## datatroll: Powerfully Wrangle Your CSV Data in Rust
datatroll is a robust and user-friendly Rust library for efficiently loading, manipulating, and exporting data stored in CSV files. Say goodbye to tedious hand-coding data parsing and welcome a streamlined workflow for wrangling your data with ease.
### Features:
- **Versatile 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.
- **Intuitive 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 using lambda functions.
- Supports Pagination
- **Seamless 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.
### Benefits:
- **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.
### Getting Started:
Add rust-csv-wrangler to your project with Cargo:
```toml
[dependencies]
datatroll = "0.1.0"
```
Import the library and start wrangling your data:
```rust
use datatroll::{Cell, Sheet};
fn main() {
// 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");
}
}
```