Tidy-TS

Sorting / Arranging Data

Sort your data to understand patterns, find extremes, and organize information for better analysis. tidy-ts provides flexible sorting with full type safety.

Basic Sorting

Sort by a single column in ascending or descending order

The arrange() function sorts your DataFrame by one or more columns. By default, sorting is ascending, but you can specify 'desc' for descending order.

import { createDataFrame } from "@tidy-ts/dataframe";

const students = createDataFrame([
  { id: 1, name: "Charlie", age: 35, score: 78 },
  { id: 2, name: "Alice", age: 25, score: 85 },
  { id: 3, name: "Bob", age: 30, score: 92 },
]);

// Sort by age (ascending by default)
const sortedByAge = students.arrange("age");
sortedByAge.print("Students sorted by age (youngest first):");

// Sort by score in descending order
const sortedByScore = students.arrange("score", "desc");
sortedByScore.print("Students sorted by score (highest first):");

import { createDataFrame } from "@tidy-ts/dataframe";

const students = createDataFrame([
  { id: 1, name: "Charlie", age: 35, score: 78 },
  { id: 2, name: "Alice", age: 25, score: 85 },
  { id: 3, name: "Bob", age: 30, score: 92 },
]);

// Sort by age (ascending by default)
const sortedByAge = students.arrange("age");
sortedByAge.print("Students sorted by age (youngest first):");

// Sort by score in descending order
const sortedByScore = students.arrange("score", "desc");
sortedByScore.print("Students sorted by score (highest first):");

Multiple Column Sorting

Sort by multiple columns with different orders

You can sort by multiple columns by passing an array. The DataFrame will be sorted by the first column, then by the second column within groups of equal values in the first column, and so on.

const employees = createDataFrame([
  { id: 1, name: "Alice", age: 25, score: 85, department: "Engineering" },
  { id: 2, name: "Bob", age: 30, score: 92, department: "Marketing" },
  { id: 3, name: "Charlie", age: 25, score: 78, department: "Engineering" },
  { id: 4, name: "Diana", age: 30, score: 88, department: "Marketing" },
]);

// Sort by department first, then by score descending within each department
const sorted = employees
  .arrange("department", "asc")
  .arrange("score", "desc");

sorted.print("Employees sorted by department, then by score:");

const employees = createDataFrame([
  { id: 1, name: "Alice", age: 25, score: 85, department: "Engineering" },
  { id: 2, name: "Bob", age: 30, score: 92, department: "Marketing" },
  { id: 3, name: "Charlie", age: 25, score: 78, department: "Engineering" },
  { id: 4, name: "Diana", age: 30, score: 88, department: "Marketing" },
]);

// Sort by department first, then by score descending within each department
const sorted = employees
  .arrange("department", "asc")
  .arrange("score", "desc");

sorted.print("Employees sorted by department, then by score:");

Sorting with Calculated Values

Sort by values calculated from existing columns

You can sort by any column, including calculated ones. This is particularly useful for finding the highest or lowest values after performing transformations.

const grades = createDataFrame([
  { id: 1, name: "Alice", math: 85, science: 90, english: 80 },
  { id: 2, name: "Bob", math: 92, science: 88, english: 95 },
  { id: 3, name: "Charlie", math: 78, science: 85, english: 90 },
]);

// Calculate average grade and sort by it
const withAverage = grades
  .mutate({
    average: (row) => (row.math + row.science + row.english) / 3,
  })
  .arrange("average", "desc");

withAverage.print("Students ranked by average grade:");

const grades = createDataFrame([
  { id: 1, name: "Alice", math: 85, science: 90, english: 80 },
  { id: 2, name: "Bob", math: 92, science: 88, english: 95 },
  { id: 3, name: "Charlie", math: 78, science: 85, english: 90 },
]);

// Calculate average grade and sort by it
const withAverage = grades
  .mutate({
    average: (row) => (row.math + row.science + row.english) / 3,
  })
  .arrange("average", "desc");

withAverage.print("Students ranked by average grade:");

Finding Extremes

Common sorting patterns for finding top performers

Use sorting to find the highest or lowest values in your data, or the best performer in each group.

const sales = createDataFrame([
  { id: 1, name: "Alice", region: "North", sales: 50000 },
  { id: 2, name: "Bob", region: "South", sales: 75000 },
  { id: 3, name: "Charlie", region: "North", sales: 60000 },
  { id: 4, name: "Diana", region: "East", sales: 80000 },
]);

// Find top 2 performers
const topPerformers = sales
  .arrange("sales", "desc")
  .sliceHead(2);

topPerformers.print("Top 2 sales performers:");

// Find best performer in each region
const bestByRegion = sales
  .groupBy("region")
  .summarise({
    top_sales: (group) => group.sliceMax("sales", 1).extractHead("name", 1) || "N/A",
    max_sales: (group) => group.sliceMax("sales", 1).extractHead("sales", 1) || 0,
  })
  .arrange("max_sales", "desc");

bestByRegion.print("Best performer by region:");

const sales = createDataFrame([
  { id: 1, name: "Alice", region: "North", sales: 50000 },
  { id: 2, name: "Bob", region: "South", sales: 75000 },
  { id: 3, name: "Charlie", region: "North", sales: 60000 },
  { id: 4, name: "Diana", region: "East", sales: 80000 },
]);

// Find top 2 performers
const topPerformers = sales
  .arrange("sales", "desc")
  .sliceHead(2);

topPerformers.print("Top 2 sales performers:");

// Find best performer in each region
const bestByRegion = sales
  .groupBy("region")
  .summarise({
    top_sales: (group) => group.sliceMax("sales", 1).extractHead("name", 1) || "N/A",
    max_sales: (group) => group.sliceMax("sales", 1).extractHead("sales", 1) || 0,
  })
  .arrange("max_sales", "desc");

bestByRegion.print("Best performer by region:");

Categorical Sorting

Sorting string and categorical data

Sort text data alphabetically or by custom order. Useful for organizing names, categories, or any text-based data.

const products = createDataFrame([
  { id: 1, name: "Charlie", category: "Zebra", price: 15.99 },
  { id: 2, name: "Alice", category: "Apple", price: 2.50 },
  { id: 3, name: "Bob", category: "Banana", price: 1.25 },
]);

// Sort by name alphabetically
const sortedByName = products.arrange("name");
sortedByName.print("Products sorted by name:");

// Sort by category alphabetically
const sortedByCategory = products.arrange("category");
sortedByCategory.print("Products sorted by category:");

// Sort by price (numeric)
const sortedByPrice = products.arrange("price");
sortedByPrice.print("Products sorted by price:");

const products = createDataFrame([
  { id: 1, name: "Charlie", category: "Zebra", price: 15.99 },
  { id: 2, name: "Alice", category: "Apple", price: 2.50 },
  { id: 3, name: "Bob", category: "Banana", price: 1.25 },
]);

// Sort by name alphabetically
const sortedByName = products.arrange("name");
sortedByName.print("Products sorted by name:");

// Sort by category alphabetically
const sortedByCategory = products.arrange("category");
sortedByCategory.print("Products sorted by category:");

// Sort by price (numeric)
const sortedByPrice = products.arrange("price");
sortedByPrice.print("Products sorted by price:");