Umami is a modern, privacy-focused analytics platform. An open-source alternative to Google Analytics, Mixpanel and Amplitude.

🏃 An R package for advanced sports performance analysis and training load monitoring using Strava data.

A web application to find patients, build cohorts and visualize health records

the source code of the COOL system

Algorithmic Marketing based Project to do Customer Segmentation using RFM Modeling and targeted Recommendations based on each segment

A Snakemake workflow to process single samples or cohorts of Illumina paired-end sequencing data (WGS or WES) using trim galore/bwa/GATK4/parabricks.

Cohort graph (Cohort Analysis)

A fully interactive data storytelling dashboard for e-commerce analytics. Built with Python, Streamlit, and Plotly, it transforms transactional data into actionable insights through KPIs, cohort retention, RFM segmentation, and global visualizations, perfect for analysts and data scientists.

A comprehensive guide and codebase for building interactive storytelling dashboards with Python, Streamlit, and Plotly. Learn how to transform static analytics into dynamic, user-driven data experiences that engage and inspire, featuring RFM segmentation, cohort analysis, and real-world insights.

Flowchart is a STATA module/package that generates publication-quality Subject Disposition Flowchart Diagrams in LaTeX Format. This package generates PGF/TikZ code through texdoc, compiled in LaTeX to produce the diagram as a PDF. The final diagram is the same in style as ones used in the PRISMA Statement, CONSORT 2010 Statement, or STROBE Statement Reporting Guidelines.

Custom Cohort Visualization based on Kibana NP

An R package for easy cohort analysis with event data

A long-form analytics article on why KPIs fail when the denominator silently changes. Covers denominator contracts, eligibility vs observed vs attempted populations, drift/coverage failure modes, mix shifts, time alignment, and a practical audit checklist to design decision-safe ratio metrics that don’t lie.

NHC: A computational approach to detect physiological homogeneity in the midst of genetic heterogeneity

Jupyter Notebook Praktikum Projects. This is repository with data analyst educational projects from Yandex.Praktikum.

A deep-dive analytics article on why most KPI “trends” are actually measurement artifacts. Covers the fake-trend taxonomy (schema drift, coverage loss, time shifts, backfills, dedupe, sampling, mix change), a Trend Courtroom evidence protocol, segment invariance tests, and copy-ready checklists + a Trend Report Card for decision safety.

Deciphering Bitcoin Blockchain Data by Cohort Analysis

Longform data analysis article arguing every “dataset” is actually three: Observed (captured rows), Missing (what should exist but doesn’t), and Excluded (what filters/joins/dropna removed). Includes dataset accounting, join-loss and missingness audits, segmentation checks, and practical templates to prevent biased KPIs and wrong conclusions.

This project uses Python and Jupyter Notebook to perform time-based Cohorts Analysis to assess and compare retention, order items quantity and order revenue of different customer cohorts.

The fastest way to make sense of a transaction log.

This repo is a code demo that implements a custom Customer Retention Analysis class with a number of helpful methods/functions to generate customer churn insights frequently used for marketing analytics to understand the growth and change of your customer base (new vs retained vs lost) .

tPC - Causal discovery with temporal background

A web-based visual analysis tool for creating and characterizing cohorts.

This project focus on customer analysis and segmentation. Which help to generate specific marketing strategies targeting different groups. RFM Analysis, Cohort Analysis, and K-means Clusters were conducted on a UK-based online retail transaction dataset with 1,067,371 rows of records hosted on the UCI Machine Learning Repository.

🫀 Webapp to explore cohorts metadata for the iCARE4CVD project

No description provided.

cohorts.py makes generating cohort analysis from raw data a magical experience

This project involves cohort analysis and customer segmentation to help an e-commerce giant improve its product offerings, customer relations and maximize profit.

A Python-based repo for modeling and predicting customer behavior. This project focuses on implementing various statistical and probabilistic models to analyze customer preferences, purchase patterns, and future actions.

https://matthieuvion.github.io/lmd_viz/ 236k comments of Le Monde on Ukraine. A proxy to measure people' engagement. Semantic search & SBERT models testing via Sentence-Transformer / Faiss