datatroll is a robust and user-friendly Rust library for efficiently loading, manipulating, and exporting data stored in CSV files.

• Data Loading:
  • Read data from CSV files with configurable separators and headers.
  • Specify data types for each column, ensuring type safety and efficient processing.
  • Handle missing values with graceful error handling.
• Data Manipulation:
  • Insert new rows with custom values into your data.
  • Drop unwanted rows or columns to focus on relevant data.
  • Leverage powerful aggregations to calculate:
    • Mean, max, min, and median of numeric columns.
    • Mode (most frequent value) of categorical columns.
    • Variance of numeric columns.
  • Apply custom transformations to specific columns.
  • Supports Pagination.
• Data Export:
  • Write manipulated data back to a new CSV file, retaining original format or specifying your own.
  • Customize output with options like separator selection and header inclusion.

• Save Time and Effort: Focus on analyzing data, not wrangling it.
• Minimize Errors: Type-safe data handling and clear error messages improve code reliability.
• Boost Productivity: Get more done with faster data loading, manipulation, and export.
• Write Concise Code: Enjoy an intuitive API for concise and expressive data wrangling tasks.

Add datatroll to your project with Cargo:

[dependencies]
datatroll = "0.1.3"

Import the library:

use datatroll::{Cell, Sheet};

fn main() {
    // 1. Read data from a CSV file
    let mut sheet = Sheet::new();
    if let Err(err) = sheet.load_data("input.csv") {
        eprintln!("Error loading data: {}", err);
    } else {
        println!("Data loaded successfully from input.csv");
    }

    // drop all the rows in which the review is less than 4.0
    sheet.drop_rows("review", |c| {
        if let Cell::Float(r) = c {
            return *r < 4.0;
        }
        false
    });

    // calculate the variance of the review column
    let variance = sheet.variance("review").unwrap();
    println!("variance for review is: {variance}");
    
    // Write the transformed data to a new CSV file
    if let Err(err) = sheet.export("output.csv") {
        eprintln!("Error exporting data: {}", err);
    } else {
        println!("Data exported successfully to output.csv");
    }

    // 2. Read data from strings
    let data = "id ,title , director, release date, review
1, old, quintin, 2011, 3.5
2, her, quintin, 2013, 4.2
3, easy, scorces, 2005, 1.0
4, hey, nolan, 1997, 4.7
5, who, martin, 2017, 5.0";
    
    let sheet = Sheet::load_data_from_str(data);
    sheet.pretty_print();
}