Added new dz! macros in dataframe.rs to create dataframe from vector of mixed data type vectors

charming/src/datatype/dataframe.rs

@@ -69,3 +69,69 @@ macro_rules! df {
         ]
     };
 }
+
+/// Code below is modified from ChatGPT generated code.
+/// The main objective of macro dz! is to transpose mixed data type vectors, 
+/// aka columns or dimensions into ECharts dataframe format. 
+
+#[macro_export]
+macro_rules! dz {
+    /*
+    Handle named vectors
+    let d1 = vec![44056, 13334];
+    let d2 = vec![81.8, 76.9];
+    let d3 = vec![23968973, 1376048943];
+    let d4 = vec!["Australia", "China"];
+    let d5 = vec![2015, 2015];
+    let df = dz!(d1, d2, d3, d4, d5);
+    >>df = [Value(Array([Number(Integer(44056)), Number(Float(81.8)), 
+    Number(Integer(23968973)), String("Australia"), Number(Integer(2015))])), 
+    Value(Array([Number(Integer(13334)), Number(Float(76.9)), 
+    Number(Integer(1376048943)), String("China"), Number(Integer(2015))]))]
+    */
+    ($($v:expr),* $(,)?) => {{
+        let mut df = Vec::new();
+        let mut iterators: Vec<Box<dyn Iterator<Item = $crate::datatype::CompositeValue>>> = vec![
+            $(Box::new($v.into_iter().map(|x| $crate::datatype::CompositeValue::from(x))),)*
+        ];
+
+        let len = iterators.first().map(|v| v.size_hint().0).unwrap_or(0);
+
+        for _ in 0..len {
+            let mut row = Vec::new();
+            for iter in iterators.iter_mut() {
+                if let Some(value) = iter.next() {
+                    row.push(value);
+                }
+            }
+            let z = $crate::datatype::DataPoint::from(row);
+            df.push(z);
+        }
+        df
+    }};
+
+    /*
+    Handle direct input of vectors
+    let df = dz!([44056, 13334], [81.8, 76.9], [23968973, 1376048943], ["Australia", "China"], [2015, 2015]);
+    >>df = [Value(Array([Number(Integer(44056)), Number(Float(81.8)), 
+    Number(Integer(23968973)), String("Australia"), Number(Integer(2015))])), 
+    Value(Array([Number(Integer(13334)), Number(Float(76.9)), 
+    Number(Integer(1376048943)), String("China"), Number(Integer(2015))]))]
+    */
+    ($([$($v:expr),*]),* $(,)?) => {{
+        let mut df = Vec::new();
+        let mut iterators: Vec<_> = vec![$(vec![$($v.into()),*].into_iter()),*];
+
+        let len = iterators.first().map(|v| v.len()).unwrap_or(0);
+        for _ in 0..len {
+            let mut row = Vec::new();
+            for iter in &mut iterators {
+                if let Some($crate::datatype::CompositeValue) = iter.next() {
+                    row.push($crate::datatype::CompositeValue);
+                }
+            }
+            df.push(row);
+        }
+        df
+    }};
+}

charming/src/series/scatter.rs

@@ -3,7 +3,7 @@ use serde::Serialize;
 use crate::{
     datatype::{DataFrame, DataPoint},
     element::{
-        ColorBy, CoordinateSystem, DimensionEncode, Emphasis, ItemStyle, MarkArea, MarkLine,
+        ColorBy, CoordinateSystem, DimensionEncode, Emphasis, ItemStyle, Label, MarkArea, MarkLine,
         Symbol, SymbolSize,
     },
 };
@@ -19,10 +19,13 @@ pub struct Scatter {
 
     #[serde(skip_serializing_if = "Option::is_none")]
     name: Option<String>,
-
+    
     #[serde(skip_serializing_if = "Option::is_none")]
     color_by: Option<ColorBy>,
 
+    #[serde(skip_serializing_if = "Option::is_none")]
+    label: Option<Label>,
+
     #[serde(skip_serializing_if = "Option::is_none")]
     dataset_index: Option<f64>,
 
@@ -67,6 +70,7 @@ impl Scatter {
             id: None,
             name: None,
             color_by: None,
+            label: None,
             dataset_index: None,
             coordinate_system: None,
             x_axis_index: None,
@@ -97,6 +101,11 @@ impl Scatter {
         self
     }
 
+    pub fn label<L: Into<Label>>(mut self, label: L) -> Self {
+        self.label = Some(label.into());
+        self
+    }
+
     pub fn dataset_index<F: Into<f64>>(mut self, dataset_index: F) -> Self {
         self.dataset_index = Some(dataset_index.into());
         self