dataframe-go
A lightweight and intuitive Go library for data manipulation, statistics, and machine learning using DataFrames.
What is dataframe-go?
dataframe-go is a Go library that implements DataFrames for data manipulation, statistical analysis, and machine learning. It provides a structured way to handle tabular data with support for importing, exporting, filtering, sorting, and applying functions, similar to pandas in Python but native to Go.
Go developers working on data analysis, machine learning projects, or any application requiring efficient tabular data manipulation and exploration.
It offers a performant, intuitive, and lightweight DataFrame implementation specifically for Go, with seamless integration into Go ecosystems and interoperability with popular packages like gonum for advanced mathematical operations.
Overview
DataFrames for Go: For statistics, machine-learning, and data manipulation/exploration
Use Cases
Best For
- Performing statistical analysis on tabular data in Go applications
- Building machine learning pipelines that require data preprocessing and transformation
- Importing and exporting data between various formats like CSV, Parquet, and SQL databases
- Creating time-series forecasts using methods like SES or Holt-Winters
- Generating synthetic datasets for testing or prototyping data workflows
- Visualizing data with cross-platform plotting capabilities
Not Ideal For
- Projects requiring a stable, production-ready API without breaking changes
- Teams needing advanced data manipulation features like pivot tables or window functions found in pandas
- Applications that depend on a large ecosystem of third-party plugins and community extensions
Pros & Cons
Pros
Supports custom series creation for any data type, as shown with civil.Date examples, enabling tailored data structures without modifying core code.
Imports and exports data from CSV, JSONL, Parquet, Excel, and SQL databases, facilitating seamless integration with various data sources and sinks.
Integrates with gonum and montanaflynn/stats packages for calculations like mean and standard deviation, leveraging Go's existing math ecosystems.
Includes built-in methods like SES and Holt-Winters for forecasting, making it useful for predictive analytics directly in Go without external tools.
Cons
The README explicitly warns that the entire package will be rewritten for Go 1.18 generics, causing breaking changes and making it unsuitable for projects needing long-term stability.
Compared to mature libraries like pandas, it lacks complex operations such as group-by aggregations with multiple functions or seamless joins, which may require workarounds.
As a niche Go library, it has fewer community contributions, third-party integrations, and extensive documentation, limiting out-of-the-box functionality and support.
Open Source Alternative To
dataframe-go is an open-source alternative to the following products:
Frequently Asked Questions
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