blue-yonder/tsfresh — GitHub trend

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FINDING #5131 · UNIT ID 71996613

blue-yonder/tsfresh

Automatic extraction of relevant features from time series:

[ JUPYTER NOTEBOOK ][ ORG ][ GITHUB ↗ ]

SURPRISE SCORE

0.00

Score Breakdown

SURPRISE0.00418

ENGAGEMENT0.32

FRESHNESS1.00

SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE

SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)

1% OF STARS IN ARCHIVE

Growth Telemetry

VELOCITY /D

9.71

ACCEL

+6.57

RETENTION

0.0%

PEAK 2026-09-12 · FORK-RETENTION 0.0% · 68 STARS / WINDOW

Author Audience

AUDIENCE

2,282

FOLLOWERS

OWNER ★

10,610

Engagement Signals

FORKS

1,284

ISSUE AUTH

PR AUTH

UNIQUE STARGAZERS 68 / 68 (DIVERSITY 1.00)

Why This Is A Finding

blue-yonder/tsfresh собрал 68 звёзд за окно, тогда как у автора всего 80 подписчиков — эффективная аудитория ≈ 2,282. Это даёт surprise-индекс 0.00418 (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.

Related Findings

RANKS ABOVE 48% OF 9789 FINDINGS

#524philshiu/Drosophila_brain_model[ JUPYTER NOTEBOOK ]0.0302 #992xbsheng/atguigu-note[ JUPYTER NOTEBOOK ]0.0178 #1033Lordog/dive-into-llms[ JUPYTER NOTEBOOK ]0.0171 #1276gmonce/scikit-learn-book[ JUPYTER NOTEBOOK ]0.0139 #1458MLO-lab/LeVJEPA[ JUPYTER NOTEBOOK ]0.0123

METRICS IN CONTEXT

MEDIAN ACROSS ALL 9789 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW

METRICVALUEMEDIANΔ MEDPERCENTILE

SCORE0.000.00-0.00ABOVE 48%

VELOCITY9.713.43+6.29ABOVE 78%

RETENTION0.0%37.5%-37.5 PPABOVE 0%

FORKS1,284120+1,164ABOVE 92%

SURPRISE0.000.01-0.00ABOVE 37%