Github Trends®
751 findingsmedian surprise 0.028window 90 days
UNIT / TREND-MONITOR · REV 2.6
[ 90 days window ]
SOURCE: gharchive
FINDING #608 · UNIT ID 1126412969
igerber/diff-diff
Difference-in-Differences causal inference in Python. Callaway-Sant'Anna, Synthetic DiD, Honest DiD, event studies. sklearn-like API, validated against R.
[ PYTHON ][ GITHUB ↗ ]
SURPRISE SCORE
0.00

Score Breakdown

SURPRISE0.0202
ENGAGEMENT0.20
FRESHNESS1.31
SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE
SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)
55% OF STARS IN ARCHIVE
[BOT] SUSPECTED STAR BOT — SCORE PENALIZED. SIGNATURES:
S2 · NO EXTERNAL ISSUE/PR AUTHORS DESPITE 100+ STARS
S5 · PREDATES WINDOW, YET HALF+ OF ALL ITS STARS LANDED IN IT
S7 · THIS REPO IS ~ALL OF THE OWNER'S STARS

Growth Telemetry

VELOCITY /D
2.11
ACCEL
+0.02
RETENTION
4.0%
PEAK 2026-05-11 · FORK-RETENTION 0.0% · 190 STARS / WINDOW

Author Audience

AUDIENCE
64
FOLLOWERS
29
OWNER ★
354

Engagement Signals

FORKS
45
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 190 / 190 (DIVERSITY 1.00)

Why This Is A Finding

igerber/diff-diff собрал 190 звёзд за окно, тогда как у автора всего 29 подписчиков — эффективная аудитория ≈ 64. Это даёт surprise-индекс 0.0202 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 0.0% и 0 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация положительная — рост ещё не выдохся.

METRICS IN CONTEXT

MEDIAN ACROSS ALL 751 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.000.00-0.00ABOVE 19%
VELOCITY2.116.61-4.50ABOVE 14%
RETENTION4.0%22.2%-18.2 PPABOVE 10%
FORKS4597-52ABOVE 33%
SURPRISE0.020.03-0.01ABOVE 39%