Tutorials

Lodash _.sampleSize() Collection Method

Posted in lodash Tutorial

Updated on Nov 22, 2024

By Mari Selvan

👁️ 37 - Views

⏳ 4 mins

💬 1 Comment

Photo Credit to CodeToFun

🙋 Introduction

In the diverse landscape of JavaScript programming, handling collections and generating random samples is a common task. Enter Lodash, a comprehensive utility library that simplifies array manipulation. Among its plethora of functions is the _.sampleSize() method, designed to extract a specified number of random elements from a collection.

This method proves invaluable for scenarios requiring randomization and varied sampling within your JavaScript projects.

🧠 Understanding _.sampleSize() Method

The _.sampleSize() method in Lodash facilitates the extraction of a random sample of elements from a collection. This allows developers to introduce randomness or implement features like shuffling, creating diverse subsets, or conducting unbiased sampling.

💡 Syntax

The syntax for the _.sampleSize() method is straightforward:

syntax.js

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_.sampleSize(collection, [size=1])

collection: The collection to sample.
size (Optional): The number of elements to sample.

📝 Example

Let's dive into a simple example to illustrate the usage of the _.sampleSize() method:

example.js

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const _ = require('lodash');

const originalCollection = [1, 2, 3, 4, 5, 6, 7, 8, 9];
const sampledElements = _.sampleSize(originalCollection, 3);

console.log(sampledElements);
// Output: e.g., [2, 7, 5] (randomly sampled elements)

In this example, sampledElements contains a random sample of three elements from the originalCollection.

🏆 Best Practices

When working with the _.sampleSize() method, consider the following best practices:

Specify Sample Size:

Be explicit about the size of the sample you want to extract. This ensures control over the number of elements retrieved and avoids unexpected behavior.

example.js

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const largeCollection = /* ...fetch data from API or elsewhere... */;
const specificSample = _.sampleSize(largeCollection, 5);

console.log(specificSample);
// Output: An array containing 5 randomly sampled elements

Handle Edge Cases:

Consider scenarios where the requested sample size exceeds the length of the collection. Implement error handling or fallback mechanisms to address these edge cases.

example.js

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const smallCollection = [1, 2, 3];
const largeSample = _.sampleSize(smallCollection, 5);

console.log(largeSample);
// Output: An array containing all elements of the small collection (no repetition)

Diversify Sampling:

Experiment with different sample sizes to achieve diverse results. This is particularly useful when dealing with visualization or scenarios where varied sample sizes enhance the user experience.

example.js

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const datasetForVisualization = /* ...fetch data from API or elsewhere... */;
const smallSample = _.sampleSize(datasetForVisualization, 3);
const largeSample = _.sampleSize(datasetForVisualization, 10);

console.log(smallSample);
console.log(largeSample);

📚 Use Cases

Randomized Display:

Enhance user engagement by randomizing the display of content, such as featured items, images, or testimonials on a webpage.

example.js

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const testimonials = /* ...fetch testimonials from API or elsewhere... */;
const randomizedTestimonials = _.sampleSize(testimonials, 3);

console.log(randomizedTestimonials);

Quiz or Assessment Randomization:

Implement question or answer randomization in quizzes or assessments to provide a fair and diverse experience for users.
example.js
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```
const quizQuestions = /* ...fetch questions from API or elsewhere... */;
const randomizedQuestions = _.sampleSize(quizQuestions, 5);

console.log(randomizedQuestions);
```

Gaming and Simulation:

Create dynamic and unpredictable scenarios in games or simulations by introducing randomness through sampled elements.

example.js

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const gameItems = ['sword', 'shield', 'potion', 'armor', 'key'];
const playerInventory = _.sampleSize(gameItems, 2);

console.log(playerInventory);
// Output: An array containing 2 randomly sampled items for the player's inventory

🎉 Conclusion

The _.sampleSize() method in Lodash proves to be an essential tool for JavaScript developers working with collections. Whether you're enhancing user experiences through randomized displays or implementing diverse sampling in quizzes and simulations, this method offers flexibility and efficiency.

By adhering to best practices and exploring diverse use cases, you can harness the full potential of the _.sampleSize() method in your Lodash projects.