About the startup
StatCode is an AI-powered statistical analysis workspace that turns datasets and plain-language questions into transparent, executable Python, R, and SQL workflows. Instead of providing a black-box answer, StatCode generates code that users can inspect, run, verify, and adapt—making every result easier to understand and reproduce. Upload a dataset, describe the analysis you need, and select your preferred programming language. StatCode helps generate analysis-ready code for exploratory data analysis, data visualization, regression, t-tests, ANOVA, correlation, and other common statistical methods. Run the code directly in the browser, review the outputs, examine tables and charts, identify potential issues, and refine the analysis before exporting a polished draft. StatCode removes the friction between knowing what statistical question to ask and knowing how to implement it correctly in code. It reduces time spent searching for syntax, switching between tools, debugging boilerplate, and manually translating the same analysis across different programming languages. Built for students, researchers, educators, data analysts, and anyone learning applied statistics, StatCode is useful for coursework, research projects, teaching demonstrations, exploratory analysis, and rapid prototyping. Whether you are learning your first statistical test or accelerating an existing analytical workflow, StatCode helps you move from raw data to clear, reproducible results faster—while keeping the underlying code visible and under your control.
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Explore expertise in Data & Analytics
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Vinicius FagundesI help companies turn raw data into leads, fraud signals, and AI products. |
Ben Griffis⚽️ Data Scientist, open for work | Past: Kolding IF 🇩🇰 & Loudoun United 🇺🇸 | Views my own | bengriffis.com & griffisanalysis.beehiiv.com |
Rob ArthurData journalist, data scientist, freelancer published many places: WSJ, NYT, the Atlantic, the Guardian, etc. |
Media about Data & Analytics
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Data ProfessorNewsletter |
Mindful ModelerNewsletter · Christoph Molnar |
To Data & BeyondNewsletter · Youssef Hosni |
Founder stories from Data & Analytics startups
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| Story |
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Plausible's open-source SaaS post clocks $1M ARR on 2 June 2022Marko Saric's June 2022 Plausible post, using Uku Täht's origin and the team's public MRR ladder, states $83,637 MRR and $1 million ARR on 2 June 2022 with 7,000-plus paying subscribers, not a $3.1 million figure the fou |
Paul Copplestone's alpha postmortem counts databases and signups, not ARRPaul Copplestone says an early GitHub follower posted Supabase on Hacker News in May 2020, after which hosted databases jumped and, in his July postmortem, the team saw about 30,000 site visitors and more than 1,400 sign |
Adriaan van Rossum logged $100K ARR, not $100K MRR, after an earlier $30K ARR yearAdriaan van Rossum wrote in March 2021 that Simple Analytics hit $100K annual recurring revenue while shipping a new data stack; two years earlier he had described a $30K ARR milestone, a different unit and date. |
Iuliia Shnai's public Papermark posts skip the $45k MRR headlineIuliia Shnai says Papermark began as Marc's open-source DocSend alternative after she built ten projects in a year, later claiming $3 million ARR at 28 months with two full-time people; she did not state $45,000 MRR in t |
Browse Data & Analytics categories
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