What is dataframe-builder?

Mechatronics, Software Engineering, Woodworking, and "Making" in General

What is dataframe-builder?

dataframe-builder is a TypeScript/JavaScript library designed to generate sample dataframes tailored to your specifications. By defining column types and the number of rows, you can produce datasets that mimic real-world data structures, facilitating effective testing and development.​

I created this project are a foray into open source software, so I welcome any suggestions, contributions, issues, etc. Github Repo here: davidinwald/data_generator

NPM: dataframe-builder – npm


Key Features

1. Customizable Column Types

Define each column’s characteristics, including:​

  • Strings: Generate names or lorem ipsum text.
  • Numbers: Specify ranges, precision, and whether values are integers or floats.
  • Booleans: Randomly assign true or false values.
  • Dates: Produce datetime values within defined intervals.​

This flexibility allows you to craft datasets that closely resemble your application’s expected data.​

2. Random and Described Data Generation

  • Random Independent Values: Each row’s data is generated independently, ideal for general testing.
  • Described Series: Create data following specific mathematical patterns (e.g., linear, quadratic), perfect for visualizations and simulations.​

3. Mathematical Series and Shapes

A standout feature is the ability to generate data that follows mathematical series or shapes. This is particularly useful for:​

  • Data Visualization: Test charts and graphs with predictable patterns.
  • Algorithm Testing: Evaluate how algorithms perform with data following known distributions.
  • Educational Purposes: Demonstrate concepts using data that follows specific mathematical rules.​

When and Where to Use dataframe-builder

  • UI Development: Populate tables, charts, and other components with realistic data during the development phase.
  • Testing: Create diverse datasets to test application behavior under various scenarios.
  • Prototyping: Quickly generate data to showcase features or concepts.
  • Data Science: Simulate datasets for algorithm development or educational demonstrations.​

Getting Started

Installation

Install the package using npm:​

bashCopyEditnpm install dataframe-builder

Basic Usage

javascriptCopyEditimport { buildDataFrame } from 'dataframe-builder';

const columnTypes = [
  { name: "Name", type: "string", subType: "name" },
  { name: "Score", type: "number", min: 0, max: 100, precision: 2 },
  { name: "Passed", type: "boolean" },
  { name: "Attempts", type: "integer", min: 1, max: 5 }
];

const numRows = 10;

const data = buildDataFrame({ columnTypes, numRows });

console.log(data);

This script generates a dataframe with 10 rows, each containing a name, score, pass status, and number of attempts.​


Next Steps and Future Enhancements

While dataframe-builder is already a powerful tool, there’s always room for growth:

  • Enhanced Mathematical Patterns: Introduce more complex series like exponential, logarithmic, or sinusoidal patterns.
  • Data Export Options: Allow exporting generated data to formats like CSV or JSON for broader usability.
  • Integration with Visualization Libraries: Provide seamless integration with libraries like D3.js or Chart.js.
  • User Interface: Develop a GUI for users who prefer not to work directly with code.​

Conclusion

dataframe-builder stands out as a versatile and user-friendly tool for generating structured, realistic datasets. Whether you’re developing a new feature, testing an application, or teaching data concepts, this package simplifies the process of data generation, saving you time and effort.​

Explore more about dataframe-builder and contribute to its development by visiting the official documentation.

 

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