Changing the style of Sankey/Alluvial plot with different color palettes for categorical data

Question

I am trying to change the color of Sankey/alluvial plot using Plotly.

Fake data is available here

import plotly.express as px
fake = pd.read_csv('Fake.csv')
fig = px.parallel_categories(fake)
fig.show()

My ideal output - the same plot but colored with different colors based on categories. Cannot find how to apply categorical palettes here.

Answer 1

The categories you have text - RoleA/B/C/D, which are not being taken by the PX color. So, one way to do this is to add a column which will have these values converted to a numerical scale - Role A = 1; Role B = 2, etc. Once done, you can use the continuous color palette you have. Note that I have used the first column (Role 1) to do this as it has data in all columns. Hope this is what you are looking for .... and may the force be with you ;-)

Code

import plotly.express as px
import pandas as pd
fake = pd.read_csv('Fake.csv')

def add_clr(row):
    if row['Role1'] == 'Role A' :
        return 1
    elif row['Role1'] == 'Role B':
        return 2
    elif row['Role1'] == 'Role C':
        return 3
    elif row['Role1'] == 'Role D':
        return 4
    else:
        return 0
        
fake['clr']=fake.apply(add_clr, axis=1) ## New Column with numbers

fig = px.parallel_categories(fake, dimensions=['Role1', 'Role2', 'Role3', 'Role4', 'Role5'],  ## Note Clr column is removed
                             color='clr', color_continuous_scale=px.colors.sequential.Inferno) ## Use any palette u like
fig.show()

.... will give you