Gantt charts with R [closed]

Question

Has anybody used R to create a Gantt chart? I'm looking for something sophisticated, if possible (looking more or less like this).

P.S. I could live without the dependency arrows.

Answer 1

There are now a few elegant ways to generate a Gantt chart in R.

Using Candela

library(candela)  data <- list(     list(name='Do this', level=1, start=0, end=5),     list(name='This part 1', level=2, start=0, end=3),     list(name='This part 2', level=2, start=3, end=5),     list(name='Then that', level=1, start=5, end=15),     list(name='That part 1', level=2, start=5, end=10),     list(name='That part 2', level=2, start=10, end=15))  candela('GanttChart',     data=data, label='name',     start='start', end='end', level='level',     width=700, height=200) 

Using DiagrammeR

library(DiagrammeR)  mermaid(" gantt dateFormat  YYYY-MM-DD title A Very Nice Gantt Diagram  section Basic Tasks This is completed             :done,          first_1,    2014-01-06, 2014-01-08 This is active                :active,        first_2,    2014-01-09, 3d Do this later                 :               first_3,    after first_2, 5d Do this after that            :               first_4,    after first_3, 5d  section Important Things Completed, critical task      :crit, done,    import_1,   2014-01-06,24h Also done, also critical      :crit, done,    import_2,   after import_1, 2d Doing this important task now :crit, active,  import_3,   after import_2, 3d Next critical task            :crit,          import_4,   after import_3, 5d  section The Extras First extras                  :active,        extras_1,   after import_4,  3d Second helping                :               extras_2,   after extras_1, 20h More of the extras            :               extras_3,   after extras_1, 48h ") 

Find this example and many more on DiagrammeR GitHub

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If your data is stored in a data.frame, you can create the string to pass to mermaid() by converting it to the proper format.

Consider the following:

df <- data.frame(task = c("task1", "task2", "task3"),                  status = c("done", "active", "crit"),                  pos = c("first_1", "first_2", "first_3"),                  start = c("2014-01-06", "2014-01-09", "after first_2"),                  end = c("2014-01-08", "3d", "5d"))  #   task status     pos         start        end #1 task1   done first_1    2014-01-06 2014-01-08 #2 task2 active first_2    2014-01-09         3d #3 task3   crit first_3 after first_2         5d 

Using dplyr and tidyr (or any of your favorite data wrangling ressources):

library(tidyr) library(dplyr)  mermaid(   paste0(     # mermaid "header", each component separated with "\n" (line break)     "gantt", "\n",      "dateFormat  YYYY-MM-DD", "\n",      "title A Very Nice Gantt Diagram", "\n",     # unite the first two columns (task & status) and separate them with ":"     # then, unite the other columns and separate them with ","     # this will create the required mermaid "body"     paste(df %>%             unite(i, task, status, sep = ":") %>%             unite(j, i, pos, start, end, sep = ",") %>%             .$j,            collapse = "\n"     ), "\n"   ) ) 

As per mentioned by @GeorgeDontas in the comments, there is a little hack that could allow to change the labels of the x axis to dates instead of 'w.01, w.02'.

Assuming you saved the above mermaid graph in m, do:

m$x$config = list(ganttConfig = list(   axisFormatter = list(list(     "%b %d, %Y"      ,htmlwidgets::JS(       'function(d){ return d.getDay() == 1 }'      )   )) )) 

Which gives:

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Using timevis

From the timevis GitHub:

timevis lets you create rich and fully interactive timeline visualizations in R. Timelines can be included in Shiny apps and R markdown documents, or viewed from the R console and RStudio Viewer.

library(timevis)  data <- data.frame(   id      = 1:4,   content = c("Item one"  , "Item two"  ,"Ranged item", "Item four"),   start   = c("2016-01-10", "2016-01-11", "2016-01-20", "2016-02-14 15:00:00"),   end     = c(NA          ,           NA, "2016-02-04", NA) )  timevis(data) 

Which gives:

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Using plotly

I stumbled upon this post providing another method using plotly. Here's an example:

library(plotly)  df <- read.csv("https://cdn.rawgit.com/plotly/datasets/master/GanttChart-updated.csv",                 stringsAsFactors = F)  df$Start  <- as.Date(df$Start, format = "%m/%d/%Y") client    <- "Sample Client" cols      <- RColorBrewer::brewer.pal(length(unique(df$Resource)), name = "Set3") df$color  <- factor(df$Resource, labels = cols)  p <- plot_ly() for(i in 1:(nrow(df) - 1)){   p <- add_trace(p,                  x = c(df$Start[i], df$Start[i] + df$Duration[i]),                   y = c(i, i),                   mode = "lines",                  line = list(color = df$color[i], width = 20),                  showlegend = F,                  hoverinfo = "text",                  text = paste("Task: ", df$Task[i], "<br>",                               "Duration: ", df$Duration[i], "days<br>",                               "Resource: ", df$Resource[i]),                  evaluate = T   ) }  p 

Which gives:

You can then add additional information and annotations, customize fonts and colors, etc. (see blog post for details)