Displaying 1 to 20 from 28 results

q - q - Run SQL directly on CSV or TSV files

  •    Python

q is a command line tool that allows direct execution of SQL-like queries on CSVs/TSVs (and any other tabular text files). q treats ordinary files as database tables, and supports all SQL constructs, such as WHERE, GROUP BY, JOINs etc. It supports automatic column name and column type detection, and provides full support for multiple encodings.

node-csv - Full featured CSV parser with simple api and tested against large datasets.

  •    Javascript

This project provides CSV generation, parsing, transformation and serialization for Node.js. It has been tested and used by a large community over the years and should be considered reliable. It provides every option you would expect from an advanced CSV parser and stringifier.

CSV.js - A simple, blazing-fast CSV parser and encoder. Full RFC 4180 compliance.

  •    Javascript

Simple, blazing-fast CSV parsing/encoding in JavaScript. Full RFC 4180 compliance. Compatible with browsers (>IE8), AMD, and NodeJS.

datalib - JavaScript data utility library.

  •    Javascript

Datalib is a JavaScript data utility library. It provides facilities for data loading, type inference, common statistics, and string templates. While datalib was created to power Vega and related projects, it is also a standalone library useful for data-driven JavaScript applications on both the client (web browser) and server (e.g., node.js). For documentation, see the datalib API Reference.

vroom - Fast reading of delimited files

  •    C++

The fastest delimited reader for R, 1.27 GB/sec. vroom doesn’t stop to actually read all of your data, it simply indexes where each record is located so it can be read later. The vectors returned use the Altrep framework to lazily load the data on-demand when it is accessed, so you only pay for what you use. This lazy access is done automatically, so no changes to your R data-manipulation code are needed.

csvtk - A cross-platform, efficient and practical CSV/TSV toolkit in Golang

  •    Go

Similar to FASTA/Q format in field of Bioinformatics, CSV/TSV formats are basic and ubiquitous file formats in both Bioinformatics and data sicence. People usually use spreadsheet softwares like MS Excel to do process table data. However it's all by clicking and typing, which is not automatically and time-consuming to repeat, especially when we want to apply similar operations with different datasets or purposes.

sq - swiss-army knife for data

  •    Go

sq is a command line tool that provides jq-style access to structured data sources such as SQL databases, or document formats like CSV or Excel. sq can perform cross-source joins, execute database-native SQL, and output to a multitude of formats including JSON, Excel, CSV, HTML, Markdown and XML, or insert directly to a SQL database. sq can also inspect sources to view metadata about the source structure (tables, columns, size) and has commands for common database operations such as copying or dropping tables.

d3-dsv - A parser and formatter for delimiter-separated values, such as CSV and TSV.

  •    Javascript

A parser and formatter for delimiter-separated values, such as CSV and TSV

FlatFiles - Reads and writes CSV, fixed-length and other flat file formats with a focus on schema definition, configuration and speed

  •    CSharp

Reads and writes CSV, fixed-length and other flat file formats with a focus on schema definition, configuration and speed. Supports mapping directly between files and classes.As a bonus for those of you using FlatFiles, as of version 1.2, you should now be seeing a nearly 2x performance improvement over previous versions, both read and write, both CSV and fixed-length. I spent some time playing with BenchmarkDotNet and using the profiler to squeeze every ounce of performance out of FlatFiles.

dsv-dataset - A metadata specification and parsing library for data sets.

  •    Javascript

A metadata specification and parsing library for data sets. One of the many recurring issues in data visualization is parsing data sets. Data sets are frequently represented in a delimiter-separated value (DSV) format, such as comma-separated value (CSV) or tab-separated value (TSV). Conveniently, the d3-dsv library supports parsing such data sets. However, the resulting parsed data table has string values for every column, and it is up to the developer to parse those string values into numbers or dates, depending on the data.

csv.js - Encodes JSON, Arrays or Objects to CSV

  •    Javascript

Encodes arg as CSV. The optional delimiter allows you change the default comma. The optional header allows you to disable the first row of column names by passing false. Decodes arg to an Array of Objects. The optional delimiter allows you to specify the delimiter if it is not a comma.

TSV - A simple javascript TSV/CSV parser.

  •    Javascript

TSV/CSV converter and parser. Good for serving time-series (or any series) data to use in D3.js or other client-side graph libraries. Warning: This module does very dumb parsing and is not suitable for unclean data not generated by yourself. Processing is synchronous. Not suitable for large datasets. Unless you're really into minimal code, please use a better supported tool like node-csv-parser.


  •    Ruby

Also Supported CSV. The gem is available as open source under the terms of the MIT License.

detect-csv - Detect if a String could be the beginning of a csv

  •    Javascript

Right now it only parses the first line and counts characters. So the rest of the CSV might be invalid. Also I recommend checking for json/ndjson first, since it's the more strict format. Delimiters and newlines don't work with multiple characters, e.g. \r\n.

quaff - :sake: A data pipeline helper written in node to convert a folder of JSON/YAML/CSV/TSV files into usable data

  •    Javascript

A data pipeline helper written in node that works similar to Middleman's Data Files collector. Under the hood it uses JavaScript's built in JSON support, js-yaml and d3-dsv to read files.

tsv-utils - eBay's TSV Utilities: Command line tools for large, tabular data files

  •    D

This is a set of command line utilities for manipulating large tabular data files. Files of numeric and text data commonly found in machine learning, data mining, and similar environments. Filtering, sampling, statistical calculations and other operations are supported. The tools were originally developed in Perl and used for day-to-day work in a large scale data mining environment. One of the tools was re-written in D as an exercise exploring the language. Significant performance gains and agreeable programmer characteristics soon led to writing additional utilities in D. Information on the D programming language is available at dlang.org.

dsv-loader - A webpack module to load dsv (e.g. .csv or .tsv) files.

  •    Javascript

A Webpack plugin for loading dsv files (for example .csv). The loader will translate the data.csv file into a JSON Object.

We have large collection of open source products. Follow the tags from Tag Cloud >>

Open source products are scattered around the web. Please provide information about the open source projects you own / you use. Add Projects.