1

I am trying to make a plotly timeline where the x_start and x_end arguments are such that the x-axis is an integer nr of months instead of a date format. I have tried to use integers or arrays with integers with no luck.

Example code that fails:

df1 = pd.DataFrame(data = {'Task':['T1.1'], 'Start':np.array((1,)), 'Finish':np.array((5,)), 'text':[""], 'WorkPackage':['WP1']})  
fig = px.timeline(df, x_start="Start", x_end="Finish", y="Task", text = "text", color = 'WorkPackage',width = None, height = None)
VG_nbi
  • 51
  • 6
  • 2
    What would you like to display on the xaxis? A continuous timeline with months? Or only months 1-12 with potentially several traces? – vestland Sep 08 '20 at 18:00
  • simply number of months since beginning of project as 1, 2, 3, 4, 5...etc – VG_nbi Sep 09 '20 at 12:23

2 Answers2

0

If you still need help with this, it looks like your question was answered here: Plotly Express timeline for Gantt Chart with integer xaxis?

Using what was suggested in the link, I made the following code and it worked.

# Import libraries
import pandas as pd
import plotly.express as px

# Create some data in a dictionary
mydict = {'Task': ['Task 1', 'Task 2', 'Task 3', 'Task 4'],
          'Start': np.arange(1, 5),
          'Finish': np.arange(6, 10)
         }

# Make a DataFrame object from the dictionary
df = pd.DataFrame(mydict)
          
# Add a column for the delta
df['Delta'] = df['Finish'] - df['Start']

# Create Figure
fig = px.timeline(
    df,
    x_start='Start',
    x_end='Finish',
    y='Task',
    color='Task',
)

# Update the layout
fig.layout.xaxis.type = 'linear'

# I found I needed to do this to get the tasks to show up as differnt colors
for i in np.arange(len(df)):
    fig.data[i].x = df['Delta'].tolist()

# Show the figure
fig.show()

enter image description here

Dharman
  • 30,962
  • 25
  • 85
  • 135
punjabWala81
  • 33
  • 6
0

Thes answer from punjabWala81 does not work as intended when you are using a dict like this, where you have different deltas

mydict = {'Task': ['Task 1', 'Task 2', 'Task 3', 'Task 4'],
          'Start':  [ 1, 2, 3, 4],
          'Finish': [10, 4, 7, 8]
         }

Then you got this

enter image description here

which is not correct.

This is due to the fact, that we got this

enter image description here

To solve this issue we can do this for example

for i in np.arange(len(df)):
    fig.data[i].x = (df['Delta'][i],)
    print(fig.data[i].x)

enter image description here

enter image description here

see as well this post https://stackoverflow.com/a/71141457/7447940

Heiko Averbeck
  • 123
  • 8