satRdays Paris 2019
| title | author | length |
|---|---|---|
| Programming in the Tidyverse | Lionel Henry | 51m |
Explains how tidyverse packages like dplyr and ggplot2 use data masking and why that breaks simple reuse: a loop passing column names yields a mean of a string… | ||
| A Shiny application for job matching | Fanny Meyer, Victor Perrier, Étienne Sanchez | 37m |
Prototype Shiny app matches a user profile to job ads using text mining on 150 PDFs of formatted job descriptions; pipeline uses tokenization, n‑grams… | ||
| Footbal meets graphs | Bea Hernández | 24m |
Graph model of leagues, matches and teams in Neo4j + cypher quantifies two concrete findings: a measurable home advantage (Barcelona shows ~+0.11 more home… | ||
| R & Space : GI Science with R | Hadrien Commenges | 22m |
R code reproduces a full workflow: ingest household travel surveys, build individual activity sequences, map hourly population locations, compute Duncan… | ||
| A Journey Into Data Science: From an Idea to a Viable Product | Denis Roussel | 19m |
Builds an R package to standardize tax spreadsheets that ingests dozens of yearly Excel/CSV files, reconciles changing column names and department codes, turns… | ||
| Everything but maps with spatial tools | Sébastien Rochette | 25m |
Focuses on using rasters as the primary data object rather than maps, with concrete examples and tools. Correlates time‑series microscopy rasters (calcium vs… | ||
| Need for speed: the data manipulation version | Suzan Baert | 44m |
Work with multi‑gigabyte CSVs (600MB, 2.5GB, 5GB, ~7GB) and avoid the repeated “cannot allocate a vector” crashes by changing approach: benchmark on the actual… | ||
| Future: Friendly Parallel Processing in R for Everyone | Henrik Bengtsson | 51m |
Introduces the future package as a minimal, cross‑platform futures API that actually runs on local multicore, SSH‑connected machines, HPC schedulers and cloud… | ||
| nothing matches | ||