Package: sugrrants 0.2.9
sugrrants: Supporting Graphs for Analysing Time Series
Provides 'ggplot2' graphics for analysing time series data. It aims to fit into the 'tidyverse' and grammar of graphics framework for handling temporal data.
Authors:
sugrrants_0.2.9.tar.gz
sugrrants_0.2.9.zip(r-4.7)sugrrants_0.2.9.zip(r-4.6)sugrrants_0.2.9.zip(r-4.5)
sugrrants_0.2.9.tgz(r-4.6-any)sugrrants_0.2.9.tgz(r-4.5-any)
sugrrants_0.2.9.tar.gz(r-4.7-any)sugrrants_0.2.9.tar.gz(r-4.6-any)
sugrrants_0.2.9.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
sugrrants/json (API)
NEWS
| # Install 'sugrrants' in R: |
| install.packages('sugrrants', repos = c('https://earowang.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/earowang/sugrrants/issues
- hourly_peds - Pedestrian counts in Melbourne city
statistical-graphicstime-series
Last updated from:204a766b59. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 188 | ||
| source / vignettes | OK | 198 | ||
| linux-release-x86_64 | OK | 163 | ||
| macos-release-arm64 | OK | 107 | ||
| macos-oldrel-arm64 | OK | 99 | ||
| windows-devel | OK | 122 | ||
| windows-release | OK | 119 | ||
| windows-oldrel | OK | 119 | ||
| wasm-release | OK | 127 |
Exports:%>%draw_key_acffacet_calendarFacetCalendarframe_calendargeom_acfGeomAcfprettifystat_acfvars
Dependencies:clicpp11dplyrfarvergenericsggplot2gluegtableisobandlabelinglifecyclelubridatemagrittrpillarpkgconfigR6RColorBrewerrlangS7scalestibbletidyselecttimechangeutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| sugrrants: supporting graphs for analysing time series | sugrrants-package |
| Lay out panels in a calendar format | FacetCalendar facet_calendar |
| Rearrange a temporal data frame to a calendar-based data format using linear algebra | frame_calendar prettify |
| Autocorrelation for temporal data | GeomAcf geom_acf |
| Pedestrian counts in Melbourne city | hourly_peds |
| Autocorrelation for temporal data | stat_acf |
