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Cohort Tool

$29

Cohort analysis with user retention heatmaps, behavior segmentation, and time-series grouping.

📁 9 files

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📁 File Structure 9 files

cohort-tool/ ├── LICENSE ├── README.md ├── examples/ │ └── sample_cohort_events.json ├── free-sample.zip ├── guide/ │ ├── 01_features.md │ ├── 02_quick-start.md │ └── 03_license.md ├── index.html └── src/ └── cohort_tool.py

📖 Documentation Preview README excerpt

Cohort Tool

Cohort analysis: user retention heatmaps, behavior segmentation, and time-series grouping. Understand how user behavior changes over time.

Features

Retention analysis — Track what percentage of users remain active over time
Flexible cohorts — Group by month, week, or day
Heatmap output — HTML retention heatmap with color-coded cells
Average retention — See the overall retention curve across all cohorts
JSON export — Machine-readable results for dashboards and further analysis
CLI and library — Use from the command line or import as a module

Requirements

Python 3.10+
No external dependencies (stdlib only)

Quick Start


# Monthly cohort retention
python src/cohort_tool.py --events examples/sample_cohort_data.json --cohort-by month

# Weekly cohorts with HTML heatmap
python src/cohort_tool.py --events data.json --cohort-by week --html heatmap.html

# Export results
python src/cohort_tool.py --events data.json --output retention.json --periods 12

Output Example


================================================================================
  COHORT RETENTION (MONTH)
  Total users: 450
================================================================================

  Cohort          Size     P0     P1     P2     P3     P4
  --------------------------------------------------------
  2026-01           80  100.0%  72.5%  58.8%  45.0%  38.8%
  2026-02           95  100.0%  68.4%  52.6%  41.1%
  2026-03          110  100.0%  70.9%  55.5%
  2026-04           85  100.0%  65.9%
  2026-05           80  100.0%
  --------------------------------------------------------
  Average                100.0%  69.4%  55.6%  43.0%  38.8%

License

MIT License — see LICENSE file.

📄 Code Sample .py preview

src/cohort_tool.py #!/usr/bin/env python3 """ Cohort Tool — Analytics Hub (DataNest) Cohort analysis: user retention, behavior segmentation, and time-series grouping. Understand how user behavior changes over time by grouping users into cohorts based on their signup date or first action. Usage: python cohort_tool.py --events users.json --cohort-by month --metric retention python cohort_tool.py --events data.csv --cohort-by week --output report.json Dependencies: Python 3.10+ stdlib only (no pip packages) License: MIT """ from __future__ import annotations import argparse import csv import json import logging import sys from collections import defaultdict from dataclasses import dataclass, field from datetime import datetime, timedelta, timezone from pathlib import Path from typing import Any logger = logging.getLogger("cohort_tool") # --------------------------------------------------------------------------- # Data models # --------------------------------------------------------------------------- @dataclass class CohortRow: """A single cohort's retention data across periods.""" cohort_label: str cohort_size: int retention: list[float] = field(default_factory=list) # % retained per period active_counts: list[int] = field(default_factory=list) # absolute active per period @dataclass class CohortResult: """Complete cohort analysis result.""" cohorts: list[CohortRow] = field(default_factory=list) periods: list[str] = field(default_factory=list) # Period labels metric: str = "retention" cohort_by: str = "month" # ... 305 more lines ...

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