Iterate a CSV file quickly using various filtering reader classes.
Filter CSV rows by column value. Zero-dependency CLI for quick CSV grep.
CSV parser and writer
fast-csv formatting module
fast-csv parsing package
CSV parsing implementing the Node.js `stream.Transform` API
CSV stringifier implementing the Node.js `stream.Transform` API
Streaming CSV parser that aims for maximum speed as well as compatibility with the csv-spectrum test suite
A mature CSV toolset with simple api, full of options and tested against large datasets.
Token-Oriented Object Notation (TOON) – Compact, human-readable, schema-aware encoding of JSON for LLM prompts
CSV and object generation implementing the Node.js `stream.Readable` API
A JSON to CSV and CSV to JSON converter that natively supports sub-documents and auto-generates the CSV heading.
Fast and powerful CSV parser for the browser that supports web workers and streaming large files. Converts CSV to JSON and JSON to CSV.
Kendo UI CSV package
Convenient parsing for Fetch.
Convert objects/arrays into a CSV string or write them into a CSV file
TypeScript definitions for react-csv
Object transformations implementing the Node.js `stream.Transform` API
Advanced Data Grid / Data Table supporting Javascript / Typescript / React / Angular / Vue
A tool concentrating on converting csv data to JSON with customised parser supporting
Easily create CSV data from json collection
TypeScript version of the gluestick ETL library for hotglue IPaaS platform
Build CSV files on the fly basing on Array/literal object of data
Fast CSV parser
quick csv reader and decoder
swiss army knife for chess file formats
A quick and lightweight CSV handling library for Ruby
Because I hate excel, I'd rather query my csv files like I would query a db
A quick solution to model Kismet-generated gpsxml log files and output to CSV
Add quick mass data import from CSV or Array to Active Record model
Quick way to inspect your Rails database, see content of tables, filter, export them to CSV, Excel, EXPLAIN SQL and run SQL queries.
Quick way to inspect your Rails database, see content of tables, filter, export them to CSV, Excel, EXPLAIN SQL and run SQL queries.
apiify is a little gem that takes any .csv file and turns it into an API. It's aimed at large organisations, e.g. government departments, that publish a lot of data as .csv and who want a quick way to access this data as JSON in their digital services.
Teamwork allows to log time for all tasks within a project but the stats capabilities do not allow for a quick overview of time loggin stats. TWStats produces useful stats from a CSV file exported from Teamwork
Quick way to inspect your Rails database, see content of tables, filter, export them to CSV, Excel, EXPLAIN SQL and run SQL queries.
qdfca (Quick-Deploy Formal Concept Analysis) is a command-line filter that implements Formal Concept Analysis (FCA). It is small, scriptable, and easy to install, with no external requirements other than the standard Ruby library. The input is a formal context in CSV table format. The output is a dot format digraph rendering of the concept lattice with reduced labelling.
# MakeData A CLI for generating fake json, csv, or yaml data. Uses Faker to produce fake data in whatever category you choose. ## Quick Start Requires `peco`, so `brew install peco` (or however you get packages) ``` mkdata ``` Follow the prompts to select the category, keys, count, and format. ## Options `-h --help` Shows the help menu `-c --category [CATEGORY]` choose a category from Faker. (I can never remember these, so I use the interactive mode. Mostly here so that this could be used without interaction, like in a script) `-f --format [FORMAT]` json, csv, or yaml. What format to generate the data in. `-a --all` use all the keys from that Faker category.
Ruby Scientist and Graphics is a practical data science toolkit for Ruby. It includes a lightweight built-in DataFrame for loading, cleaning, and transforming data; quick descriptive statistics and correlations; charting via Gruff (bar and line); and simple ML utilities (linear regression and k-means)—all behind a small, unified, pandas-inspired API. Key features: - Load data from CSV and JSON. - Clean and transform (remove/add columns, handle missing values, limit rows). - Describe datasets and compute correlations quickly. - Create bar and line charts with customization options. - Train/predict with linear regression; cluster with k-means. - Save/load project state (data + trained model) and run simple pipelines. - Optional backend adapters (e.g., Rover) while keeping the same API. Ideal for analysts and developers who want to explore data in Ruby without relying on Python or R. Note: plotting via Gruff uses rmagick, which requires ImageMagick installed on the system.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.