Project planning with plotly

Something a little different today for a quick chat about my latest project and why I’m finding the plotly package so helpful!

Are you like me and physically can’t function unless you’ve got a to do list in front of you? Well even if you’re not, imagine my pain while I’m wearing my non - Locke Data hat and trying to plan out the final year of my PhD thesis!

I needed something that updated easily, something visual and something to keep my supervisors in the know. I’ve previously made gantt charts using LaTeX but found it ridiculously clunky to get working and decided there had to be a better way. And if I could include interactivity then all the better, which is how I discovered plotly.


The plotly package makes interactive, publication quality graphs online. It uses the JavaScript graphing library and is really versatile! You can make graphs, maps, 3D plots and, as I’m about to explain, gantt charts.


Step by Step Gantt Chart

Install the packages you need for generating the gantt chart


Setting fonts isn’t necessary as there are defaults, but it’s always nice to know how to do it should you want to.

f <- list(
  family = "Courier New, monospace",
  size = 18,
  color = "#7f7f7f"

Set a title for the X axis. Uncomment the Y axis if you’d like to label that too :)

x <- list(
  title = "Date",
  titlefont = f
# y <- list(
#   title = "Task Number",
#   titlefont = f
# ) 

Read in your data

To make this gantt chart work, you need a column with a date you intend to start the task - we’ll make sure this is formatted in a minute. You also need a column with a duration to generate the length of the bar for each task (this is in days in my case!) and if you want to group and colour code your tasks, it’s the Chapter column which does this.

The Task and Progress columns aren’t necessary, but they are good for labelling and keeping yourself accountable, and an easy way to share updates with people who are checking up on your progress!

df <- read_xlsx(path = "../../../../Book_thesis/00_Time_Plan/timeplan.xlsx", sheet = 1) 
## # A tibble: 6 x 5
##   Task                       start               Duration Chapter Progress
##   <chr>                      <dttm>                 <dbl> <chr>   <chr>   
## 1 Review literature review … 2018-07-03 00:00:00        2 2       Complet…
## 2 2.1 Energy on a larger sc… 2018-07-05 00:00:00        5 2       Complet…
## 3 2.1 Energy in a UK context 2018-07-12 00:00:00        7 2       Complet…
## 4 2.2 Traditional collectio… 2018-07-23 00:00:00        3 2       Complet…
## 5 2.2 New technologies and … 2018-07-26 00:00:00        3 2       Complet…
## 6 2.3 Data Bias and Represe… 2018-07-31 00:00:00        3 2       Complet…

Make sure your date column is correctly formatted

df$start <- as.Date(df$start, format="%Y-%m-%d") 

Next generate a list of colours. This corresponds to my Chapter column, so change this accordingly. It creates a list assigning a colour to each group of tasks

cols <- brewer.pal(length(unique(factor(df$Chapter))), name = "Set3") # Generate a list of colours that are as long as your group of tasks
# This won't work if column has blanks

df$color <- factor(df$Chapter, labels = cols) # Attach these colours as factors to each group of tasks

The next chunk of code generates a date line updated automatically based on your computer’s system date.

# annotation
a <- list(text = "Today's date",
          x = Sys.Date(),
          y = 1.02,
          xref = 'x',
          yref = 'paper',
          xanchor = 'left',
          showarrow = FALSE

# use shapes to create a line
l <- list(type = line,
          x0 = Sys.Date(),
          x1 = Sys.Date(),
          y0 = 0,
          y1 = 1,
          xref = 'x',
          yref = 'paper',
          line = list(color = 'black',
                      width = 0.7)

Build your plot combining all the elements you generated earlier. Change the text section to personalise your chart

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>",
                              "Chapter: ", df$Chapter[i], "<br>",
                              "Status: ", df$Progress[i]), "<br>",
                 evaluate = T

Now simply plot your chart and add axis labels, your title and ‘Today’s date’ - The plotly package will generate an interactive chart that you can zoom, hover and share!

p %>%
  layout(xaxis = x, 
         # yaxis = y,
         title = "Thesis Schedule",
         annotations = a,
         shapes = l)

Ta-Dah! Now all I have to do is stick to it…