Plotly Express Timeline Gantt Chart, color coding based on column in dataframe

Question

I'm trying to create a machine shop schedule that is color coded by parts that belong to the same assembly. I'm using plotly express timeline to create the Gantt. It is reading an excel file on my desktop to generate the schedule. I created a sample below. The goal is to have all the Chair parts be the same color, and all the Desk parts be the same color.

Here's the code to read the excel file and create the Gantt:

df = pd.read_excel(r"C:\Users\john.doe\Documents\Machine Durations - Sample.xlsx")

df['Start Shift'] = df['Start Shift'].astype(int)
df['Finish'] = df['Finish'].astype(int)
#display(df)

# create a slice if the df for the rank = 1
dfRank1 = df[df.Rank == 1]
# reindex it 
dfRank1 = dfRank1.reset_index()
#display(dfRank1)

#Create the visual 

df["Part"] = df["Part"].astype(str)
df["delta"] = df["Finish"]-df["Start Shift"]
fig = px.timeline(df,x_start ="Start Shift", x_end = "Finish", y = "Machine", hover_name ="Part",color = "Part", text = "Part", title = "Machine Shop Cycle", opacity = .75)
fig.update_yaxes(autorange="reversed")
fig.layout.xaxis.type = 'linear'
#fig.data[0].x = df.delta.tolist()
for d in fig.data:
    filt = df['Part'] == d.name
    d.x = df[filt]['delta'].tolist()

fig.update_traces(textposition='inside')    
    
fig.show()

Answer 1

• good practice is paste you data as text into a question
• have made two changes
  1. put Assembly into hover_data so that it is in customdata of each trace
  2. loop through traces to update marker_color based on Assembly in customdata

# update colors to that of the assembly
cmap = {"Chair":"red", "Desk":"blue"}
fig.for_each_trace(lambda t: t.update({"marker":{"color":[cmap[a] for a in t["customdata"][:,0]]}}))

full code

import pandas as pd
import plotly.express as px
import io

df = pd.read_csv(
    io.StringIO(
        """Part,Machine,Duration,Duration Shifts(6),Start Shift,Finish,Index,Assembly,Rank
Legs,Lathe,100,5,0,5,1,Chair,A
Seat,Mill,400,5,0,5,1,Chair,A
Back,Mill,200,3,5,8,1,Chair,A
Legs,Lathe,200,3,5,8,1,Desk,A
Table Top,Mill,200,3,8,11,1,Desk,A
Wheels,Mill-Turn,200,10,0,10,1,Desk,A"""
    )
)

df["Start Shift"] = df["Start Shift"].astype(int)
df["Finish"] = df["Finish"].astype(int)
# display(df)

# create a slice if the df for the rank = 1
dfRank1 = df[df.Rank == 1]
# reindex it
dfRank1 = dfRank1.reset_index()
# display(dfRank1)

# Create the visual

df["Part"] = df["Part"].astype(str)
df["delta"] = df["Finish"] - df["Start Shift"]
fig = px.timeline(
    df,
    x_start="Start Shift",
    x_end="Finish",
    y="Machine",
    hover_name="Part",
    hover_data=["Assembly"], # want this for setting color
    color="Part",
    text="Part",
    title="Machine Shop Cycle",
    opacity=0.75,
)
fig.update_yaxes(autorange="reversed")
fig.layout.xaxis.type = "linear"
# fig.data[0].x = df.delta.tolist()
for d in fig.data:
    filt = df["Part"] == d.name
    d.x = df[filt]["delta"].tolist()

fig.update_traces(textposition="inside")

# update colors to that of the assembly
cmap = {"Chair":"red", "Desk":"blue"}
fig.for_each_trace(lambda t: t.update({"marker":{"color":[cmap[a] for a in t["customdata"][:,0]]}}))

output