Tasks with the same name in Gantt diagram using plotly.express.timeline

Question

Is there a way to separate tasks on a Gantt diagram if they have the same names?

import plotly.express as px
import pandas as pd

df = pd.DataFrame([
    dict(Task="Job A", Start='2009-01-01', Finish='2009-02-28', Worker='Alex'),
    dict(Task="Job B", Start='2009-03-05', Finish='2009-04-15', Worker='John'),
    dict(Task="Job A", Start='2009-02-20', Finish='2009-05-30', Worker='Marc')
])

fig = px.timeline(df, x_start="Start", x_end="Finish", y="Task", color="Worker")
fig.update_yaxes(autorange="reversed") 
fig.show()

I want to show two jobs named "Job A" as separate tasks, not grouping and not in one line using opacity, and preferably not using deprecated plotly.figure_factory.create_gantt. Thanks in advance!

Answer 1

You could do something like this :

df = pd.DataFrame([
    dict(Task="Job A", Start='2009-01-01', Finish='2009-02-28', Worker='Alex'),
    dict(Task="Job B", Start='2009-03-05', Finish='2009-04-15', Worker='John'),
    dict(Task="Job A", Start='2009-02-20', Finish='2009-05-30', Worker='Marc')
])

# Add a column to help identify unique task per worker
df['id'] = df['Task'] + ':' + df['Worker']
df = df.sort_values('id').reset_index()

# Use that column instead
fig = px.timeline(df, x_start="Start", x_end="Finish", y='id', color="Worker")

# Optionally, if you want to preserve original yaxis title and tick labels
fig.update_yaxes(title='Task', tickmode='array', tickvals=df['id'], ticktext=df['Task'])

fig.update_yaxes(autorange="reversed")
fig.show()

Answer 2

It seems there is deprecated function create_gantt() which has option group_tasks=False

import plotly.express as px
import pandas as pd

df = pd.DataFrame([
    dict(Task="Job A", Start='2009-01-01', Finish='2009-02-28', Worker='Alex'),
    dict(Task="Job B", Start='2009-03-05', Finish='2009-04-15', Worker='John'),
    dict(Task="Job A", Start='2009-02-20', Finish='2009-05-30', Worker='Marc')
])

import plotly.figure_factory as ff
fig = ff.create_gantt(df, index_col='Task', group_tasks=False)
fig.update_yaxes(autorange="reversed")
fig.show()

But it is deprecated so some day it may not work.
And it looks little different. It may need other functions to add text and legend.

---

You may have to use unique value in y= - for example df.index (it doesn't have to be converted to string) - and it will put every value in separate row.

Later you have to only use update_yaxes() to replace text (using text=) and labels on y-axis (using ticktext= with tickvals=).

import plotly.express as px
import pandas as pd

df = pd.DataFrame([
    dict(Task="Job A", Start='2009-01-01', Finish='2009-02-28', Worker='Alex'),
    dict(Task="Job B", Start='2009-03-05', Finish='2009-04-15', Worker='John'),
    dict(Task="Job A", Start='2009-02-20', Finish='2009-05-30', Worker='Marc')
])

fig = px.timeline(df, x_start="Start", x_end="Finish", y=df.index, color="Worker")
fig.update_yaxes(autorange="reversed", title='Task', ticktext=df['Task'], tickvals=df.index) 

fig.show()