blue-yonder/tsfresh — GitHub trend

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FINDING #855 · UNIT ID 71996613

blue-yonder/tsfresh

Automatic extraction of relevant features from time series:

[ JUPYTER NOTEBOOK ][ ORG ][ GITHUB ↗ ]

SURPRISE SCORE

0.00

Score Breakdown

SURPRISE0.0271

ENGAGEMENT0.30

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

63.00

ACCEL

0.00

RETENTION

0.0%

PEAK 2026-09-12 · FORK-RETENTION 0.0% · 63 STARS / WINDOW

Author Audience

AUDIENCE

2,282

FOLLOWERS

OWNER ★

10,610

Engagement Signals

FORKS

1,284

ISSUE AUTH

PR AUTH

UNIQUE STARGAZERS 63 / 63 (DIVERSITY 1.00)

Why This Is A Finding

blue-yonder/tsfresh собрал 63 звёзд за окно, тогда как у автора всего 80 подписчиков — эффективная аудитория ≈ 2,282. Это даёт surprise-индекс 0.0271 (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 83% OF 4998 FINDINGS

#194philshiu/Drosophila_brain_model[ JUPYTER NOTEBOOK ]0.11 #558fbach2000/Learning_Theory_from_First_Principles[ JUPYTER NOTEBOOK ]0.0219 #568xbsheng/atguigu-note[ JUPYTER NOTEBOOK ]0.0216 #604mcarfagno/mpc_python[ JUPYTER NOTEBOOK ]0.0198 #620mit-zardini-lab/pyncd[ JUPYTER NOTEBOOK ]0.0189

METRICS IN CONTEXT

MEDIAN ACROSS ALL 4998 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW

METRICVALUEMEDIANΔ MEDPERCENTILE

SCORE0.010.00+0.01ABOVE 83%

VELOCITY63.009.00+54.00ABOVE 93%

RETENTION0.0%0.0%0.0 PPABOVE 0%

FORKS1,284459+825ABOVE 68%

SURPRISE0.030.01+0.02ABOVE 74%