dplyr
for R developers, data analysts
Why this scored 7
every term, weightedIts fastest-moving item, measured against the pace of its own source
Whether that velocity is itself speeding up, as a per-hour rate
How many independent communities its own items come from
Decays to zero over 14 days, counted from when we first saw it
Subtracted once something is big and old — sized by its biggest item, aged from when we first saw it
Weights are hand-tuned, not learned — we're calibrating them against realized trends as history accumulates. On an entity's first sighting there's no previous reading to compare against, so acceleration starts from a neutral prior rather than a measurement, and velocity falls back to engagement over its whole lifetime until a second reading exists. Full methodology
Outlook
low confidence · estimate, not a guarantee7-day
~9
range 0–21
14-day
~9
range 0–24
30-day
~9
range 0–28
Signal history
7-day window (free)projected trajectory (estimate, not a guarantee)
The evidence
The live items this entity's score aggregates — every community independently talking about it right now. This is the corroboration, shown, not claimed.
- 118
How to summarise hourly data of the Formal class 'Period'?
Data summarization technique · for data scientists
stackoverflowSteadydata32d ago - 215
Why does case_when() work with one RHS value but return character(0) with another?
Shows inconsistent case_when behavior that can break R data transformation scripts. · for r developers, data analysts
stackoverflowSteadydata15d ago - 315
How to loop a function and save the outputs of each run as independent objects?
Shows how to loop a function in R and store each iteration as a separate object using dplyr. · for r developers, data analysts
stackoverflowSteadydata27d ago - 414
dplyr::pick behaving differently than the deprecated dplyr::cur_data for list columns
dplyr::pick shows unexpected behavior with list columns, requiring attention for tidyverse data pipelines. · for R developers, data analysts
stackoverflowSteadydata12d ago - 514
Grouping by variables in a dataset across multiple columns
Explains how to group variables across multiple columns using R's dplyr. · for R developers, data analysts
stackoverflowSteadydata26d ago - 65
How to handle the ... parameter when programming with dplyr
Parameter handling issue · for r devs
stackoverflowSteadydata61d ago - 74
Performing summary statistics on a data table in R (with two different classes)
R data analysis · for data scientists
stackoverflowSteadydata47d ago