How to indicate expected dates and actual dates in a Gantt chart?

user_14773854 0
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I am trying to create a Gantt chart which involves planned and actual start/end dates. I would like same tasks to overlap like:
So far this is my code.

import plotly.figure_factory as ff
import pandas as pd

df = pd.DataFrame([
    dict(Task="Job A", Start='2009-01-01', Finish='2009-02-28'),
    dict(Task="Job A", Start='2009-01-05', Finish='2009-02-15'),
    dict(Task="Job C", Start='2009-02-20', Finish='2009-05-30')
])
colors = {'Job A': 'rgb(220, 0, 0)',
          'Job C': (1, 0.9, 0.16), }

fig = ff.create_gantt(df, colors=colors, index_col="Task", show_colorbar=True, group_tasks=True)
fig.update_yaxes(autorange="reversed")  # otherwise tasks are listed from the bottom up
fig.show()

This is the result: Gantt chart without overlapping colors

How do I distinguish planned v. actual dates? Python, R and Excel solutions are welcome. Usage of Plotly in solutions is completely optional.

plotly gantt-chart r excel python
2 Answers

Here's an R solution:

library(tidyverse)

df %>%
  mutate(Task = factor(Task, rev(levels(factor(Task)))),
         yval = as.numeric(Task)) %>% {
  ggplot(., aes(xmin = Start, xmax = Finish)) + 
  geom_rect(data = filter(., Type == "Planned"), alpha = 0.5,
            aes(ymin = yval - 0.4, ymax = yval + 0.4, fill = "Planned")) +
  geom_rect(data = filter(., Type == "Actual"),
            aes(ymin = yval - 0.2, ymax = yval + 0.2, fill = "Actual"), 
            color = "black") +
  scale_fill_manual("", values = c("deepskyblue4", "olivedrab")) +
  scale_y_continuous(breaks = seq_along(levels(.$Task)),
                     labels = levels(.$Task)) +
  labs(title = "Planned versus actual job times", x = "Date") +
  coord_fixed(15) +
  theme_bw(base_size = 16)
}

enter image description here

Your data should be in the following format for this:

df
#>    Task      Start     Finish    Type
#> 1 Job A 2009-01-01 2009-02-28 Planned
#> 2 Job A 2009-01-05 2009-02-15  Actual
#> 3 Job B 2009-02-01 2009-03-15 Planned
#> 4 Job B 2009-02-10 2009-03-15  Actual
#> 5 Job C 2009-02-20 2009-05-30 Planned
#> 6 Job C 2009-02-22 2009-05-20  Actual

Created on 2022-05-23 by the reprex package (v2.0.1)

user_125003150

You can use Plotly express if you update the width of the 2nd trace.

import plotly.express as px

df = pd.DataFrame([
    dict(Task="Job A", Type="Plan", Start='2009-01-01', Finish='2009-02-28'),
    dict(Task="Job A", Type="Actual", Start='2009-01-05', Finish='2009-02-15'),
    dict(Task="Job C", Type="Plan", Start='2009-02-20', Finish='2009-05-30'),
    dict(Task="Job C", Type="Actual", Start='2009-02-23', Finish='2009-06-04')
])

colours = {}
colours['Plan'] =  'red' # or 'rgb(220, 0, 0)' for rgb colours
colours['Actual'] = 'blue'

fig = px.timeline(df,
                  x_start="Start", 
                  x_end="Finish", 
                  y="Task", 
                  color='Type',
                  color_discrete_map = colours
                     )

fig.data[1].width=0.5 # update the width of the secodn trace

fig.update_yaxes(autorange="reversed") # otherwise tasks are listed from the bottom up

fig.show()

enter image description here

user_20071530
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