googleVis 0.7.0 adds Gantt charts

Version 0.7.0 of the googleVis R package has been released, adding a new function for Gantt charts. Gantt charts are helpful to illustrates a project schedule and its dependencies.

Following the Google documentation the project has to be broken down into task IDs, task names, resources, start date, end dates, task duration (in milliseconds), how far the task has been completed (in percent), and finally any dependencies to other tasks IDs.

Here is an example for a project to write a research paper:

# Helper function
daysToMilliseconds <- function(days){
  days * 24 * 60 * 60 * 1000
}
# Project outline
dat <- data.frame(
  taskID = c("Research", "Write", "Cite", "Complete", "Outline"),
  taskName = c("Find sources", "Write Paper",  
               "Create bibliography", "Hand in paper", 
               "Outline paper"),
  resource = c(NA, "write", "write", "complete", "write"),
  start = c(as.Date("2022-01-01"), NA, NA, NA, NA),
  end = as.Date(c("2022-01-05", "2022-01-09", "2022-01-07", 
                  "2022-01-10", "2022-01-06")),
  duration = c(NA, daysToMilliseconds(c(3, 1, 1, 1))),
  percentComplete = c(100, 25, 20, 0, 100),
  dependencies = c(NA, "Research, Outline", "Research", 
                   "Cite, Write", "Research"))
dat

##     taskID            taskName resource      start        end  duration
## 1 Research        Find sources     <NA> 2022-01-01 2022-01-05        NA
## 2    Write         Write Paper    write       <NA> 2022-01-09 259200000
## 3     Cite Create bibliography    write       <NA> 2022-01-07  86400000
## 4 Complete       Hand in paper complete       <NA> 2022-01-10  86400000
## 5  Outline       Outline paper    write       <NA> 2022-01-06  86400000
##   percentComplete      dependencies
## 1             100              <NA>
## 2              25 Research, Outline
## 3              20          Research
## 4               0       Cite, Write
## 5             100          Research

To create a Gantt chart we load the googleVis package and use the gvisGantt function, mapping the various columns in our data to the relevant arguments:

library(googleVis)
gntt <- gvisGantt(dat, taskID = "taskID",
                  taskName = "taskName", 
                  resource = "resource",
                  start = "start", end = "end", 
                  duration = "duration",
                  percentComplete = "percentComplete",
                  dependencies = "dependencies", 
                  options = list(height='300', width = 'auto'))

Finally, we can display the Gantt chart using the plot method:

plot(gntt)

For more information about the googleVis package and other visualisation methods visit: https://mages.github.io/googleVis/

Session info

sessionInfo()

## R version 4.2.0 (2022-04-22)
## Platform: aarch64-apple-darwin20 (64-bit)
## Running under: macOS Monterey 12.3.1
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/lib/libRlapack.dylib
## 
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] googleVis_0.7.0
## 
## loaded via a namespace (and not attached):
##  [1] bookdown_0.26    codetools_0.2-18 digest_0.6.29    R6_2.5.1        
##  [5] jsonlite_1.8.0   magrittr_2.0.3   evaluate_0.15    blogdown_1.10   
##  [9] stringi_1.7.6    rlang_1.0.2      cli_3.3.0        rstudioapi_0.13 
## [13] jquerylib_0.1.4  bslib_0.3.1      rmarkdown_2.14   tools_4.2.0     
## [17] stringr_1.4.0    xfun_0.31        yaml_2.3.5       fastmap_1.1.0   
## [21] compiler_4.2.0   htmltools_0.5.2  knitr_1.39       sass_0.4.1