean() and Value::string() (#7412)

# Description

While perusing Value.rs, I noticed the `Value::int()`, `Value::float()`,
`Value::boolean()` and `Value::string()` constructors, which seem
designed to make it easier to construct various Values, but which aren't
used often at all in the codebase. So, using a few find-replaces
regexes, I increased their usage. This reduces overall LOC because
structures like this:
```
Value::Int {
  val: a,
  span: head
}
```
are changed into
```
Value::int(a, head)
```
and are respected as such by the project's formatter.
There are little readability concerns because the second argument to all
of these is `span`, and it's almost always extremely obvious which is
the span at every callsite.

# User-Facing Changes

None.

# Tests + Formatting

Don't forget to add tests that cover your changes.

Make sure you've run and fixed any issues with these commands:

- `cargo fmt --all -- --check` to check standard code formatting (`cargo
fmt --all` applies these changes)
- `cargo clippy --workspace -- -D warnings -D clippy::unwrap_used -A
clippy::needless_collect` to check that you're using the standard code
style
- `cargo test --workspace` to check that all tests pass

# After Submitting

If your PR had any user-facing changes, update [the
documentation](https://github.com/nushell/nushell.github.io) after the
PR is merged, if necessary. This will help us keep the docs up to date.

crates/nu-command/src/dataframe/eager/columns.rs

@@ -30,14 +30,8 @@ impl Command for ColumnsDF {
             example: "[[a b]; [1 2] [3 4]] | into df | columns",
             result: Some(Value::List {
                 vals: vec![
-                    Value::String {
-                        val: "a".into(),
-                        span: Span::test_data(),
-                    },
-                    Value::String {
-                        val: "b".into(),
-                        span: Span::test_data(),
-                    },
+                    Value::string("a", Span::test_data()),
+                    Value::string("b", Span::test_data()),
                 ],
                 span: Span::test_data(),
             }),
@@ -67,10 +61,7 @@ fn command(
         .as_ref()
         .get_column_names()
         .iter()
-        .map(|v| Value::String {
-            val: v.to_string(),
-            span: call.head,
-        })
+        .map(|v| Value::string(*v, call.head))
         .collect();
 
     let names = Value::List {

crates/nu-command/src/dataframe/eager/dtypes.rs

@@ -82,10 +82,7 @@ fn command(
                 span: call.head,
             });
 
-            Value::String {
-                val: v.to_string(),
-                span: call.head,
-            }
+            Value::string(*v, call.head)
         })
         .collect();
 

crates/nu-command/src/dataframe/eager/list.rs

@@ -61,15 +61,9 @@ impl Command for ListDF {
                     span: call.head,
                 };
 
-                let columns = Value::Int {
-                    val: df.as_ref().width() as i64,
-                    span: call.head,
-                };
+                let columns = Value::int(df.as_ref().width() as i64, call.head);
 
-                let rows = Value::Int {
-                    val: df.as_ref().height() as i64,
-                    span: call.head,
-                };
+                let rows = Value::int(df.as_ref().height() as i64, call.head);
 
                 let cols = vec![
                     "name".to_string(),

crates/nu-command/src/dataframe/eager/shape.rs

@@ -61,15 +61,9 @@ fn command(
 ) -> Result<PipelineData, ShellError> {
     let df = NuDataFrame::try_from_pipeline(input, call.head)?;
 
-    let rows = Value::Int {
-        val: df.as_ref().height() as i64,
-        span: call.head,
-    };
+    let rows = Value::int(df.as_ref().height() as i64, call.head);
 
-    let cols = Value::Int {
-        val: df.as_ref().width() as i64,
-        span: call.head,
-    };
+    let cols = Value::int(df.as_ref().width() as i64, call.head);
 
     let rows_col = Column::new("rows".to_string(), vec![rows]);
     let cols_col = Column::new("columns".to_string(), vec![cols]);