Gantt Style Time Line Plot (In Base R)

Gantt style time line plot (in base R)

While the y-axis is categorical all you need to do is assign numbers to the categories (1:5) and track them. Using the default as.numeric() of the factor will usually number them alphabetically but you should check anyway. Make your plot with the xaxt = 'n' argument. Then use the axis() command to put in a y-axis.

axis(2, 1:5, myLabels)

Keep in mind that whenever you're plotting the only way to place things is with a number. Categorical x or y values are always just the numbers 1:nCategories with category name labels in place of the numbers on the axis.

Something like the following gets you close enough (assuming your data.frame object is called datf)...

datf$pNum <- as.numeric(datf$person)
plot(datf$pNum, xlim = c(0, 53), type = 'n', yaxt = 'n', xlab ='Duration (words)', ylab = 'person', main = 'Speech Duration')
axis(2, 1:5, sort(unique(datf$person)), las = 2, cex.axis = 0.75)
with(datf, segments(start, pNum, end, pNum, lwd = 3, lend=2))

Gantt plot in base r - modifying plot properties

I slightly modified your function to account for NA in start and end dates :

plotGantt <- function(data, res.col='resources', 
                      start.col='start', end.col='end', res.colors=rainbow(30))
{
  #slightly enlarge Y axis margin to make space for labels
  op <- par('mar')
  par(mar = op + c(0,1.2,0,0)) 

  minval <- min(data[,start.col],na.rm=T)
  maxval <- max(data[,end.col],na.rm=T)

  res.colors <- rev(res.colors)
  resources <- sort(unique(data[,res.col]),decreasing=T)

  plot(c(minval,maxval),
       c(0.5,length(resources)+0.5),
       type='n', xlab='Duration',ylab=NA,yaxt='n' )
  axis(side=2,at=1:length(resources),labels=resources,las=1)
  for(i in 1:length(resources))
  {
    yTop <- i+0.5
    yBottom <- i-0.5
    subset <- data[data[,res.col] == resources[i],]
    for(r in 1:nrow(subset))
    {
      color <- res.colors[((i-1)%%length(res.colors))+1]
      start <- subset[r,start.col]
      end <- subset[r,end.col]
      rect(start,yBottom,end,yTop,col=color)
    }
  }
  par(mar=op) # reset the plotting margins
  invisible()
}

In this way, if you simply append all your possible group values to your data you'll get them printed on the y axis. e.g. :

mydf1 <- data.frame(startyear=2000:2009, endyear=2001:2010,
                    group=c(1,1,1,1,2,2,2,1,1,1))
# add all the group values you want to print with NA dates
mydf1 <- rbind(mydf1,data.frame(startyear=NA,endyear=NA,group=1:4))

plotGantt(mydf1, res.col='group', start.col='startyear', end.col='endyear', 
          res.colors=c('red','orange','yellow','gray99'))

About the colors, at the moment the ordered res.colors are applied to the sorted groups; so the 1st color in res.colors is applied to 1st (sorted) group and so on...

How to modify my R code to plot this kind of gantt chart?

Extending the answer suggested by @Tyler Rinker:

library(ggplot2)

df <- read.table(text="Task, Start, End
A,2,7
B,5,10
C,5,12
D,16,22
E,18,20", 
                 header=TRUE,
                 sep = ',')

p <- ggplot(df, aes(colour=Task))
p <- p + theme_bw()
p <- p + geom_segment(aes(x=Start, 
                          xend=End, 
                          y=Task, 
                          yend=Task), 
                      size=2)
p <- p + geom_point(aes(x=Start,
                        y=Task),
                    size=5)
p <- p + geom_point(aes(x=End,
                        y=Task),
                    size=5)
p <- p + geom_text(aes(x=Start-0.5,
                       y=Task,
                       label=Task),
                   fontface="bold")
p <- p + opts(legend.position="None",
              panel.grid.major = theme_blank(),
              axis.text.y = theme_blank())
p <- p + xlab("Duration")
p

Produces:

EDIT to produce centred labels

library(ggplot2)

df <- read.table(text="Task, Start, End
A,2,7
B,5,10
C,5,12
D,16,22
E,18,20", 
                 header=TRUE,
                 sep = ',')

df$TaskLabel <- df$Task
df$Task <- as.numeric(df$Task)

p <- ggplot(df, aes(colour=TaskLabel))
p <- p + theme_bw()
p <- p + geom_segment(aes(x=Start, 
                          xend=End, 
                          y=Task, 
                          yend=Task), 
                      size=2)
p <- p + geom_point(aes(x=Start,
                        y=Task),
                    size=5)
p <- p + geom_point(aes(x=End,
                        y=Task),
                    size=5)
p <- p + geom_text(aes(x=(Start+End)/2,
                       y=Task+0.25,
                       label=TaskLabel),
                   fontface="bold")
p <- p + opts(legend.position="None",
              panel.grid.major = theme_blank(),
              axis.text.y = theme_blank())
p <- p + xlab("Duration")
p

Which in turn produces:

Plot grouped point data using only base R code

set.seed(1)
variables <- paste0('V_', seq(1,16,1))
data <- data.frame(t(rbind(variables, rnorm(16,0,1),rnorm(16,0,1), rnorm(16,0,1))))
colnames(data) <- c('variables','OLS', 'IV', '2SLS')

attach(data)
#> The following object is masked _by_ .GlobalEnv:
#>     variables

variables <- factor(variables, 
                    levels = variables[order(as.numeric(gsub("V_","", variables)))])

plot.default(variables,as.double(OLS),type='p',xaxt='n', ylab="value", cex=1, col="red")
points(x=variables, y=as.double(IV), col="blue")
points(x=variables, y=as.double(`2SLS`), col="green")
axis(side = 1, at = as.numeric(variables), labels = variables)

detach(data)

^{Created on 2019-06-19 by the reprex package (v0.3.0)}

Gantt charts with R

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

---

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:

---

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:

---

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)

Deviation chart in base graphics

You can convert the factor in a numeric variable, supress the x-axis and then add the correct labels to the plot:

df$ID2 <- factor(letters[df$ID]) # Use letters to show that this is working

plot(range(as.numeric(df$ID2)), range(df$score), type = "n", xaxt = "n")
segments(as.numeric(df$ID2), df$score, as.numeric(df$ID2), mid)
axis(1, at = seq_along(levels(df$ID2)), labels = levels(df$ID2))

How do I create a bar graph in r?

If you need both IN and OUT plotted in the same plot, you can do that by changing up the data a little, as shown below:

library(ggplot2)
IN <- c(3.5, 5.75, 9, 13.25, 13, 9.5, 9.25, 6.75, 7, 4.25, 3.25, 1.75, 0)
OUT <- c(0.25, 2, 5.25, 8.5, 10.5, 11, 11.75, 9.25, 9.5, 7, 3.75, 4, 3.5)
type <-c(rep("IN", 13), rep("OUT", 13))
values <- c(IN, OUT)

foo <- c("10~11", "11~12", "12~13", "13~14", "14~15", "15~16", 
               "16~17", "17~18", "18~19", "19~20", "20~21", "21~22", "22~23")
dat <- data.frame(foo, values)
p <- ggplot(dat, aes(foo, values))
p + geom_bar(stat = "identity", aes(fill = type), position = "dodge")

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