Quadratic registra 87.216 visitas mensuales con un crecimiento intermensual de -18,3 % y un modelo de precios Freemium. RTutor registra 2247 visitas mensuales con un crecimiento de -60,2 % y un modelo de precios Precio a consultar, Gratis.
Quadratic is an AI spreadsheet where you connect live data, ask questions in plain language, and get Python, SQL, JavaScript or formulas plus charts that you can read, verify and share with your team.
RTutor is a web app that turns plain-English requests into R (or Python) code, runs it against your uploaded data and returns results plus a downloadable HTML report. Built on large language models such as GPT-4o, it lets analysts upload a CSV, TSV or Excel file and explore distributions, plots, correlations and EDA reports without writing code.
Quadratic is an AI spreadsheet where you connect live data, ask questions in plain language, and get Python, SQL, JavaScript or formulas plus charts that you can read, verify and share with your team.
Live data connections
CSV, Excel and PDF files plus live connections to Postgres, MySQL, Snowflake, BigQuery, SQL Server, Supabase and more flow into one sheet that refreshes from the source.
Natural-language analysis
Ask in ordinary language and the assistant writes the formulas, Python or SQL that answers the question — then leaves the code on the sheet so you can check it.
Python, SQL, formula and JavaScript cells
Write real Python, SQL, JavaScript and spreadsheet formulas in cells, which makes Quadratic far more capable than a formulas-only grid.
MCP and API access
Quadratic speaks the Model Context Protocol, so you can point Claude, Cursor, ChatGPT or another agent at your spreadsheet to read, write and verify work in it.
Fortalezas y ventajas
+The generated code stays in the sheet, so results are auditable instead of a black box.
+Genuinely large datasets are workable where Excel and Google Sheets hit their limits.
+Live database and SaaS connectors replace repetitive CSV export workflows.
Preguntas frecuentes: Quadratic vs RTutor
Quadratic tiene 87.216 visitas mensuales, mientras que RTutor tiene 2247. Las estimaciones de tráfico describen el tamaño de la audiencia, no la calidad del producto.
–The feature surface is large — AI agents, code cells, MCP, API — so onboarding takes longer than a basic spreadsheet.
–Code-based analysis assumes some comfort with Python, SQL or JavaScript concepts.
–Heavier data sources and agent runs consume plan limits, which is worth monitoring at volume.
–Teams standardised on Excel macros will need to rebuild some existing workbooks.
RTutor
RTutor is a web app that turns plain-English requests into R (or Python) code, runs it against your uploaded data and returns results plus a downloadable HTML report. Built on large language models such as GPT-4o, it lets analysts upload a CSV, TSV or Excel file and explore distributions, plots, correlations and EDA reports without writing code.
Natural language to R/Python
Upload CSV, TSV or Excel files and request analyses in plain English; RTutor generates the R or Python code and executes it for you.
Guided analysis tabs
Dedicated tabs for basic, categorical and numerical analysis, summary statistics, tables, correlation and GGpairs plots guide common workflows.
Downloadable EDA reports
Generate multi-section EDA reports and download them as HTML documents in minutes.
Conversational iteration
In a session, previous questions and generated code become context, so you can refine charts and clean data conversationally.
Fortalezas y ventajas
+Analyze data by describing requests in plain English — no R syntax required
+Runs generated code and returns results, plots and a downloadable HTML report
+Context carries within a session, so you can refine charts and clean data conversationally
+
Guided tabs for EDA, distributions, tables and correlations speed up common tasks
+Available as an R package from GitHub, and Python mode is supported
+Clear privacy stance with automatic deletion of uploaded data after the session
Limitaciones
–Generated code can be logically wrong even when it runs without error, so results need validation
–Analyzes only traditional statistical data where rows are observations and columns are variables
–Non-profit use is free but commercial use requires a paid license
–By default a small random sample of rows is sent to OpenAI unless you opt out in settings
–Complex or messy datasets are better handled by its sibling tool Datably.ai
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