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@ -98,17 +98,15 @@ assert!(check);
```
---
## DataFrame Usage Example
```rust
use chrono::NaiveDate;
use rustframe::dataframe::DataFrame;
use rustframe::utils::{BDateFreq, BDatesList};
use std::any::TypeId;
use chrono::NaiveDate;
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(
"col_string",
vec![
"apple".to_string(),
"banana".to_string(),
"cherry".to_string(),
"date".to_string(),
"elderberry".to_string(),
],
);
df.add_column("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",
BDatesList::from_n_periods("2023-01-01".to_string(), BDateFreq::Daily, 5)
.unwrap()
.list()
.unwrap(),
);
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)]);
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!(
"\nInitial number of internal frames: {}",
initial_frames_count
);
println!("\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!(
"Number of internal frames after adding more columns of existing types: {}",
frames_after_reuse
);
println!("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!(
"\nDataFrame after adding more columns of existing types:\n{}",
df
);
println!("\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);
println!("Integer column (col_int1): {:?}", int_col); // Output: Integer column: [1, 2, 3, 4, 5]
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);
println!("Integer column (col_int2): {:?}", int_col2); // Output: Integer column: [6, 7, 8, 9, 10]
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);
println!("Float column (col_float1): {:?}", float_col); // Output: Float column: [1.1, 2.2, 3.3, 4.4, 5.5]
// 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);
println!("Wrong type column: {:?}", wrong_type_col); // Output: Wrong type column: None
// 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);
println!("Row out of bounds: {:?}", row_out_of_bounds); // Output: Row out of bounds: None
// 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!(
"Column names after second drop: {:?}",
df.get_column_names()
);
println!("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