Merge d9bdf8ee965dbcd624856250c3285bf0ac1ac2e2 into e7d4e2221c19ad607a7c8632b2cf64657e95e83f

README.md

@@ -98,17 +98,15 @@ assert!(check);
 
 
 ```
-
 ---
 
 ## DataFrame Usage Example
 
 ```rust
-use chrono::NaiveDate;
 use rustframe::dataframe::DataFrame;
-use rustframe::utils::{BDateFreq, BDatesList};
+use chrono::NaiveDate;
-use std::any::TypeId;
 use std::collections::HashMap;
+use std::any::TypeId; // Required for checking TypeId
 
 // Helper for NaiveDate
 fn d(y: i32, m: u32, d: u32) -> NaiveDate {
@@ -121,49 +119,25 @@ let mut df = DataFrame::new();
 // Add columns of different types
 df.add_column("col_int1", vec![1, 2, 3, 4, 5]);
 df.add_column("col_float1", vec![1.1, 2.2, 3.3, 4.4, 5.5]);
-df.add_column(
+df.add_column("col_string", vec!["apple".to_string(), "banana".to_string(), "cherry".to_string(), "date".to_string(), "elderberry".to_string()]);
-    "col_string",
-    vec![
-        "apple".to_string(),
-        "banana".to_string(),
-        "cherry".to_string(),
-        "date".to_string(),
-        "elderberry".to_string(),
-    ],
-);
 df.add_column("col_bool", vec![true, false, true, false, true]);
-// df.add_column("col_date", vec![d(2023,1,1), d(2023,1,2), d(2023,1,3), d(2023,1,4), d(2023,1,5)]);
+df.add_column("col_date", vec![d(2023,1,1), d(2023,1,2), d(2023,1,3), d(2023,1,4), d(2023,1,5)]);
-df.add_column(
-    "col_date",
-    BDatesList::from_n_periods("2023-01-01".to_string(), BDateFreq::Daily, 5)
-        .unwrap()
-        .list()
-        .unwrap(),
-);
 
 println!("DataFrame after initial column additions:\n{}", df);
 
 // Demonstrate frame re-use when adding columns of existing types
 let initial_frames_count = df.num_internal_frames();
-println!(
+println!("\nInitial number of internal frames: {}", initial_frames_count);
-    "\nInitial number of internal frames: {}",
-    initial_frames_count
-);
 
 df.add_column("col_int2", vec![6, 7, 8, 9, 10]);
 df.add_column("col_float2", vec![6.6, 7.7, 8.8, 9.9, 10.0]);
 
 let frames_after_reuse = df.num_internal_frames();
-println!(
+println!("Number of internal frames after adding more columns of existing types: {}", frames_after_reuse);
-    "Number of internal frames after adding more columns of existing types: {}",
-    frames_after_reuse
-);
 assert_eq!(initial_frames_count, frames_after_reuse); // Should be equal, demonstrating re-use
 
-println!(
+println!("\nDataFrame after adding more columns of existing types:\n{}", df);
-    "\nDataFrame after adding more columns of existing types:\n{}",
+
-    df
-);
 
 // Get number of rows and columns
 println!("Rows: {}", df.rows()); // Output: Rows: 5
@@ -175,21 +149,17 @@ println!("Column names: {:?}", df.get_column_names());
 
 // Get a specific column by name and type
 let int_col = df.get_column::<i32>("col_int1").unwrap();
-// Output: Integer column: [1, 2, 3, 4, 5]
+println!("Integer column (col_int1): {:?}", int_col); // Output: Integer column: [1, 2, 3, 4, 5]
-println!("Integer column (col_int1): {:?}", int_col);
 
 let int_col2 = df.get_column::<i32>("col_int2").unwrap();
-// Output: Integer column: [6, 7, 8, 9, 10]
+println!("Integer column (col_int2): {:?}", int_col2); // Output: Integer column: [6, 7, 8, 9, 10]
-println!("Integer column (col_int2): {:?}", int_col2);
 
 let float_col = df.get_column::<f64>("col_float1").unwrap();
-// Output: Float column: [1.1, 2.2, 3.3, 4.4, 5.5]
+println!("Float column (col_float1): {:?}", float_col); // Output: Float column: [1.1, 2.2, 3.3, 4.4, 5.5]
-println!("Float column (col_float1): {:?}", float_col);
 
 // Attempt to get a column with incorrect type (returns None)
 let wrong_type_col = df.get_column::<bool>("col_int1");
-// Output: Wrong type column: None
+println!("Wrong type column: {:?}", wrong_type_col); // Output: Wrong type column: None
-println!("Wrong type column: {:?}", wrong_type_col);
 
 // Get a row by index
 let row_0 = df.get_row(0).unwrap();
@@ -202,8 +172,7 @@ println!("Row 2: {:?}", row_2);
 
 // Attempt to get an out-of-bounds row (returns None)
 let row_out_of_bounds = df.get_row(10);
-// Output: Row out of bounds: None
+println!("Row out of bounds: {:?}", row_out_of_bounds); // Output: Row out of bounds: None
-println!("Row out of bounds: {:?}", row_out_of_bounds);
 
 // Drop a column
 df.drop_column("col_bool");
@@ -217,10 +186,7 @@ df.drop_column("col_float1");
 println!("\nDataFrame after dropping 'col_float1':\n{}", df);
 
 println!("Columns after second drop: {}", df.cols());
-println!(
+println!("Column names after second drop: {:?}", df.get_column_names());
-    "Column names after second drop: {:?}",
-    df.get_column_names()
-);
 
 // Attempt to drop a non-existent column (will panic)
 // df.drop_column("non_existent_col"); // Uncomment to see panic